Agronomy

Article

15 pages, 2751 KiB

Open AccessEditor’s ChoiceArticle

Industrial Hemp Clone Selection Method under LED Smart Farm Condition Based on CBD Production per Cubic Meter

by Byeong-Ryeol Ryu, Chang-Hyeug Kim, Tae-Hyung Kwon, Joon-Hee Han, Gyeong-Ju Gim, Md Jahirul Islam, Md Obyedul Kalam Azad, Md Hafizur Rahman, Md Soyel Rana, Jung-Dae Lim and Young-Seok Lim

Agronomy 2022, 12(8), 1809; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12081809 - 30 Jul 2022

Cited by 1 | Viewed by 3895

Abstract

Cannabis breeders are combining several genes to develop economically valuable fiber, seed, and medicinal hemp. This study analyzed the characteristics and selection of traits based on cannabidiol production of medicinal cannabis lines successfully grown under artificial light and nutrient solution cultivation conditions in [...] Read more.

Cannabis breeders are combining several genes to develop economically valuable fiber, seed, and medicinal hemp. This study analyzed the characteristics and selection of traits based on cannabidiol production of medicinal cannabis lines successfully grown under artificial light and nutrient solution cultivation conditions in smart farm conditions. Sixteen female plants were selected by seeding medical hemp F1 hybrid specimens obtained by randomly crossing Cherry Wine and native hemp from each country. The F1 generation was treated with 12 h light to induce flower differentiation. CBD production peaked on day 50 of the treatment, and this was selected as the harvesting day. All F1 hybrids were separated by leaf and inflorescence after collecting morphological data, and fresh and dry weights were measured. The CBD production of leaf and inflorescence per cubic meter was calculated. The CW21-5 line produced a total of 53.002 ± 0.228 g of CBD per cubic meter, the highest CBD producer. In addition, heatmap correlation analysis showed that most morphological data were not related to cannabinoid content. Principal Component Analysis (PCA) and Self-Organizing Map (SOM) analysis showed that CW21-5 is an arbitrary line that does not cluster with other lines, and the reason for its excellent CBD yield per cubic meter is that it has a narrow plant diameter and a high CBD content at the same time. Full article

(This article belongs to the Topic Plants Nutrients)

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22 pages, 5949 KiB

Open AccessEditor’s ChoiceArticle

Choosing Feature Selection Methods for Spatial Modeling of Soil Fertility Properties at the Field Scale

by Caner Ferhatoglu and Bradley A. Miller

Agronomy 2022, 12(8), 1786; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12081786 - 29 Jul 2022

Cited by 6 | Viewed by 2138

Abstract

With the growing availability of environmental covariates, feature selection (FS) is becoming an essential task for applying machine learning (ML) in digital soil mapping (DSM). In this study, the effectiveness of six types of FS methods from four categories (filter, wrapper, embedded, and [...] Read more.

With the growing availability of environmental covariates, feature selection (FS) is becoming an essential task for applying machine learning (ML) in digital soil mapping (DSM). In this study, the effectiveness of six types of FS methods from four categories (filter, wrapper, embedded, and hybrid) were compared. These FS algorithms chose relevant covariates from an exhaustive set of 1049 environmental covariates for predicting five soil fertility properties in ten fields, in combination with ten different ML algorithms. Resulting model performance was compared by three different metrics (R² of 10-fold cross validation (CV), robustness ratio (RR; developed in this study), and independent validation with Lin’s concordance correlation coefficient (IV-CCC)). FS improved CV, RR, and IV-CCC compared to the models built without FS for most fields and soil properties. Wrapper (BorutaShap) and embedded (Lasso-FS, Random forest-FS) methods usually led to the optimal models. The filter-based ANOVA-FS method mostly led to overfit models, especially for fields with smaller sample quantities. Decision-tree based models were usually part of the optimal combination of FS and ML. Considering RR helped identify optimal combinations of FS and ML that can improve the performance of DSM compared to models produced from full covariate stacks. Full article

(This article belongs to the Special Issue Geostatistics and Machine Learning in the Mapping of Agricultural Soils: State-of-the-Art and Perspectives)

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16 pages, 552 KiB

Open AccessEditor’s ChoiceArticle

Iron Biofortification of Greenhouse Soilless Lettuce: An Effective Agronomic Tool to Improve the Dietary Mineral Intake

by Camila Vanessa Buturi, Leo Sabatino, Rosario Paolo Mauro, Eloy Navarro-León, Begoña Blasco, Cherubino Leonardi and Francesco Giuffrida

Agronomy 2022, 12(8), 1793; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12081793 - 29 Jul 2022

Cited by 13 | Viewed by 2124

Abstract

The present experiment addressed the effects of different iron (Fe) concentrations in the nutrient solution supplied as Fe-HBED, i.e., 0.02 (Fe0, control), 1.02 (Fe1), and 2.02 mmol L⁻¹ (Fe2) on lettuce (‘Nauplus’ and ‘Romana’) yield and compositional traits. This experiment was carried [...] Read more.

The present experiment addressed the effects of different iron (Fe) concentrations in the nutrient solution supplied as Fe-HBED, i.e., 0.02 (Fe0, control), 1.02 (Fe1), and 2.02 mmol L⁻¹ (Fe2) on lettuce (‘Nauplus’ and ‘Romana’) yield and compositional traits. This experiment was carried out in a greenhouse using an open soilless cultivation system, at the experimental farm of the University of Catania (Sicily, Italy: 37°24′31.5″ N, 15°03′32.8″ E, 6 m a.s.l.). The addition of Fe-HBED reduced the plants’ aboveground biomass (−18%, averaged over Fe1 and Fe2), but promoted their dry matter content (+16% in Fe2). The concentration of chlorophylls, carotenoids, anthocyanins, and antioxidants peaked at Fe2, along with the antioxidant capacity and concentration of stress indicators in leaves. The Fe content in leaves was promoted in the Fe-treated plants (+187% averaged over Fe1 and Fe2). ‘Romana’ showed the highest Fe accumulation (reaching 29.8 mg kg⁻¹ FW in Fe1), but ‘Nauplus’ proved a higher tolerance to the Fe-derived oxidative stress. The Fe2 treatment maximized leaf N, P, K, S, and Zn contents, while those of Ca, Mg, Mn, and B peaked at Fe1. Overall, our study revealed the effectiveness of Fe-HBED in increasing the Fe content and improving the nutritional quality of lettuce grown in soilless cultivation systems. Full article

(This article belongs to the Special Issue Biofortification of Field Crops)

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17 pages, 4387 KiB

Open AccessEditor’s ChoiceArticle

Investigating Stability Parameters for Agronomic and Quality Traits of Durum Wheat Grown under Mediterranean Conditions

by Angelos C. Kyratzis, Andreas Pallides and Andreas Katsiotis

Agronomy 2022, 12(8), 1774; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12081774 - 28 Jul 2022

Cited by 10 | Viewed by 1746

Abstract

Durum wheat in the Mediterranean grows under rainfed conditions, where unpredictable climatic conditions result in substantial variation in grain yield and quality. Climate change intensifies Genotype × Environment interactions and urges breeders to escalate their efforts to breed cultivars combining high performance and [...] Read more.

Durum wheat in the Mediterranean grows under rainfed conditions, where unpredictable climatic conditions result in substantial variation in grain yield and quality. Climate change intensifies Genotype × Environment interactions and urges breeders to escalate their efforts to breed cultivars combining high performance and stability. The current study aimed to appraise the relations between twelve stability parameters derived by different statistical models for yield, yield-related and quality traits of durum wheat grown under Mediterranean conditions. Stability parameters were estimated in two experiments of twenty and sixteen cultivars, respectively. The parameters were categorized into three groups. Group A included Additive Main Effect and Multiplicative Interaction (AMMI)-derived parameters (ASV and AWAI), Wrickle’s ecovalence (Wi), Shukla’s stability variance (σ²), and the nonparametric parameters Si₍₁₎ and Si₍₂₎. Group B included regression parameters (bi, Bi_A), Coefficient of Variance (CV), and Superiority measure (Pi). Group C encompassed deviation from regression parameters (s²di-DJi) when the heterogeneity of the slope was significant. Correlations between stability parameters for different traits and the between stability parameters and the traits per se were modest. Stability parameters of Group B had higher repeatability for grain yield. The results of the present study contribute to the adjustment of durum wheat breeding strategies. Full article

(This article belongs to the Special Issue Current Status and Future Prospects of Genotype X Environment Interaction in Plant Breeding and Crop Adaptation)

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19 pages, 816 KiB

Open AccessEditor’s ChoiceArticle

Diet Composition Influences Growth Performance, Bioconversion of Black Soldier Fly Larvae: Agronomic Value and In Vitro Biofungicidal Activity of Derived Frass

by Ghazaleh Arabzadeh, Maxime Delisle-Houde, Russell J. Tweddell, Marie-Hélène Deschamps, Martine Dorais, Yolaine Lebeuf, Nicolas Derome and Grant Vandenberg

Agronomy 2022, 12(8), 1765; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12081765 - 27 Jul 2022

Cited by 25 | Viewed by 5023

Abstract

In recent years, the larval stage of Hermetia illucens, commonly known as the black soldier fly (BSFL), has been used to promote the circularity of the agri-food sector by bioconverting organic waste into larval biomass which has been used as a livestock [...] Read more.

In recent years, the larval stage of Hermetia illucens, commonly known as the black soldier fly (BSFL), has been used to promote the circularity of the agri-food sector by bioconverting organic waste into larval biomass which has been used as a livestock feed. A secondary byproduct of this process is frass that can be used as an organic fertilizer. This study compared two different plant-based diets on frass characteristics as well as larval performance, nutritional composition, and waste reduction efficiency. A fruit/vegetable/bakery waste-based diet supplemented with brewery waste (FVBB) was compared to a control Gainesville (GV) reference diet and fed to BSFL under standard conditions. The results demonstrated that NPK and some of the macro and micronutrients in both frasses are comparable to commercially available organic fertilizers. It was shown that microorganisms present in frass from the two diets inhibit the mycelial growth of several plant pathogens through the production of antifungal and/or anti-oomycetes compound(s) (antibiosis). This diet also had a positive effect on individual larval mass (162.11 mg), bioconversion rate (13.32%), and larval crude lipid (35.99% of dry matter) content. The BSFL reared on this diet reduced feedstock dry matter by 67.76% in a very short time (10 days), which is a promising solution for food waste management. Full article

(This article belongs to the Special Issue Agroecology and Organic Horticulture)

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12 pages, 2585 KiB

Open AccessEditor’s ChoiceArticle

Effects of Tertill^® Weeding Robot on Weed Abundance and Diversity

by Kristine M. Averill, Anna S. Westbrook, Laura Pineda-Bermudez, Ryan P. O’Briant, Antonio DiTommaso and Matthew R. Ryan

Agronomy 2022, 12(8), 1754; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12081754 - 26 Jul 2022

Cited by 6 | Viewed by 3047

Abstract

Robotic weed control may reduce labor requirements, soil disturbance, and amount of herbicide applied relative to non-robotic methods. Tertill^® is among the first weeding robots to become commercially available. This solar-powered robot moves in a random walk, avoiding obstacles using capacitive sensors, [...] Read more.

Robotic weed control may reduce labor requirements, soil disturbance, and amount of herbicide applied relative to non-robotic methods. Tertill^® is among the first weeding robots to become commercially available. This solar-powered robot moves in a random walk, avoiding obstacles using capacitive sensors, and cuts weeds with a string trimmer. We tested the effects of Tertill (two hours per week) with and without the string trimmer and hand weeding (from 3 to 5.6 min per week with a stirrup hoe) on weed communities at two field sites in Ithaca, NY. Tertill with trimmer and hand weeding provided similar levels of weed control (visual estimates averaging 2–9% ground cover at the end of the experiment, compared to 14–48% in the unweeded control). Without the string trimmer, Tertill was ineffective. Tertill did not significantly reduce monocot weed density but did reduce dicot weed density. At one site, Tertill reduced species richness and increased evenness based on density. Overall, these results suggest that Tertill can effectively remove newly emerged weed seedlings. Future research should investigate Tertill performance against more established weeds and the long-term effects of Tertill on weed community composition (e.g., possible selection for monocots and other species with low growing points). Full article

(This article belongs to the Special Issue Robotic Weeding)

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20 pages, 7505 KiB

Open AccessEditor’s ChoiceArticle

Real-Time Localization and Mapping Utilizing Multi-Sensor Fusion and Visual–IMU–Wheel Odometry for Agricultural Robots in Unstructured, Dynamic and GPS-Denied Greenhouse Environments

by Yaxuan Yan, Baohua Zhang, Jun Zhou, Yibo Zhang and Xiao’ang Liu

Agronomy 2022, 12(8), 1740; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12081740 - 23 Jul 2022

Cited by 30 | Viewed by 5433

Abstract

Autonomous navigation in greenhouses requires agricultural robots to localize and generate a globally consistent map of surroundings in real-time. However, accurate and robust localization and mapping are still challenging for agricultural robots due to the unstructured, dynamic and GPS-denied environmental conditions. In this [...] Read more.

Autonomous navigation in greenhouses requires agricultural robots to localize and generate a globally consistent map of surroundings in real-time. However, accurate and robust localization and mapping are still challenging for agricultural robots due to the unstructured, dynamic and GPS-denied environmental conditions. In this study, a state-of-the-art real-time localization and mapping system was presented to achieve precise pose estimation and dense three-dimensional (3D) point cloud mapping in complex greenhouses by utilizing multi-sensor fusion and Visual–IMU–Wheel odometry. In this method, measurements from wheel odometry, an inertial measurement unit (IMU) and a tightly coupled visual–inertial odometry (VIO) are integrated into a loosely coupled framework based on the Extended Kalman Filter (EKF) to obtain a more accurate state estimation of the robot. In the multi-sensor fusion algorithm, the pose estimations from the wheel odometry and IMU are treated as predictions and the localization results from VIO are used as observations to update the state vector. Simultaneously, the dense 3D map of the greenhouse is reconstructed in real-time by employing the modified ORB-SLAM2. The performance of the proposed system was evaluated in modern standard solar greenhouses with harsh environmental conditions. Taking advantage of measurements from individual sensors, our method is robust enough to cope with various challenges, as shown by extensive experiments conducted in the greenhouses and outdoor campus environment. Additionally, the results show that our proposed framework can improve the localization accuracy of the visual–inertial odometry, demonstrating the satisfactory capability of the proposed approach and highlighting its promising applications in autonomous navigation of agricultural robots. Full article

(This article belongs to the Special Issue AI, Sensors and Robotics for Smart Agriculture)

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14 pages, 3098 KiB

Open AccessEditor’s ChoiceArticle

Insect Pest Image Recognition: A Few-Shot Machine Learning Approach including Maturity Stages Classification

by Jacó C. Gomes and Díbio L. Borges

Agronomy 2022, 12(8), 1733; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12081733 - 22 Jul 2022

Cited by 15 | Viewed by 4487

Abstract

Recognizing insect pests using images is an important and challenging research issue. A correct species classification will help choosing a more proper mitigation strategy regarding crop management, but designing an automated solution is also difficult due to the high similarity between species at [...] Read more.

Recognizing insect pests using images is an important and challenging research issue. A correct species classification will help choosing a more proper mitigation strategy regarding crop management, but designing an automated solution is also difficult due to the high similarity between species at similar maturity stages. This research proposes a solution to this problem using a few-shot learning approach. First, a novel insect data set based on curated images from IP102 is presented. The IP-FSL data set is composed of 97 classes of adult insect images, and 45 classes of early stages, totalling 6817 images. Second, a few-shot prototypical network is proposed based on a comparison with other state-of-art models and further divergence analysis. Experiments were conducted separating the adult classes and the early stages into different groups. The best results achieved an accuracy of 86.33% for the adults, and 87.91% for early stages, both using a Kullback–Leibler divergence measure. These results are promising regarding a crop scenario where the more significant pests are few and it is important to detect them at earlier stages. Further research directions would be in evaluating a similar approach in particular crop ecosystems, and testing cross-domains. Full article

(This article belongs to the Special Issue Remote Sensing, GIS, and AI in Agriculture)

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19 pages, 4661 KiB

Open AccessEditor’s ChoiceArticle

DEM-MBD Coupling Simulation and Analysis of the Working Process of Soil and Tuber Separation of a Potato Combine Harvester

by Yuyao Li, Zhichao Hu, Fengwei Gu, Bing Wang, Jiali Fan, Hongguang Yang and Feng Wu

Agronomy 2022, 12(8), 1734; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12081734 - 22 Jul 2022

Cited by 15 | Viewed by 2404

Abstract

To address the competing relationship between tuber damage and soil removal in potato combine harvesting, this study investigated the operating mechanism of a belt-rod type separator of a small-scale self-propelled potato combine harvester and the separation performance between tuber and soil. The main [...] Read more.

To address the competing relationship between tuber damage and soil removal in potato combine harvesting, this study investigated the operating mechanism of a belt-rod type separator of a small-scale self-propelled potato combine harvester and the separation performance between tuber and soil. The main factors affecting the tuber-soil separation characteristics were derived from a theoretical analysis of the belt-rod angle, belt-rod linear velocity, and harvester forward speed. A simulation model based on DEM (Discrete Element Method)-MBD (Multibody Dynamics) coupling was constructed and single-factor simulation tests were carried out. Then a three-factor, three-level Box–Behnken test was conducted using the coefficient of force on the tuber and soil clearing rate as response indicators. The optimal combination of parameters resulting in low tuber damage and high soil clearing rate was obtained by solving the regression equations. The optimal parameters were a belt-rod angle of 17.5°, a belt-rod linear velocity of 1.37 m/s, and a harvester forward speed of 0.80 m/s. The simulation model was validated by field experiments and the error between the simulation model and the field harvest was found to be 3.81%. The results can be used as a reference for parameter optimization of small-scale potato combine harvesters and coupled DEM-MBD simulation of tuber-soil separation. Full article

(This article belongs to the Special Issue Research on Key Technologies of Planting Machinery and Combine Harvester)

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17 pages, 19098 KiB

Open AccessEditor’s ChoiceArticle

Estimation of Leaf Area Index and Above-Ground Biomass of Winter Wheat Based on Optimal Spectral Index

by Zijun Tang, Jinjin Guo, Youzhen Xiang, Xianghui Lu, Qian Wang, Haidong Wang, Minghui Cheng, Han Wang, Xin Wang, Jiaqi An, Ahmed Abdelghany, Zhijun Li and Fucang Zhang

Agronomy 2022, 12(7), 1729; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12071729 - 21 Jul 2022

Cited by 29 | Viewed by 3828

Abstract

Leaf area index (LAI) and above-ground biomass are both vital indicators for evaluating crop growth and development, while rapid and non-destructive estimation of crop LAI and above-ground biomass is of considerable significance for crop field management. Owing to the advantages of repeatable and [...] Read more.

Leaf area index (LAI) and above-ground biomass are both vital indicators for evaluating crop growth and development, while rapid and non-destructive estimation of crop LAI and above-ground biomass is of considerable significance for crop field management. Owing to the advantages of repeatable and high-throughput observations, spectral technology provides a feasible method for obtaining LAI and above-ground biomass of crops. In the present study, the spectral, LAI and above-ground biomass data of winter wheat were collected, and 7 species (14 in total) were calculated based on the original and first-order differential spectrum correlation spectral indices with LAI. Then, the correlation matrix method was used for correlation with LAI. The optimal wavelength combination was extracted, and the results were calculated as the optimal spectral index related to LAI. The calculation process of the optimal spectral index related to above-ground biomass was the same as that aforementioned. Finally, the optimal spectral index was divided into three groups of model input variables, winter wheat LAI and above-ground biomass estimation models were constructed using support vector machine (SVM), random forest (RF) and a back propagation neural network (BPNN), and the models were verified. The results show that the correlation coefficient between the highest of the optimal spectral indices, the LAI, and the above-ground biomass of winter wheat exceeded 0.6, and the correlation was good. The methods for establishing the optimal estimation models for LAI and above-ground biomass of winter wheat are all modeling methods in which the input variables are the combination of the first-order differential spectral index (combination 2) and RF. The R² of the LAI estimation model validation set was 0.830, the RMSE was 0.276, and the MRE was 6.920; the R² of the above-ground biomass estimation model validation set was 0.682, RMSE was 235.016, MRE was 4.336, and the accuracies of both models were high. The present research results can provide a theoretical basis for crop monitoring based on spectral technology and provide an application reference for the rapid estimation of crop growth parameters. Full article

(This article belongs to the Special Issue Current Research on Hyperspectral and Multispectral Imaging and Their Applications in Precision Agriculture)

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17 pages, 309 KiB

Open AccessEditor’s ChoiceArticle

Fermentation Quality of Silages Produced from Wilted Sown Tropical Perennial Grass Pastures with or without a Bacterial Inoculant

by John W. Piltz, Richard G. Meyer, Mark A. Brennan and Suzanne P. Boschma

Agronomy 2022, 12(7), 1721; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12071721 - 21 Jul 2022

Cited by 3 | Viewed by 1744

Abstract

High growth rates and rapid reproductive development and associated decline in feed quality of sown tropical perennial grass pastures present management challenges for livestock producers. Conservation of surplus forage as silage could be an effective management tool. Experiments were conducted to evaluate the [...] Read more.

High growth rates and rapid reproductive development and associated decline in feed quality of sown tropical perennial grass pastures present management challenges for livestock producers. Conservation of surplus forage as silage could be an effective management tool. Experiments were conducted to evaluate the fermentation quality of silages produced from tropical grasses. Five species (Chloris gayana, Megathyrsus maximus, Panicum coloratum, Digitaria eriantha and Cenchrus clandestinus) were ensiled without additives after a short, effective wilt at dry matter (DM) contents ranging from 302.4 to 650.1 g kg⁻¹. The fermentation profile of all silages in 2019 was typical for high DM silages, but in 2020 ammonia (% of total nitrogen: NH₃-N), acetic acid and pH levels were higher. In 2020 M. maximus (302.4 g kg⁻¹ DM) was poorly preserved with 20.2% NH₃-N. The DM content of all other silages exceeded 350 g kg⁻¹ and fermentation quality was generally good. In a second experiment, M. maximus was ensiled at 365 g kg⁻¹ chopped and 447 g kg⁻¹ DM chopped and unchopped, either without or with Pioneer 1171^® (Lactobacillus plantarum and Enterococcus faecium) or Lallemand Magniva Classic^® (L. plantarum and Pediococcus pentasaceus) bacterial inoculant. Inoculants increased lactic acid production, reduced pH and improved fermentation compared to Control, but D-lactate, L-lactate and acetic acid production differed between inoculants. Unchopped silages had higher pH and NH₃-N and better preserved protein fraction than chopped silages at the same DM content. In both experiments, wilting increased water soluble carbohydrates by 0.5–31.5 g kg⁻¹ DM and ensiling increased degradation of the protein fraction. We concluded that a rapid and effective wilt combined with a bacterial additive resulted in well preserved tropical grass silages. Full article

(This article belongs to the Special Issue Research Progress and Future Perspectives of Silage)

18 pages, 3394 KiB

Open AccessEditor’s ChoiceArticle

Simulation Parameter Calibration and Test of Typical Pear Varieties Based on Discrete Element Method

by Guiju Fan, Siyu Wang, Wenjie Shi, Zhenfeng Gong and Ming Gao

Agronomy 2022, 12(7), 1720; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12071720 - 21 Jul 2022

Cited by 9 | Viewed by 1803

Abstract

To improve the accuracy of discrete element simulation parameters for the mechanized picking and collection of pears, the study calibrated the simulation parameters of pears by the method of combining a physical experiment and simulation. Based on the intrinsic parameters of four kinds [...] Read more.

To improve the accuracy of discrete element simulation parameters for the mechanized picking and collection of pears, the study calibrated the simulation parameters of pears by the method of combining a physical experiment and simulation. Based on the intrinsic parameters of four kinds of pears (Snow pears, Crisp pears, Huangguan pears and Qiuyue pears), their simulation models were constructed by the Hertz-Mindlin with a bonding model. The simulation parameters between pears and the contact material (PVC, EVA foam material) were calibrated by the methods of free fall collision, inclined sliding and rolling, respectively. The experiments of pear accumulation angle were carried out. It was obtained to process the image of pears with Matrix Laboratory software. In order to determine the optimal value interval of influencing factors of the pear accumulation angle, the steepest ascent experiment was carried out. Considering the coefficient of collision recovery, the coefficient of static friction and the coefficient of rolling friction between pears, five-level simulation experiments of the pear accumulation angle were designed for each factor by the method of orthogonal rotation combination. The regression model of the error between the measured value and the simulated value of the pear accumulation angle was established, and the influence of three factors on the pear accumulation angle was analyzed. The results showed that the static friction coefficient and rolling friction coefficient between pears have significant effects on the pear accumulation angle. Therefore, the optimal model of minimum error was constructed according to constraint condition, and the coefficient of collision recovery, coefficient of static friction and coefficient of rolling friction between pears were obtained. The accumulation angle verification experiments were carried out by the method of bottomless barrel lifting. The results showed that the relative error between the simulated and measured accumulation angle of four kinds of pears were 1.42%, 1.68%, 2.19% and 1.83%, respectively, which indicated that the calibrated simulation parameters were reliable. The research can provide a basis for the design and parameters optimization of harvesting machinery of pears. Full article

(This article belongs to the Special Issue Advances in Modelling Cropping Systems to Improve Yield and Quality)

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15 pages, 997 KiB

Open AccessEditor’s ChoiceArticle

Phenotypic Variability, Heritability and Associations of Agronomic and Quality Traits in Cultivated Ethiopian Durum Wheat (Triticum turgidum L. ssp. Durum, Desf.)

by Temesgen Dagnaw, Behailu Mulugeta, Teklehaimanot Haileselassie, Mulatu Geleta and Kassahun Tesfaye

Agronomy 2022, 12(7), 1714; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12071714 - 20 Jul 2022

Cited by 9 | Viewed by 2421

Abstract

Quality is an important aspect of durum wheat in the processing sector. Thus, recognizing the variability of quality and agronomic traits and their association is fundamental in designing plant breeding programs. This study aimed to assess the variability, heritability, genetic advance, and correlation [...] Read more.

Quality is an important aspect of durum wheat in the processing sector. Thus, recognizing the variability of quality and agronomic traits and their association is fundamental in designing plant breeding programs. This study aimed to assess the variability, heritability, genetic advance, and correlation of some agronomic and quality traits among 420 Ethiopian durum wheat genotypes and to identify the promising genotypes with distinct processing quality attributes to produce superior quality pasta. The field experiment was conducted at two locations (Sinana and Chefe Donsa) using an alpha lattice design with two replications. Analysis of variance, chi-square test, and Shannon–Weaver diversity index revealed the existence of highly significant (p < 0.001) variation among genotypes for all studied traits. The broad-sense heritability values were ranging from 46.2% (days to maturity) to 81% (thousand kernel weight) with the genetic advance as a percent of the mean ranging from 1.1% (days to maturity) to 21.2% (grain yield). The phenotypic correlation coefficients for all possible pairs of quantitative traits showed a significant (p < 0.05) association among most paired traits. The gluten content (GC) and grain protein content (GPC) were negatively correlated with grain yield and yield-related traits and positively associated with phenological traits, while yield and phenological traits correlated negatively. The frequency distributions of amber-colored and vitreous kernels, which are preferable characters of durum wheat in processing, were highly dominant in Ethiopian durum wheat genotypes. The identified top 5% genotypes, which have amber color and vitreous kernel with high GC and GPC content as well as sufficient grain yield, could be directly used by the processing sector and/or as donors of alleles in durum wheat breeding programs. Full article

(This article belongs to the Special Issue Crop Landraces: Resources, Conservation, and Utilization)

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20 pages, 2407 KiB

Open AccessEditor’s ChoiceArticle

Genetic Pool of the Cultivated Pear Tree (Pyrus spp.) in the Canary Islands (Spain), Studied Using SSR Molecular Markers

by María Encarnación Velázquez-Barrera, Ana María Ramos-Cabrer, Santiago Pereira-Lorenzo and Domingo José Ríos-Mesa

Agronomy 2022, 12(7), 1711; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12071711 - 20 Jul 2022

Cited by 8 | Viewed by 2160

Abstract

The Canary Islands have an enormous richness of crops and varieties, many of them traditional or local, selected for decades by farmers based on the most desirable characteristics. Pear trees were introduced to the Canary Islands presumably in the first years after their [...] Read more.

The Canary Islands have an enormous richness of crops and varieties, many of them traditional or local, selected for decades by farmers based on the most desirable characteristics. Pear trees were introduced to the Canary Islands presumably in the first years after their Conquest in the 15th century, reaching a high degree of diversification. In this study, to determine the genetic identity of the genus Pyrus in the Canary Islands for conservation purposes, 266 pear accessions from the islands of Tenerife, La Palma and Gran Canaria were characterized with 18 SSRs, in addition to 190 genotypes from Galicia, Asturias, wild and commercial varieties as references to detect possible synonyms, genetic relationships and the possible genetic structure. We identified 310 unique genotypes, both diploid and putative triploid, 120 of them present only in the Canary Islands (39%, with 50% clonality). The population structure of the genotypes was analyzed by STRUCTURE 2.3.4 software (Pritchard Lab, Stanford University, Stanford, CA, USA). The dendrogram, by using the Jaccard coefficient and principal component analysis (PCoA), separated the analyzed genotypes into stable groups. One of these groups was formed only by Canarian varieties present at lower altitudes, showing adaptation to low chilling requirements with a significant positive correlation (0.432, p < 0.01). This first study of the pear germplasm in the Canary Islands reflects the importance of the group of local cultivars and their need for conservation given they are adapted to their peculiar climatic conditions and have a low number of chill units. Full article

(This article belongs to the Collection Genetic Diversity Evaluation of the Fruit Trees)

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15 pages, 1565 KiB

Open AccessEditor’s ChoiceArticle

Stoichiometry of Soil, Microorganisms, and Extracellular Enzymes of Zanthoxylum planispinum var. dintanensis Plantations for Different Allocations

by Yitong Li, Yanghua Yu and Yanping Song

Agronomy 2022, 12(7), 1709; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12071709 - 19 Jul 2022

Cited by 6 | Viewed by 1815

Abstract

Plantations with different allocation patterns significantly affect soil elements, microorganisms, extracellular enzymes, and their stoichiometric characteristics. Rather than studying them as a continuum, this study used four common allocations of plantations: Zanthoxylum planispinum var. dintanensis (hereafter Z. planispinum) + Prunus salicina, [...] Read more.

Plantations with different allocation patterns significantly affect soil elements, microorganisms, extracellular enzymes, and their stoichiometric characteristics. Rather than studying them as a continuum, this study used four common allocations of plantations: Zanthoxylum planispinum var. dintanensis (hereafter Z. planispinum) + Prunus salicina, Z. planispinum + Sophora tonkinensis, Z. planispinum + Arachis hypogaea, and Z. planispinum + Lonicera japonica plantations, as well as a single-stand Z. planispinum plantation as a control. Soil samples from depths of 0–10 and 10–20 cm at the five plantations were used to analyze the element stoichiometry, microorganisms and extracellular enzymes. (1) One-way analysis of variance (ANOVA) showed that the contents of soil organic carbon (C), nitrogen (N), phosphorus (P), and potassium (K) of Z. planispinum + L. japonica plantation were high, while those of calcium (Ca) and magnesium (Mg) were low compared to the Z. planispinum pure plantation; soil microbial and enzyme activities were also relatively high. Stoichiometric analysis showed that soil quality was good and nutrient contents were high compared to the other plantations, indicating that this was the optimal plantation. (2) Two-way ANOVA showed that stoichiometry was more influenced by plantation type than soil depth and their interaction, suggesting that plantation type significantly affected the ecosystem nutrient cycle; soil microbial biomass (MB) C:MBN:MBP was not sensitive to changes in planting, indicating that MBC:MBN:MBP was more stable than soil C:N:P, which can be used to diagnose ecosystem nutrient constraints. (3) Pearson’s correlation and standardized major axis analyses showed that there was no significant correlation between soil C:N:P and MBC:MBN:MBP ratios in this study; moreover, MBN:MBP had significant and extremely significant correlations with MBC:MBN and MBC:MBP. Fitting the internal stability model equation of soil nutrient elements and soil MBC, MBN, and MBP failed (p > 0.05), and the MBC, MBN, and MBP and their stoichiometric ratios showed an absolute steady state. This showed that, in karst areas with relative nutrient deficiency, soil microorganisms resisted environmental stress and showed a more stable stoichiometric ratio. Overall stoichiometric characteristics indicated that the Z. planispinum + L. japonica plantation performed best. Full article

(This article belongs to the Special Issue Emerging Research on Adaptive Plants in Karst Ecosystems)

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20 pages, 1236 KiB

Open AccessEditor’s ChoiceArticle

Effects of Daily Light Integral on Compact Tomato Plants Grown for Indoor Gardening

by Stephanie Cruz and Celina Gómez

Agronomy 2022, 12(7), 1704; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12071704 - 19 Jul 2022

Cited by 6 | Viewed by 3622

Abstract

Our objective was to characterize the growth, physiological responses, fruit yield, and quality of tomato (Solanum lycopersicum L.) plants grown under different daily light integrals (DLIs) and photoperiods. In experiment I, nine compact tomato cultivars were grown indoors using broadband white light-emitting [...] Read more.

Our objective was to characterize the growth, physiological responses, fruit yield, and quality of tomato (Solanum lycopersicum L.) plants grown under different daily light integrals (DLIs) and photoperiods. In experiment I, nine compact tomato cultivars were grown indoors using broadband white light-emitting diode (LED) fixtures. Plants were grown under low (10.4 mol·m⁻²·d⁻¹) and high (18.4 mol·m⁻²·d⁻¹) DLIs with 12 and 16 h photoperiods, respectively, and two intermediate DLIs of 13.8 mol·m⁻²·d⁻¹ with either 12 or 16 h photoperiods. In experiment II, three compact tomato cultivars were grown under the same low DLI with either 8 or 12 h photoperiods, and the same high DLI with either 12 or 16 h photoperiods. Generally, higher DLIs decreased plant growth and increased the fruit yield. Changing the DLI delivery strategy by adjusting the photoperiod and photosynthetic photon flux density (PPFD) did not have major effects on the growth, yield, and fruit quality of the compact tomato plants evaluated in this study, even though net photosynthesis increased under higher PPFDs in experiment II. Although several cultivars were affected by intumescence, only two cultivars showed treatment responses, for which the severity was generally higher in lower PPFDs using the same DLI. Full article

(This article belongs to the Special Issue Growing Food in Cities: Rooftops, Window Sills, Vertical Farms, Urban Agroecology)

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16 pages, 9609 KiB

Open AccessEditor’s ChoiceArticle

Research on Hydraulic Properties and Energy Dissipation Mechanism of the Novel Water-Retaining Labyrinth Channel Emitters

by Yanfei Li, Xianying Feng, Yandong Liu, Xingchang Han, Haiyang Liu, Yitian Sun, Hui Li and Yining Xie

Agronomy 2022, 12(7), 1708; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12071708 - 19 Jul 2022

Cited by 10 | Viewed by 1605

Abstract

As a key component of a drip irrigation system, the performance of the drip irrigation emitters is mainly determined by the flow channel structures and structural parameters. In this study, a novel type of circular water-retaining labyrinth channel (CWRLC) structure emitter was proposed, [...] Read more.

As a key component of a drip irrigation system, the performance of the drip irrigation emitters is mainly determined by the flow channel structures and structural parameters. In this study, a novel type of circular water-retaining labyrinth channel (CWRLC) structure emitter was proposed, inspired by the effect of roundabouts that make vehicles slow down and turn. Using the single-factor experiment method, the influence of the hydraulic performance of CWRLC emitters was researched under different circular radii. The internal flow characteristics and energy dissipation mechanism were analyzed by a computational fluid dynamics (CFD) simulation. It can be seen from the analysis that the energy dissipation abilities of the flow channel depend on the proportion of low-speed vortex areas. The larger the proportion of low-speed vortex areas, the smaller the flow index of the CWRLC emitter. Quadrate water-retaining labyrinth channel (QWRLC) and stellate water-retaining labyrinth channel (SWRLC) structures were obtained by structural improvements for increasing the proportion of low-speed vortex areas. The simulation results showed that the flow indexes of two improved structural emitters were significantly decreased. CWRLC, QWRLC, SWRLC, and widely used tooth labyrinth channel (TLC) emitters were manufactured by using technologies of electrical discharge machining (EDM) and injection molding (IM). The physical test results showed that the SWRLC emitter achieved the best hydraulic performance compared with the other three emitters. Therefore, the SWRLC emitter has a broad prospect of application in water-saving irrigation. Full article

(This article belongs to the Special Issue Agricultural Water Conservation: Tools, Strategies, and Practices - Series II)

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13 pages, 936 KiB

Open AccessEditor’s ChoiceArticle

Large-Effect QTLs for Titratable Acidity and Soluble Solids Content Validated in ‘Honeycrisp’-Derived Apple Germplasm

by Baylee A. Miller, Sarah A. Kostick and James J. Luby

Agronomy 2022, 12(7), 1703; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12071703 - 19 Jul 2022

Cited by 2 | Viewed by 2492

Abstract

Fruit acidity and sweetness are important fruit quality traits in the apple and are therefore targets in apple breeding programs. Multiple quantitative trait loci (QTLs) associated with titratable acidity (TA) and soluble solids content (SSC) have been previously detected. In this study a [...] Read more.

Fruit acidity and sweetness are important fruit quality traits in the apple and are therefore targets in apple breeding programs. Multiple quantitative trait loci (QTLs) associated with titratable acidity (TA) and soluble solids content (SSC) have been previously detected. In this study a pedigree-based QTL analysis approach was used to validate QTLs associated with TA and SSC in a ‘Honeycrisp’-derived germplasm set. TA and SSC data collected from 2014 to 2018 and curated genome-wide single nucleotide polymorphism (SNP) data were leveraged to validate three TA QTLs on linkage groups (LGs) 1, 8, and 16 and three SSC QTLs on LGs 1, 13, and 16. TA and SSC QTL haplotypes were characterized in six University of Minnesota apple breeding families representing eight breeding parents including ‘Honeycrisp’ and ‘Minneiska’. Six high-TA haplotypes, four low-TA haplotypes, 14 high-SSC haplotypes, and eight low-SSC haplotypes were characterized. The results of this study will enable more informed selection in apple breeding programs. Full article

(This article belongs to the Special Issue DNA-Informed Breeding in Fruit and Nut Crops)

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17 pages, 2209 KiB

Open AccessEditor’s ChoiceArticle

Optimized Phosphorus Application Alleviated Adverse Effects of Short-Term Low-Temperature Stress in Winter Wheat by Enhancing Photosynthesis and Improved Accumulation and Partitioning of Dry Matter

by Hui Xu, Zhaochen Wu, Bo Xu, Dongyue Sun, Muhammad Ahmad Hassan, Hongmei Cai, Yu Wu, Min Yu, Anheng Chen, Jincai Li and Xiang Chen

Agronomy 2022, 12(7), 1700; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12071700 - 18 Jul 2022

Cited by 13 | Viewed by 2175

Abstract

Low-temperature stress has become an important abiotic factor affecting high and stable wheat production. Therefore, it is necessary to take appropriate measures to enhance low-temperature tolerance in wheat. A pot experiment was carried out using Yannong19 (YN19, a cold-tolerant cultivar) and Xinmai26 (XM26, [...] Read more.

Low-temperature stress has become an important abiotic factor affecting high and stable wheat production. Therefore, it is necessary to take appropriate measures to enhance low-temperature tolerance in wheat. A pot experiment was carried out using Yannong19 (YN19, a cold-tolerant cultivar) and Xinmai26 (XM26, a cold-sensitive cultivar). We employed traditional phosphorus application (TPA, i.e., R1) and optimized phosphorus application (OPA, i.e., R2) methods. Plants undertook chilling (T1 at 4 °C) and freezing treatment (T2 at −4 °C) as well as ambient temperature (CK at 11 °C) during the anther differentiation period to investigate the effects of OPA and TPA on photosynthetic parameters and the accumulation and distribution of dry matter. The net photosynthetic rate (Pn), stomatal conductance (Gs) and transpiration rate (Tr) of flag leaves decreased in low-temperature treatments, whereas intercellular carbon dioxide concentration (Ci) increased. Compared with R1CK, Pn in R1T1 and R1T2 treatments was reduced by 26.8% and 42.2% in YN19 and 34.2% and 54.7% in XM26, respectively. In contrast, it increased by 6.5%, 8.9% and 12.7% in YN19 and 7.7%, 15.6% and 22.6% in XM26 for R2CK, R2T1 and R2T2 treatments, respectively, under OPA compared with TPA at the same temperature treatments. Moreover, low-temperature stress reduced dry matter accumulation at the reproductive growth stage. OPA increased dry matter accumulation of vegetative organs after the flowering stage and promoted the transportation of assimilates to grains. Hence, the grain number per spike (GNPS), 1000-grain weight (TGW) and yield per plant (YPP) increased. The low-temperature treatments of T1 and T2 caused yield losses of 24.1~64.1%, and the yield increased by 8.6~20.5% under OPA treatments among the two wheat cultivars. In brief, OPA enhances low-temperature tolerance in wheat, effectively improves wheat architecture and photosynthesis, increases GNPS and TGW and ultimately lessens yield losses. Full article

(This article belongs to the Special Issue Strategizing Agricultural Management for Climate Change Adaptation and Mitigation-Series II)

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10 pages, 286 KiB

Open AccessEditor’s ChoiceCommunication

Variation in Fatty Acids Concentration in Grasses, Legumes, and Forbs in the Allegheny Plateau

by Marcella Whetsell and Edward Rayburn

Agronomy 2022, 12(7), 1693; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12071693 - 16 Jul 2022

Cited by 2 | Viewed by 1448

Abstract

This study was conducted to determine the fatty acid (FA) content in pasture grasses, legumes, and non-leguminous forbs in northeast West Virginia. Grass, legume, and forb plant material were collected from rotationally stocked pastures and analyzed for crude protein (CP), linoleic acid (C18:2), [...] Read more.

This study was conducted to determine the fatty acid (FA) content in pasture grasses, legumes, and non-leguminous forbs in northeast West Virginia. Grass, legume, and forb plant material were collected from rotationally stocked pastures and analyzed for crude protein (CP), linoleic acid (C18:2), α-linolenic acid (C18:3), and total FA content. Species within botanical classes varied in FA content. Forbs had the highest linoleic acid (C18:2) content followed by legume and grass species. Grasses and forbs had the highest α-linolenic acid (C18:3) content. Forbs had the highest total FA content. These field data were combined with FA data from the research literature to evaluate the correlation of CP concentration with fatty acid concentration. Likewise, after accounting for CP, the summer months caused a decrease while forbs caused an increase in α-linolenic acid (C18:3) content. Vegetative growth and leafiness are the major determinants of FA content in pasture forage. Grazing management to benefit vegetative growth and the presence of desirable forbs in tune with seasonal changes are valuable tools to increase desirable FA profiles in milk and meat products that may be of benefit to human health. Full article

(This article belongs to the Special Issue Management of Grasslands: Forage Growth and Nutritive Composition, Livestock Grazing and Performance)

22 pages, 3472 KiB

Open AccessEditor’s ChoiceArticle

Analysis of Genotypic and Environmental Effects on Biomass Yield, Nutritional and Antinutritional Factors in Common Vetch

by Zoi Parissi, Maria Irakli, Evangelia Tigka, Panayiota Papastylianou, Christos Dordas, Eleni Tani, Eleni M. Abraham, Agisilaos Theodoropoulos, Anastasia Kargiotidou, Leonidas Kougiteas, Angeliki Kousta, Avraam Koskosidis, Stavroula Kostoula, Dimitrios Beslemes and Dimitrios N. Vlachostergios

Agronomy 2022, 12(7), 1678; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12071678 - 15 Jul 2022

Cited by 9 | Viewed by 2316

Abstract

Vicia sativa L. (common vetch) is an annual legume species of high economic and ecological importance which is characterized by high nutritive value for animal feeding and its ability to adapt to various edaphic–climatic conditions. However, limited information is available about genotypic and [...] Read more.

Vicia sativa L. (common vetch) is an annual legume species of high economic and ecological importance which is characterized by high nutritive value for animal feeding and its ability to adapt to various edaphic–climatic conditions. However, limited information is available about genotypic and environmental effects on agronomic, nutritional, and antinutritional traits of common vetch genotypes. Thus, in the present study, four advanced breeding lines and three commercial cultivars were evaluated for yield biomass, color assessment, fiber, crude protein (CP), and polyphenols in three locations (Spata, Larissa, and Thessaloniki) for two consecutive growing seasons (2018–2019 and 2019–2020). The effects of genotype, environment and their interaction (GXE) were significant for all the studied traits. The main source of variation for yield, color, CP, and polyphenols was the environment as it explained 71.5–89.7% of the total variation, whereas for the fibers content it was the GXE interaction. On the other hand, genotype had a much smaller effect on all the traits studied (2.9–16.6%). According to GGE biplot analysis, the ‘Alexandros’ cultivar was the most high-yielding and stable, whereas ‘Leonidas’ was the best performing in terms of nutritional and antinutritional traits. However, one advanced line combined high and stable yield biomass with high nutritive value, indicating the possibility for simultaneous improvement of both features. Full article

(This article belongs to the Special Issue Toward a "Green Revolution" for Crop Breeding)

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12 pages, 1471 KiB

Open AccessEditor’s ChoiceArticle

Mode of Action of a Novel Synthetic Auxin Herbicide Halauxifen-Methyl

by Jiaqi Xu, Xudong Liu, Richard Napier, Liyao Dong and Jun Li

Agronomy 2022, 12(7), 1659; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12071659 - 12 Jul 2022

Cited by 11 | Viewed by 3196

Abstract

Halauxifen-methyl is a new auxin herbicide developed by Corteva Agriscience (Wilmington, DE, USA). It has been suggested that ABF5 may be the target of halauxifen-methyl, as AFB5 mutants of Arabidopsis thaliana are resistant to halauxifen-methyl, which preferentially binds to AFB5. However, the [...] Read more.

Halauxifen-methyl is a new auxin herbicide developed by Corteva Agriscience (Wilmington, DE, USA). It has been suggested that ABF5 may be the target of halauxifen-methyl, as AFB5 mutants of Arabidopsis thaliana are resistant to halauxifen-methyl, which preferentially binds to AFB5. However, the mode of action of halauxifen-methyl has not yet been reported. Therefore, the aim of the present study was to reveal the mode of action of halauxifen-methyl by exploring its influence on indole-3-acetic acid (IAA) homeostasis and the biosynthesis of ethylene and Abscisic Acid (ABA) in Galium aparine. The results showed that halauxifen-methyl could disrupt the homeostasis of IAA and stimulate the overproduction of ethylene and ABA by inducing the overexpression of the 1-aminocyclopropane-1-carboxylate synthase (ACS) and 9-cis-epoxycarotenoid dioxygenase (NCED) genes involved in ethylene and ABA biosynthesis, finally leading to senescence and plant death. Full article

(This article belongs to the Special Issue Herbicides Toxicology and Weeds Herbicide-Resistant Mechanism)

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18 pages, 2430 KiB

Open AccessEditor’s ChoiceArticle

Susceptibility of Cassava Varieties to Disease Caused by Sri Lankan Cassava Mosaic Virus and Impacts on Yield by Use of Asymptomatic and Virus-Free Planting Material

by Al Imran Malik, Sok Sophearith, Erik Delaquis, Wilmer J. Cuellar, Jenyfer Jimenez and Jonathan C. Newby

Agronomy 2022, 12(7), 1658; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12071658 - 12 Jul 2022

Cited by 12 | Viewed by 3799

Abstract

Cassava (Manihot esculenta Crantz) is a rainfed, smallholder-produced crop in mainland Southeast Asia, and is currently facing a serious challenge posed by the introduction of cassava mosaic disease (CMD). This study assessed the susceptibility of popular Asian varieties to CMD, yield penalties [...] Read more.

Cassava (Manihot esculenta Crantz) is a rainfed, smallholder-produced crop in mainland Southeast Asia, and is currently facing a serious challenge posed by the introduction of cassava mosaic disease (CMD). This study assessed the susceptibility of popular Asian varieties to CMD, yield penalties associated with the disease, and the efficacy of selecting clean or asymptomatic plants as seed for the following season. Field experiments evaluated agronomic management practices (i.e., fertilizer application, use of symptomatic and asymptomatic seed stakes) in Cambodia with six to nine popular varieties over three seasons under natural disease pressure. Popular cassava varieties KU50 and Huaybong60 showed superior CMD tolerance, with consistently fewer symptomatic plants, lower disease progress measures, and higher yields. Plants demonstrating symptoms at early stages of development, i.e., 60 days after planting, yielded significantly less than those developing symptoms later (i.e., 270 DAP) or not at all. Plants grown from clean stems yielded on average 20% to 2.7-fold higher than those grown from symptomatic planting material. A yield decline of ~50% was recorded with symptomatic planting materials of susceptible varieties (e.g., SC8, ~25 t ha⁻¹) over successive years. The findings emphasize that farmers could use positive selection by choosing asymptomatic plants to significantly reduce yield losses. Full article

(This article belongs to the Section Pest and Disease Management)

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12 pages, 4856 KiB

Open AccessEditor’s ChoiceArticle

Prediction of Cultivation Areas for the Commercial and an Early Flowering Wild Accession of Salvia hispanica L. in the United States

by Mohammad Hassani, Thomas Piechota and Hagop S. Atamian

Agronomy 2022, 12(7), 1651; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12071651 - 11 Jul 2022

Cited by 1 | Viewed by 1928

Abstract

Salvia hispanica L., commonly known as chia, is a plant-based alternative to seafood and is rich in heart-healthy omega-3 fatty acid, protein, fiber, and antioxidants. In the Northern Hemisphere, chia flowering is triggered by the fall equinox (12-h light and dark, early October) [...] Read more.

Salvia hispanica L., commonly known as chia, is a plant-based alternative to seafood and is rich in heart-healthy omega-3 fatty acid, protein, fiber, and antioxidants. In the Northern Hemisphere, chia flowering is triggered by the fall equinox (12-h light and dark, early October) and the seeds mature after approximately three months. Chia is sensitive to frost and end of season moisture which limits its cultivation to small areas in regions with temperate climate. The U.S. chia import has increased considerably over the years; however, chia is not widely cultivated in the United States. This study used the historical U.S. temperature and precipitation data as a first step to explore the potential of widescale chia cultivation. The 10th percentiles of 25 mm precipitation level as well as soft frost (32 °F: 0 °C) and hard frost (28 °F: −2.2 °C) were tabulated for the months of November and December. The results identified temperature as the main limiting factor for chia cultivation in the United States. The commercial chia variety (harvested in December) can be planted on approximately 10,000 km² cropland (1,000,000 hectare) in the United States. The future development of early flowering variety (harvested in November) was demonstrated to open an additional 44,000 km² (4,400,000 hectares) for chia cultivation in the United States. In conclusion, chia cultivation could provide economic benefits to U.S. farmers both by enriching the diversity within crop rotations aimed at reducing pest and pathogen populations and by its high economic value as an alternative specialty crop. Full article

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20 pages, 308 KiB

Open AccessEditor’s ChoiceArticle

The Effect of Spur Position and Pruning Severity on Shoot Development

by Jose Munoz, Dylan Ellis, Claire Villasenor, Michael Anderson, Michael Andrew Walker, Prince Afriyie and Jean Catherine Dodson Peterson

Agronomy 2022, 12(7), 1634; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12071634 - 8 Jul 2022

Viewed by 1551

Abstract

Adjusting yearly pruning severity is a common vineyard management practice employed to manipulate vegetative and reproductive growth in grapevines. Although the effects of pruning on total vegetative growth are well documented, there is little research on the effects of adjusting shoots meter⁻¹ [...] Read more.

Adjusting yearly pruning severity is a common vineyard management practice employed to manipulate vegetative and reproductive growth in grapevines. Although the effects of pruning on total vegetative growth are well documented, there is little research on the effects of adjusting shoots meter⁻¹ via dormant season pruning on addressing mid-cordon shoot weakness and developmental delays. Cordon-trained, spur-pruned vines are thought, by many growers, to be especially prone to weaker positions and delayed development at mid-cordon positions. This phenomenon is also thought to become more exaggerated as the vine ages. Therefore, the effects of shoot density manipulation, implemented via dormant pruning practices, to homogenize shoot and cluster development along the length of the cordon were examined. In this research, Cabernet Sauvignon grapevines were pruned to either 5.5 shoots meter⁻¹ (5.5) or 11.1 shoots meter⁻¹ (11.1). To control for variations in light interception into the fruiting zone, a control of 11.1 shoots meter⁻¹ with sensor guided leaf thinning (11.1LT) was implemented at full berry set to match the canopy light of the 5.5 shoots meter⁻¹ treatment. It was found that individual shoot growth and yield were directly impacted by manipulation of pruning severity. Shoot growth response varied primarily by growing season, including shoot length and internode length. Yield components were significantly lower in the 5.5 treatment during the first two years of the study but were not significantly different during the last year of the study. The 5.5 treatment resulted in the highest pH and total soluble solids at harvest in 2016 and 2017. Full article

(This article belongs to the Special Issue The Factors Affecting the Yield of Table and Wine Grape Vineyards)

15 pages, 5657 KiB

Open AccessEditor’s ChoiceArticle

Tomato Maturity Classification Based on SE-YOLOv3-MobileNetV1 Network under Nature Greenhouse Environment

by Fei Su, Yanping Zhao, Guanghui Wang, Pingzeng Liu, Yinfa Yan and Linlu Zu

Agronomy 2022, 12(7), 1638; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12071638 - 8 Jul 2022

Cited by 23 | Viewed by 5425

Abstract

The maturity level of tomato is a key factor of tomato picking, which directly determines the transportation distance, storage time, and market freshness of postharvest tomato. In view of the lack of studies on tomato maturity classification under nature greenhouse environment, this paper [...] Read more.

The maturity level of tomato is a key factor of tomato picking, which directly determines the transportation distance, storage time, and market freshness of postharvest tomato. In view of the lack of studies on tomato maturity classification under nature greenhouse environment, this paper proposes a SE-YOLOv3-MobileNetV1 network to classify four kinds of tomato maturity. The proposed maturity classification model is improved in terms of speed and accuracy: (1) Speed: Depthwise separable convolution is used. (2) Accuracy: Mosaic data augmentation, K-means clustering algorithm, and the Squeeze-and-Excitation attention mechanism module are used. To verify the detection performance, the proposed model is compared with the current mainstream models, such as YOLOv3, YOLOv3-MobileNetV1, and YOLOv5 in terms of accuracy and speed. The SE-YOLOv3-MobileNetV1 model is able to distinguish tomatoes in four kinds of maturity, the mean average precision value of tomato reaches 97.5%. The detection speed of the proposed model is 278.6 and 236.8 ms faster than the YOLOv3 and YOLOv5 model. In addition, the proposed model is considerably lighter than YOLOv3 and YOLOv5, which meets the need of embedded development, and provides a reference for tomato maturity classification of tomato harvesting robot. Full article

(This article belongs to the Special Issue Application of Image Recognition Processing Technology in Agricultural)

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13 pages, 13683 KiB

Open AccessEditor’s ChoiceArticle

Remediation of Lead Contamination by Aspergillus niger and Phosphate Rocks under Different Nitrogen Sources

by Yi Feng, Liangliang Zhang, Xiang Li, Liyan Wang, Kianpoor Kalkhajeh Yusef, Hongjian Gao and Da Tian

Agronomy 2022, 12(7), 1639; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12071639 - 8 Jul 2022

Cited by 9 | Viewed by 1666

Abstract

Co-application of Aspergillus niger (A. niger) and phosphate rocks (PR) has been practiced by environmentalists for lead (Pb) remediation. The secretion of organic acid by A. niger usually dominates the dissolution of PR and Pb immobilization. In this study, two types [...] Read more.

Co-application of Aspergillus niger (A. niger) and phosphate rocks (PR) has been practiced by environmentalists for lead (Pb) remediation. The secretion of organic acid by A. niger usually dominates the dissolution of PR and Pb immobilization. In this study, two types of PR (fluorapatite (FAp) and phosphogypsum (PG)) were investigated in Pb remediation by A. niger under three different forms of nitrogen (ammonium, nitrate, and urea). Our results reveal that the formation of pyromorphite and lead oxalate contributed to Pb removal by the combination of A. niger with FAp and PG. PG showed a significant capability for Pb remediation compared with FAP, over 94% of Pb vs. 50%. Compared with nitrate and urea, ammonium significantly decreased Pb cation concentrations from 1500 mg/L to 0.4 mg/L. Due to ammonium containing sulfate, the lead sulfate formed also contributed to Pb removal. However, nitrate stimulated A. niger to secrete more oxalic acid (~1400 mg/L) than ammonium and urea (~200 mg/L), which can form insoluble lead oxalate. These insoluble minerals can reduce the availability of removed Pb. Despite the efficacy of both ammonium and nitrate for Pb remediation, our findings suggest that nitrate is the primary candidate in this regard due to high oxalic acid secretion. Full article

(This article belongs to the Special Issue Environmental Ecological Remediation and Farming Sustainability)

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17 pages, 2640 KiB

Open AccessEditor’s ChoiceArticle

Growth and Fruit Yields of Greenhouse Tomato under the Integrated Water and Fertilizer by Moistube Irrigation

by Mingzhi Zhang, Na Xiao, Yangjian Li, Yuan Li, Dong Zhang, Zhijing Xu and Zhenxing Zhang

Agronomy 2022, 12(7), 1630; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12071630 - 7 Jul 2022

Cited by 8 | Viewed by 2886

Abstract

The mechanism of greenhouse tomato growth and yield under the integrated water and fertilizer of moistube irrigation (MI) is not clear. Thus, to fill the research gap, a completely randomized trial design was used to study the effects of different irrigation amounts (I; [...] Read more.

The mechanism of greenhouse tomato growth and yield under the integrated water and fertilizer of moistube irrigation (MI) is not clear. Thus, to fill the research gap, a completely randomized trial design was used to study the effects of different irrigation amounts (I; to realize different I, the tube working pressure was 1 (I1), 2 (I2), 3 (I3) m) and fertilizer amounts (F, N-P-K: 20%-20%-20%; the F at a single time was 100 (F1), 200 (F2) and 300 (F3) kg/ha) on growth and yield of tomato. The results showed that with an increase in I, the photosynthetic rate (Pn) of leaves and total dry matter mass (TDM) first increased and then decreased, while the nutrition and the flavor indexes of fruit decreased. With an increase in F, the Pn of leaves, the TDM of tomato and the fruit quality increased at first and then decreased. The effects of I on the yield of tomato was higher than that of F. With an increase in I, the partial fertilizer productivity (PFP) increased at first and then decreased, and the water use efficiency (WUE) decreased by 13.96%. With an increase in F, the WUE increased at first and then decreased, and the PFP decreased by 148.97%. The conclusion based on a spatial analysis was consistent with the comprehensive evaluation of yield and water use efficiency, which showed that I2F2 was the best. Full article

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13 pages, 1610 KiB

Open AccessEditor’s ChoiceArticle

Suitability of Early Blight Forecasting Systems for Detecting First Symptoms in Potato Crops of NW Spain

by Laura Meno, Isaac Kwesi Abuley, Olga Escuredo and M. Carmen Seijo

Agronomy 2022, 12(7), 1611; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12071611 - 4 Jul 2022

Cited by 9 | Viewed by 2623

Abstract

In recent years, early blight epidemics have been frequently causing important yield loses in potato crop. This fungal disease develops quickly when weather conditions are favorable, forcing the use of fungicides by farmers. A Limia is one of the largest areas for potato [...] Read more.

In recent years, early blight epidemics have been frequently causing important yield loses in potato crop. This fungal disease develops quickly when weather conditions are favorable, forcing the use of fungicides by farmers. A Limia is one of the largest areas for potato production in Spain. Usually, early blight epidemics are controlled using pre-established schedule calendars. This strategy is expensive and can affect the environment of agricultural areas. Decision support systems are not currently in place to be used by farmers for managing early blight. Thus, the objective of this research was to evaluate different early blight forecasting models based on plant or/and pathogen requirements and weather conditions to check their suitability for predicting the first symptoms of early blight, which is necessary to determine the timings of the first fungicide application. For this, weather, phenology and symptomatology of disease were monitored throughout five crop seasons. The first early blight symptoms appeared starting the flowering stage, between 37 and 40 days after emergence of plants. The forecasting models that were based on plants offered the best results. Specifically, the Wang-Engel model, with 1.4 risk units and Growing Degree-Days (361 cumulative units) offeredthe best prediction. The pathogen-based models showed a conservative forecast, whereas the models that integrated both plant and pathogen features forecasted the first early blight attack markedly later. Full article

(This article belongs to the Special Issue Epidemiology and Control of Fungal Diseases of Crop Plants)

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21 pages, 2789 KiB

Open AccessEditor’s ChoiceArticle

Effects of Nitrogen and Phosphorus Addition on Agronomic Characters, Photosynthetic Performance and Anatomical Structure of Alfalfa in Northern Xinjiang, China

by Yanliang Sun, Xuzhe Wang, Chunhui Ma and Qianbing Zhang

Agronomy 2022, 12(7), 1613; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12071613 - 4 Jul 2022

Cited by 9 | Viewed by 1914

Abstract

The productivity of alfalfa is associated with a large amount of nitrogen (N) and phosphorus (P); the addition of exogenous N and P fertilizers can fully exploit the growth potential of alfalfa. However, there is uncertainty about the relationship between changes in alfalfa [...] Read more.

The productivity of alfalfa is associated with a large amount of nitrogen (N) and phosphorus (P); the addition of exogenous N and P fertilizers can fully exploit the growth potential of alfalfa. However, there is uncertainty about the relationship between changes in alfalfa productivity and photosynthetic physiology and anatomy. We conducted field fertilization experiments on alfalfa in the second and third years under drip irrigation, as well as measurement of the photosynthetic physiology, anatomical structure and agronomic traits of alfalfa at different levels of N (0, 120 kg·ha⁻¹) and different levels of P₂O₅ (0, 50, 100 and 150 kg·ha⁻¹). The results showed that the dry matter yield (DMY), crude protein (CP), net photosynthetic rate (P_n) and specific leaf weight (SLW) were increased by 2.10~11.82%, 4.95~11.93%, 4.71~7.59% and 2.02~7.12% in the N application treatment compared with the non-N application treatment, while the DMY, CP, P_n and SLW were increased by 3.19~17.46%, 1.99~8.42%, 6.15~24.95% and 2.16~11.90% in the P application treatment compared with the non-P application treatment. N and P increase the thickness of the spongy tissue (ST) of alfalfa, which will facilitate the entry and exit of gas and water, and will further affect the photosynthetic indexes, such as stomatal conductance (G_s) and transpiration rate (T_r), of alfalfa leaves. Increased palisade tissue (PT) thickness will also enhance the adaptability of plant leaves to strong sunlight, thereby increasing the maximum net photosynthetic rate (P_max) and light saturation point (LSP). Fertilization treatment showed the highest utilization efficiency for low light and better adaptation to strong light, but the R_d decreased. The comprehensive scores of principal component analysis for anatomical structure, photosynthetic performance and agronomic traits were N₁P₂ > N₀P₂ > N₁P₃ > N₁P₁ > N₀P₃ > N₀P₁ > N₁P₀ > N₀P₀. Therefore, the application of N and P fertilizers contributed to the adaptive changes in alfalfa leaf anatomy and the improvement of photosynthetic capacity, which were beneficial to the improvement of alfalfa dry matter yield, growth traits and nutritional quality, with the most obvious improvement effect obtained with the application of 120 kg·ha⁻¹ of N and 100 kg·ha⁻¹ of P₂O₅. Full article

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22 pages, 7972 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

A Study on Long-Close Distance Coordination Control Strategy for Litchi Picking

by Hongjun Wang, Yiyan Lin, Xiujin Xu, Zhaoyi Chen, Zihao Wu and Yunchao Tang

Agronomy 2022, 12(7), 1520; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12071520 - 24 Jun 2022

Cited by 37 | Viewed by 3447

Abstract

For the automated robotic picking of bunch-type fruit, the strategy is to roughly determine the location of the bunches, plan the picking route from a remote location, and then locate the picking point precisely at a more appropriate, closer location. The latter can [...] Read more.

For the automated robotic picking of bunch-type fruit, the strategy is to roughly determine the location of the bunches, plan the picking route from a remote location, and then locate the picking point precisely at a more appropriate, closer location. The latter can reduce the amount of information to be processed and obtain more precise and detailed features, thus improving the accuracy of the vision system. In this study, a long-close distance coordination control strategy for a litchi picking robot was proposed based on an Intel Realsense D435i camera combined with a point cloud map collected by the camera. The YOLOv5 object detection network and DBSCAN point cloud clustering method were used to determine the location of bunch fruits at a long distance to then deduce the sequence of picking. After reaching the close-distance position, the Mask RCNN instance segmentation method was used to segment the more distinctive bifurcate stems in the field of view. By processing segmentation masks, a dual reference model of “Point + Line” was proposed, which guided picking by the robotic arm. Compared with existing studies, this strategy took into account the advantages and disadvantages of depth cameras. By experimenting with the complete process, the density-clustering approach in long distance was able to classify different bunches at a closer distance, while a success rate of 88.46% was achieved during fruit-bearing branch locating. This was an exploratory work that provided a theoretical and technical reference for future research on fruit-picking robots. Full article

(This article belongs to the Collection Advances of Agricultural Robotics in Sustainable Agriculture 4.0)

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17 pages, 1854 KiB

Open AccessEditor’s ChoiceArticle

Yield and Quality of Romaine Lettuce at Different Daily Light Integral in an Indoor Controlled Environment

by Bożena Matysiak, Ewa Ropelewska, Anna Wrzodak, Artur Kowalski and Stanisław Kaniszewski

Agronomy 2022, 12(5), 1026; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12051026 - 24 Apr 2022

Cited by 31 | Viewed by 5065

Abstract

In this study, the effect of different photosynthetic photon flux density (PPFD) provided by LEDs (Light Emitting Diodes) and photoperiod on biomass production, morphological traits, photosynthetic performance, sensory attributes, and image texture parameters of indoor cultivated romaine lettuce was evaluated. Two cultivars of [...] Read more.

In this study, the effect of different photosynthetic photon flux density (PPFD) provided by LEDs (Light Emitting Diodes) and photoperiod on biomass production, morphological traits, photosynthetic performance, sensory attributes, and image texture parameters of indoor cultivated romaine lettuce was evaluated. Two cultivars of lettuce Lactuca sativa var. longifolium namely ‘Casual’ (Syngenta)—midi romaine lettuce with medium-compact heads—and ‘Elizium’ (Enza Zaden)—a mini type (Little Gem) with compact heavy heads—were used. PPFD of 160 and 240 µmol m⁻² s⁻¹ and photoperiod of 16 and 20 h were applied, and Daily Light Integral (DLI) values were 9.2, 11.5, 13.8, and 17.3 mol m⁻² day⁻¹. The experiment lasted 30 days in the Indoor Controlled Environment Agriculture facility. DLI equal to 17.3 mol m⁻² per day for cv. ‘Casual’ and 11.5–17.3 mol m⁻² per day for cv. ‘Elizium’ allowed to obtain a very high fresh weight, 350 and 240 g, respectively, within 30 days of cultivation in an indoor plant production facility. The application of the lowest PPFD 160 µmol m⁻² s⁻¹ and 16 h photoperiod (9.2 mol m⁻² per day DLI) resulted in the lowest fresh weight, the number of leaves and head circumference. The level of nitrate, even at the lowest DLI, was below the limit imposed by European Community Regulation. The cv. ‘Elizium’ lettuce grown at PPFD 240 µmol m⁻² s⁻¹ and 16 h photoperiod had the highest overall sensory quality. The cv. ‘Casual’ lettuce grown at PPFD 160 µmol m⁻² s⁻¹ and 20 h photoperiod had the lowest sensory quality. The samples subjected to different photoperiod and PPFD were also successively distinguished in an objective and non-destructive way using image features and machine learning algorithms. The average accuracy for the leaf samples of cv. ‘Casual’ lettuce reached 98.75% and for cv. ‘Elizium’ cultivar—86.25%. The obtained relationship between DLI and yield, as well as the quality of romaine lettuce, can be used in practice to improve romaine lettuce production in an Indoor Controlled Environment. Full article

(This article belongs to the Special Issue Growth Control of Plants on the Light Environment)

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23 pages, 303 KiB

Open AccessEditor’s ChoiceArticle

Evaluation of Combining Ability and Heterosis of Popular Restorer and Male Sterile Lines for the Development of Superior Rice Hybrids

by Abul Kalam Azad, Umakanta Sarker, Sezai Ercisli, Amine Assouguem, Riaz Ullah, Rafa Almeer, Amany A. Sayed and Ilaria Peluso

Agronomy 2022, 12(4), 965; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12040965 - 16 Apr 2022

Cited by 27 | Viewed by 2921

Abstract

Twenty-four hybrids, obtained from a mating design following 6 line × 4 testers, were evaluated to estimate the heterosis, specific, and general combining ability (SCA and GCA) of parents and hybrids to find out suitable general combiner (GC) parents and cross combinations for [...] Read more.

Twenty-four hybrids, obtained from a mating design following 6 line × 4 testers, were evaluated to estimate the heterosis, specific, and general combining ability (SCA and GCA) of parents and hybrids to find out suitable general combiner (GC) parents and cross combinations for utilization in the future breeding program. A randomized complete block design with three replications was followed to set the experiment. Data were recorded on grain yield and 13 yield-related agronomic traits. The analysis of variance of all cross combinations had highly significant differences for most of the characters studied, which indicated a wide variation across the genotypes, parents, lines, testers, and crosses. SCA and GCA variances were significant for all studied traits except for the panicle length, indicating that both non-additive and additive gene actions were involved in these traits. The GCA variance/SCA variance for all the traits was <1, signifying the multitude of dominant and epistatic gene actions. The GCA effects of three lines GAN46A, IR58025A, IR62629A, and a tester IR46R were significant for the majority of the agronomic traits including grain yield and might be used for improving the yield of grains in rice as parents of excellent GC. Based on the yield of grains and agronomic traits, the hybrids IR58025A × IR46R and GAN46A × IR46R might be considered the best hybrids and another nine hybrids could also be considered good hybrids. Similarly, based on the yield of grains and agronomic traits, the positive and significant mid-parent, better parent, and standard heterosis were obtained from 3 F₁s, 1 F₁, and 3 F₁s, respectively. Heterosis and combining ability study revealed that hybrids IR58025A × IR46R and GAN46A × IR46R might be considered preferable hybrid cultivars. Full article

(This article belongs to the Special Issue Hybrid Breeding: Future Status and Future Prospects - Series II)

21 pages, 1082 KiB

Open AccessEditor’s ChoiceArticle

Use of Copper-Based Fungicides in Organic Agriculture in Twelve European Countries

by Lucius Tamm, Barbara Thuerig, Stoilko Apostolov, Hugh Blogg, Esmeralda Borgo, Paola Elisa Corneo, Susanne Fittje, Michelangelo de Palma, Adam Donko, Catherine Experton, Évelyne Alcázar Marín, Ángela Morell Pérez, Ilaria Pertot, Anton Rasmussen, Håvard Steinshamn, Airi Vetemaa, Helga Willer and Joëlle Herforth-Rahmé

Agronomy 2022, 12(3), 673; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12030673 - 10 Mar 2022

Cited by 50 | Viewed by 10327

Abstract

The reduction of copper-based plant-protection products with the final aim of phasing out has a high priority in European policy, as well as in organic agriculture. Our survey aims at providing an overview of the current use of these products in European organic [...] Read more.

The reduction of copper-based plant-protection products with the final aim of phasing out has a high priority in European policy, as well as in organic agriculture. Our survey aims at providing an overview of the current use of these products in European organic agriculture and the need for alternatives to allow policymakers to develop strategies for a complete phasing out. Due to a lack of centralized databases on pesticide use, our survey combines expert knowledge on permitted and real copper use per crop and country, with statistics on organic area. In the 12 surveyed countries (Belgium, Bulgaria, Denmark, Estonia, France, Germany, Hungary, Italy, Norway, Spain, Switzerland, and the UK), we calculated that approximately 3258 t copper metal per year is consumed by organic agriculture, equaling to 52% of the permitted annual dosage. This amount is split between olives (1263 t y⁻¹, 39%), grapevine (990 t y⁻¹, 30%), and almonds (317 t y⁻¹, 10%), followed by other crops with much smaller annual uses (<80 t y⁻¹). In 56% of the allowed cases (countries × crops), farmers use less than half of the allowed amount, and in 27%, they use less than a quarter. At the time being, completely abandoning copper fungicides would lead to high yield losses in many crops. To successfully reduce or avoid copper use, all preventive strategies have to be fully implemented, breeding programs need to be intensified, and several affordable alternative products need to be brought to the market. Full article

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19 pages, 5769 KiB

Open AccessEditor’s ChoiceArticle

A Reversible Automatic Selection Normalization (RASN) Deep Network for Predicting in the Smart Agriculture System

by Xuebo Jin, Jiashuai Zhang, Jianlei Kong, Tingli Su and Yuting Bai

Agronomy 2022, 12(3), 591; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12030591 - 27 Feb 2022

Cited by 74 | Viewed by 4834

Abstract

Due to the nonlinear modeling capabilities, deep learning prediction networks have become widely used for smart agriculture. Because the sensing data has noise and complex nonlinearity, it is still an open topic to improve its performance. This paper proposes a Reversible Automatic Selection [...] Read more.

Due to the nonlinear modeling capabilities, deep learning prediction networks have become widely used for smart agriculture. Because the sensing data has noise and complex nonlinearity, it is still an open topic to improve its performance. This paper proposes a Reversible Automatic Selection Normalization (RASN) network, integrating the normalization and renormalization layer to evaluate and select the normalization module of the prediction model. The prediction accuracy has been improved effectively by scaling and translating the input with learnable parameters. The application results of the prediction show that the model has good prediction ability and adaptability for the greenhouse in the Smart Agriculture System. Full article

(This article belongs to the Special Issue Application of Artificial Neural Networks in Agriculture)

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17 pages, 1708 KiB

Open AccessEditor’s ChoiceArticle

Combination of Limited Meteorological Data for Predicting Reference Crop Evapotranspiration Using Artificial Neural Network Method

by Ahmed Elbeltagi, Attila Nagy, Safwan Mohammed, Chaitanya B. Pande, Manish Kumar, Shakeel Ahmad Bhat, József Zsembeli, László Huzsvai, János Tamás, Elza Kovács, Endre Harsányi and Csaba Juhász

Agronomy 2022, 12(2), 516; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12020516 - 18 Feb 2022

Cited by 38 | Viewed by 3148

Abstract

Reference crop evapotranspiration (ET_o) is an important component of the hydrological cycle that is used for water resource planning, irrigation, and agricultural management, as well as in other hydrological processes. The aim of this study was to estimate the ET_o [...] Read more.

Reference crop evapotranspiration (ET_o) is an important component of the hydrological cycle that is used for water resource planning, irrigation, and agricultural management, as well as in other hydrological processes. The aim of this study was to estimate the ET_o based on limited meteorological data using an artificial neural network (ANN) method. The daily data of minimum temperature (T_min), maximum temperature (T_max), mean temperature (T_mean), solar radiation (SR), humidity (H), wind speed (WS), sunshine hours (Ssh), maximum global radiation (grad_max), minimum global radiation (grad_min), day length, and ET_o data were obtained over the long-term period from 1969 to 2019. The analysed data were divided into two parts from 1969 to 2007 and from 2008 to 2019 for model training and testing, respectively. The optimal ANN for forecasting ET_o included T_max, T_min, H, and SR at hidden layers (4, 3); grad_min, SR, and WS at (6, 4); SR, day length, Ssh, and T_mean at (3, 2); all collected parameters at hidden layer (5, 4). The results showed different alternative methods for estimation of ET_o in case of a lack of climate data with high performance. Models using ANN can help promote the decision-making for water managers, designers, and development planners. Full article

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16 pages, 2551 KiB

Open AccessEditor’s ChoiceArticle

Chitosan-Induced Physiological and Biochemical Regulations Confer Drought Tolerance in Pot Marigold (Calendula officinalis L.)

by Gulzar Akhtar, Hafiz Nazar Faried, Kashif Razzaq, Sami Ullah, Fahad Masoud Wattoo, Muhammad Asif Shehzad, Yasar Sajjad, Muhammad Ahsan, Talha Javed, Eldessoky S. Dessoky, Nader R. Abdelsalam and Muhammad Sohaib Chattha

Agronomy 2022, 12(2), 474; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12020474 - 14 Feb 2022

Cited by 28 | Viewed by 3093

Abstract

Severe water stress conditions limit growth and development of floricultural crops which affects flower quality. Hence, development of effective approaches for drought tolerance is crucial to limit recurring water deficit challenges. Foliar application of various plant growth regulators has been evaluated to improve [...] Read more.

Severe water stress conditions limit growth and development of floricultural crops which affects flower quality. Hence, development of effective approaches for drought tolerance is crucial to limit recurring water deficit challenges. Foliar application of various plant growth regulators has been evaluated to improve drought tolerance in different floricultural crops; however, reports regarding the role of chitosan (Ci) on seasonal flowers like calendula are still scant. Therefore, we evaluated the role of Ci foliar application on morphological, physiological, biochemical, and anatomical parameters of calendula under water stress conditions. Different doses of Ci (0, 2.5, 5, 7.5, 10 mg L⁻¹) were applied through foliar application to evaluate their impact in enhancing growth and photosynthetic pigments of calendula. The optimized Ci level of 7.5 mg L⁻¹ was further evaluated to study mechanisms of water stress tolerance in calendula. Ci application significantly increased biomass and pigments in calendula. Ci (7.5 mg L⁻¹) resulted in increased photosynthetic rate (72.98%), transpiration rate (62.11%), stomatal conductance (59.54%), sub-stomatal conductance (20.62%), and water use efficiency (84.93%). Furthermore, it improved catalase, guaiacol peroxidase, and superoxide dismutase by 56.70%, 64.94%, and 32.41%, respectively. These results highlighted the significance of Ci in inducing drought tolerance in pot marigold. Full article

(This article belongs to the Special Issue Molecular Genetic Improvement of Crop Drought Tolerance)

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16 pages, 3119 KiB

Open AccessEditor’s ChoiceArticle

Lignin–Chitosan Nanocarriers for the Delivery of Bioactive Natural Products against Wood-Decay Phytopathogens

by Eva Sánchez-Hernández, Natalia Langa-Lomba, Vicente González-García, José Casanova-Gascón, Jesús Martín-Gil, Alberto Santiago-Aliste, Sergio Torres-Sánchez and Pablo Martín-Ramos

Agronomy 2022, 12(2), 461; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12020461 - 12 Feb 2022

Cited by 23 | Viewed by 3377

Abstract

The use of nanocarriers (NCs), i.e., nanomaterials capable of encapsulating drugs and releasing them selectively, is an emerging field in agriculture. In this study, the synthesis, characterization, and in vitro and in vivo testing of biodegradable NCs loaded with natural bioactive products was [...] Read more.

The use of nanocarriers (NCs), i.e., nanomaterials capable of encapsulating drugs and releasing them selectively, is an emerging field in agriculture. In this study, the synthesis, characterization, and in vitro and in vivo testing of biodegradable NCs loaded with natural bioactive products was investigated for the control of certain phytopathogens responsible for wood degradation. In particular, NCs based on methacrylated lignin and chitosan oligomers, loaded with extracts from Rubia tinctorum, Silybum marianum, Equisetum arvense, and Urtica dioica, were first assayed in vitro against Neofusicoccum parvum, an aggressive fungus that causes cankers and diebacks in numerous woody hosts around the world. The in vitro antimicrobial activity of the most effective treatment was further explored against another fungal pathogen and two bacteria related to trunk diseases: Diplodia seriata, Xylophilus ampelinus, and Pseudomonas syringae pv. syringae, respectively. Subsequently, it was evaluated in field conditions, in which it was applied by endotherapy for the control of grapevine trunk diseases. In the in vitro mycelial growth inhibition tests, the NCs loaded with R. tinctorum resulted in EC₉₀ concentrations of 65.8 and 91.0 μg·mL⁻¹ against N. parvum and D. seriata, respectively. Concerning their antibacterial activity, a minimum inhibitory concentration of 37.5 μg·mL⁻¹ was obtained for this treatment against both phytopathogens. Upon application via endotherapy on 20-year-old grapevines with clear esca and Botryosphaeria decay symptoms, no phytotoxicity effects were observed (according to SPAD and chlorophyll fluorescence measurements) and the sugar content of the grape juice was not affected either. Nonetheless, the treatment led to a noticeable decrease in foliar symptoms as well as a higher yield in the treated arms as compared to the control arms (3177 vs. 1932 g/arm), suggestive of high efficacy. Given the advantages in terms of controlled release and antimicrobial product savings, these biodegradable NCs loaded with natural extracts may deserve further research in large-scale field tests. Full article

(This article belongs to the Special Issue Selected Papers from 11th Iberian Agroengineering Congress)

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15 pages, 11732 KiB

Open AccessEditor’s ChoiceArticle

Growth and Antioxidant Responses of Lettuce (Lactuca sativa L.) to Arbuscular Mycorrhiza Inoculation and Seaweed Extract Foliar Application

by Farzad Rasouli, Trifa Amini, Mohammad Asadi, Mohammad Bagher Hassanpouraghdam, Mohammad Ali Aazami, Sezai Ercisli, Sona Skrovankova and Jiri Mlcek

Agronomy 2022, 12(2), 401; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12020401 - 5 Feb 2022

Cited by 26 | Viewed by 4964

Abstract

Biofertilizers, such as arbuscular mycorrhiza fungi (AMF) and seaweed extract (SWE), have been effective in environmental and agricultural ecosystems. In this study, the effects of AMF, SWE, and their co-application were assayed on the growth and antioxidant potential of lettuce plants. The experiment [...] Read more.

Biofertilizers, such as arbuscular mycorrhiza fungi (AMF) and seaweed extract (SWE), have been effective in environmental and agricultural ecosystems. In this study, the effects of AMF, SWE, and their co-application were assayed on the growth and antioxidant potential of lettuce plants. The experiment was conducted as a factorial based on a completely randomized design with two factors and four replications under greenhouse conditions. The first factor was AMF (Glomus mosseae) at two levels consisting of AMF application (20 g pot⁻¹), and without using AMF; and the second factor was SWE foliar spraying (Ascophyllum nodosum) at 0.5, 1.5 and 3 g L⁻¹ concentration. The results revealed that the highest root colonization (85%) belonged to AMF and SWE (3 g L⁻¹) × AMF; the lowest colonization rate (65%) was observed for AMF × SWE (0.5 g L⁻¹) treatment. The highest growth parameters (leaf number, shoot and root fresh weight, head diameter), biochemical traits (total soluble proteins, carbohydrates content) and TAA, total antioxidant activity by FRAP method and ascorbic acid, total phenolics, and flavonoids content were obtained with the co-applications. Therefore, the best results of the evaluated traits were achieved with AMF × SWE (3 g L⁻¹). The TAA value was increased three-fold compared to the control. Total phenolics and flavonoids content were 2.24 and 6.59 times higher than the control, respectively. On the other hand, leaf dry weight was decreased with the further growth of the plants. Overall, the co-application of AMF with SWE can be recommended to producers as an alternative and environment-friendly strategy to improve the qualitative and quantitative traits of the lettuce crop. Full article

(This article belongs to the Special Issue Plant Responses to Stress and Environmental Stimulus)

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23 pages, 2441 KiB

Open AccessEditor’s ChoiceArticle

Impact of Temperature and Water on Seed Germination and Seedling Growth of Maize (Zea mays L.)

by Hussein Khaeim, Zoltán Kende, Márton Jolánkai, Gergő Péter Kovács, Csaba Gyuricza and Ákos Tarnawa

Agronomy 2022, 12(2), 397; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12020397 - 5 Feb 2022

Cited by 38 | Viewed by 17273

Abstract

Germination and seedling development are essential stages in a plant’s life cycle, greatly influenced by temperature and moisture conditions. The aim of this study was to determine maize (Zea mays L.) seeds’ germination and seedling development under various abiotic stresses. Eight different [...] Read more.

Germination and seedling development are essential stages in a plant’s life cycle, greatly influenced by temperature and moisture conditions. The aim of this study was to determine maize (Zea mays L.) seeds’ germination and seedling development under various abiotic stresses. Eight different temperature levels, 5, 10, 15, 20, 25, 30, 35, and 40 °C, were used. Drought and waterlogging stresses were tested using 30 water levels based on one-milliliter intervals and as percentages of thousand kernel weight (TKW) at 20 and 25 °C. Seedling density and the use of antifungals were also examined. Temperature significantly affected germination duration and seedling growth, and 20 °C was found to be ideal with an optimal range of less than 30 °C. Germination occurred at 25% of the TKW. The optimal water range for seedling growth was higher and broader than the range for germination. Seed size assisted in defining germination water requirements and providing an accurate basis. The present research established an optimum water supply range of 150–325% of the TKW for maize seedling development. A total of 6 seeds per 9 cm Petri dish may be preferable over greater densities. The technique of priming seeds with an antifungal solution before planting was observed to have a better effect than applying it in the growth media. Full article

(This article belongs to the Special Issue Effective Methods for Improving Seed Germination and Seed Quality)

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16 pages, 7262 KiB

Open AccessEditor’s ChoiceArticle

YOLO-Banana: A Lightweight Neural Network for Rapid Detection of Banana Bunches and Stalks in the Natural Environment

by Lanhui Fu, Zhou Yang, Fengyun Wu, Xiangjun Zou, Jiaquan Lin, Yongjun Cao and Jieli Duan

Agronomy 2022, 12(2), 391; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12020391 - 4 Feb 2022

Cited by 41 | Viewed by 4198

Abstract

The real-time detection of banana bunches and stalks in banana orchards is a key technology in the application of agricultural robots. The complex conditions of the orchard make accurate detection a difficult task, and the light weight of the deep learning network is [...] Read more.

The real-time detection of banana bunches and stalks in banana orchards is a key technology in the application of agricultural robots. The complex conditions of the orchard make accurate detection a difficult task, and the light weight of the deep learning network is an application trend. This study proposes and compares two improved YOLOv4 neural network detection models in a banana orchard. One is the YOLO-Banana detection model, which analyzes banana characteristics and network structure to prune the less important network layers; the other is the YOLO-Banana-l4 detection model, which, by adding a YOLO head layer to the pruned network structure, explores the impact of a four-scale prediction structure on the pruning network. The results show that YOLO-Banana and YOLO-Banana-l4 could reduce the network weight and shorten the detection time compared with YOLOv4. Furthermore, YOLO-Banana detection model has the best performance, with good detection accuracy for banana bunches and stalks in the natural environment. The average precision (AP) values of the YOLO-Banana detection model on banana bunches and stalks are 98.4% and 85.98%, and the mean average precision (mAP) of the detection model is 92.19%. The model weight is reduced from 244 to 137 MB, and the detection time is shortened from 44.96 to 35.33 ms. In short, the network is lightweight and has good real-time performance and application prospects in intelligent management and automatic harvesting in the banana orchard. Full article

(This article belongs to the Collection Advances of Agricultural Robotics in Sustainable Agriculture 4.0)

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20 pages, 1894 KiB

Open AccessEditor’s ChoiceArticle

Carbon, Nitrogen and Water Footprints of Organic Rice and Conventional Rice Production over 4 Years of Cultivation: A Case Study in the Lower North of Thailand

by Noppol Arunrat, Sukanya Sereenonchai, Winai Chaowiwat, Can Wang and Ryusuke Hatano

Agronomy 2022, 12(2), 380; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12020380 - 3 Feb 2022

Cited by 31 | Viewed by 4931

Abstract

An integrated method is required for comprehensive assessment of the environmental impacts and economic benefits of rice production systems. Therefore, the objective of this study was to apply different footprinting approaches (carbon footprint (CF), nitrogen footprint (NF), water footprint (WF)) and determine the [...] Read more.

An integrated method is required for comprehensive assessment of the environmental impacts and economic benefits of rice production systems. Therefore, the objective of this study was to apply different footprinting approaches (carbon footprint (CF), nitrogen footprint (NF), water footprint (WF)) and determine the economic return on organic rice farming (OF) and conventional rice farming (CVF) at the farm scale. Over the 4-year study period (2018–2021), the results showed lower net greenhouse gas (GHG) emissions in OF (3289.1 kg CO₂eq ha⁻¹ year⁻¹) than in CVF (4921.7 kg CO₂eq ha⁻¹ year⁻¹), indicating that the use of OF can mitigate the GHG emissions from soil carbon sequestration. However, there was a higher CF intensity in OF (1.17 kg CO₂eq kg⁻¹ rice yield) than in CVF (0.93 kg CO₂eq kg⁻¹ rice yield) due to the lower yield. The NF intensities of OF and CVF were 0.34 and 11.94 kg Neq kg⁻¹ rice yield, respectively. The total WF of CVF (1470.1 m³ ton⁻¹) was higher than that in OF (1216.3 m³ ton⁻¹). The gray water in CVF was significantly higher than that in OF due to the use of chemical fertilizers, herbicides, and pesticides. Although the rice yield in OF was nearly two times lower than that in CVF, the economic return was higher due to lower production costs and higher rice prices. However, more field studies and long-term monitoring are needed for future research. Full article

(This article belongs to the Special Issue Agroecology, Organic Agriculture and Energy Efficiency of Food Production)

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23 pages, 56779 KiB

Open AccessEditor’s ChoiceArticle

Benchmark of Deep Learning and a Proposed HSV Colour Space Models for the Detection and Classification of Greenhouse Tomato

by Germano Moreira, Sandro Augusto Magalhães, Tatiana Pinho, Filipe Neves dos Santos and Mário Cunha

Agronomy 2022, 12(2), 356; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12020356 - 31 Jan 2022

Cited by 46 | Viewed by 6588

Abstract

The harvesting operation is a recurring task in the production of any crop, thus making it an excellent candidate for automation. In protected horticulture, one of the crops with high added value is tomatoes. However, its robotic harvesting is still far from maturity. [...] Read more.

The harvesting operation is a recurring task in the production of any crop, thus making it an excellent candidate for automation. In protected horticulture, one of the crops with high added value is tomatoes. However, its robotic harvesting is still far from maturity. That said, the development of an accurate fruit detection system is a crucial step towards achieving fully automated robotic harvesting. Deep Learning (DL) and detection frameworks like Single Shot MultiBox Detector (SSD) or You Only Look Once (YOLO) are more robust and accurate alternatives with better response to highly complex scenarios. The use of DL can be easily used to detect tomatoes, but when their classification is intended, the task becomes harsh, demanding a huge amount of data. Therefore, this paper proposes the use of DL models (SSD MobileNet v2 and YOLOv4) to efficiently detect the tomatoes and compare those systems with a proposed histogram-based HSV colour space model to classify each tomato and determine its ripening stage, through two image datasets acquired. Regarding detection, both models obtained promising results, with the YOLOv4 model standing out with an F1-Score of 85.81%. For classification task the YOLOv4 was again the best model with an Macro F1-Score of 74.16%. The HSV colour space model outperformed the SSD MobileNet v2 model, obtaining results similar to the YOLOv4 model, with a Balanced Accuracy of 68.10%. Full article

(This article belongs to the Topic Grand Challenges of Advanced Technologies in Sustainable Agriculture 4.0: Future Farming, Harvesting and Preservation)

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14 pages, 6112 KiB

Open AccessEditor’s ChoiceArticle

Plant Disease Recognition Model Based on Improved YOLOv5

by Zhaoyi Chen, Ruhui Wu, Yiyan Lin, Chuyu Li, Siyu Chen, Zhineng Yuan, Shiwei Chen and Xiangjun Zou

Agronomy 2022, 12(2), 365; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12020365 - 31 Jan 2022

Cited by 143 | Viewed by 15735

Abstract

To accurately recognize plant diseases under complex natural conditions, an improved plant disease-recognition model based on the original YOLOv5 network model was established. First, a new InvolutionBottleneck module was used to reduce the numbers of parameters and calculations, and to capture long-distance information [...] Read more.

To accurately recognize plant diseases under complex natural conditions, an improved plant disease-recognition model based on the original YOLOv5 network model was established. First, a new InvolutionBottleneck module was used to reduce the numbers of parameters and calculations, and to capture long-distance information in the space. Second, an SE module was added to improve the sensitivity of the model to channel features. Finally, the loss function ‘Generalized Intersection over Union’ was changed to ‘Efficient Intersection over Union’ to address the former’s degeneration into ‘Intersection over Union’. These proposed methods were used to improve the target recognition effect of the network model. In the experimental phase, to verify the effectiveness of the model, sample images were randomly selected from the constructed rubber tree disease database to form training and test sets. The test results showed that the mean average precision of the improved YOLOv5 network reached 70%, which is 5.4% higher than that of the original YOLOv5 network. The precision values of this model for powdery mildew and anthracnose detection were 86.5% and 86.8%, respectively. The overall detection performance of the improved YOLOv5 network was significantly better compared with those of the original YOLOv5 and the YOLOX_nano network models. The improved model accurately identified plant diseases under natural conditions, and it provides a technical reference for the prevention and control of plant diseases. Full article

(This article belongs to the Topic Grand Challenges of Advanced Technologies in Sustainable Agriculture 4.0: Future Farming, Harvesting and Preservation)

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17 pages, 11037 KiB

Open AccessEditor’s ChoiceArticle

Automatic Bunch Detection in White Grape Varieties Using YOLOv3, YOLOv4, and YOLOv5 Deep Learning Algorithms

by Marco Sozzi, Silvia Cantalamessa, Alessia Cogato, Ahmed Kayad and Francesco Marinello

Agronomy 2022, 12(2), 319; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12020319 - 26 Jan 2022

Cited by 128 | Viewed by 8904

Abstract

Over the last few years, several Convolutional Neural Networks for object detection have been proposed, characterised by different accuracy and speed. In viticulture, yield estimation and prediction is used for efficient crop management, taking advantage of precision viticulture techniques. Convolutional Neural Networks for [...] Read more.

Over the last few years, several Convolutional Neural Networks for object detection have been proposed, characterised by different accuracy and speed. In viticulture, yield estimation and prediction is used for efficient crop management, taking advantage of precision viticulture techniques. Convolutional Neural Networks for object detection represent an alternative methodology for grape yield estimation, which usually relies on manual harvesting of sample plants. In this paper, six versions of the You Only Look Once (YOLO) object detection algorithm (YOLOv3, YOLOv3-tiny, YOLOv4, YOLOv4-tiny, YOLOv5x, and YOLOv5s) were evaluated for real-time bunch detection and counting in grapes. White grape varieties were chosen for this study, as the identification of white berries on a leaf background is trickier than red berries. YOLO models were trained using a heterogeneous dataset populated by images retrieved from open datasets and acquired on the field in several illumination conditions, background, and growth stages. Results have shown that YOLOv5x and YOLOv4 achieved an F1-score of 0.76 and 0.77, respectively, with a detection speed of 31 and 32 FPS. Differently, YOLO5s and YOLOv4-tiny achieved an F1-score of 0.76 and 0.69, respectively, with a detection speed of 61 and 196 FPS. The final YOLOv5x model for bunch number, obtained considering bunch occlusion, was able to estimate the number of bunches per plant with an average error of 13.3% per vine. The best combination of accuracy and speed was achieved by YOLOv4-tiny, which should be considered for real-time grape yield estimation, while YOLOv3 was affected by a False Positive–False Negative compensation, which decreased the RMSE. Full article

(This article belongs to the Special Issue Precision Management to Promote Fruit Yield and Quality in Orchards)

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17 pages, 912 KiB

Open AccessEditor’s ChoiceArticle

Screening of Wheat (Triticum aestivum L.) Genotypes for Drought Tolerance through Agronomic and Physiological Response

by Ali Ahmad, Zubair Aslam, Talha Javed, Sadam Hussain, Ali Raza, Rubab Shabbir, Freddy Mora-Poblete, Tasbiha Saeed, Faisal Zulfiqar, Muhammad Moaaz Ali, Muhammad Nawaz, Muhammad Rafiq, Hany S. Osman, Mohammed Albaqami, Mohamed A. A. Ahmed and Muhammad Tauseef

Agronomy 2022, 12(2), 287; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12020287 - 23 Jan 2022

Cited by 58 | Viewed by 8307

Abstract

Water scarcity is a major challenge to wheat productivity under changing climate conditions, especially in arid and semi-arid regions. During recent years, different agronomic, physiological and molecular approaches have been used to overcome the problems related to drought stress. Breeding approaches, including conventional [...] Read more.

Water scarcity is a major challenge to wheat productivity under changing climate conditions, especially in arid and semi-arid regions. During recent years, different agronomic, physiological and molecular approaches have been used to overcome the problems related to drought stress. Breeding approaches, including conventional and modern breeding, are among the most efficient options to overcome drought stress through the development of new varieties adapted to drought. Growing drought-tolerant wheat genotypes may be a sustainable option to boost wheat productivity under drought stress conditions. Therefore, the present study was conducted with the aim to screen different wheat genotypes based on stress tolerance levels. For this purpose, eleven commonly cultivated wheat genotypes (V₁ = Akbar-2019, V₂ = Ghazi-2019, V₃ = Ujala-2016, V₄ = Zincol-2016, V₅ = Anaj-2017, V₆ = Galaxy-2013, V₇ = Pakistan-2013, V₈ = Seher-2006, V₉ = Lasani-2008, V₁₀ = Faisalabad-2008 and V₁₁ = Millat-2011) were grown in pots filled with soil under well-watered (WW, 70% of field capacity) and water stress (WS, 35% of field capacity) conditions. Treatments were arranged under a completely randomized design (CRD) with three replicates. Data on yield and yield-related traits (tillers/plant, spikelets/spike, grains/spike, 100 grain weight, seed and biological yield) and physio-biochemical (chlorophyll contents, relative water content, membrane stability index, leaf nitrogen, phosphorus, and potassium content) attributes were recorded in this experiment. Our results showed that drought stress significantly affected the morpho-physiological, and biochemical attributes in all tested wheat varieties. Among the genotypes, all traits were found to be significantly (p < 0.05) higher in wheat genotype Faisalabad-2008, including biological yield (9.50 g plant⁻¹) and seed yield (3.39 g plant⁻¹), which was also proven to be more drought tolerant than the other tested genotypes. The higher biological and grain yield of genotype Faisalabad-2008 was mainly attributed to greater numbers of tillers/plant and spikelets/spike compared to the other tested genotypes. The wheat genotype Galaxy-2013 had significantly lower biological (7.43 g plant⁻¹) and seed yield (2.11 g plant⁻¹) than all other tested genotypes, and was classified as a drought-sensitive genotype. For the genotypes, under drought stress, biological and grain yield decreased in the order V₁₀ > V₂ > V₁ > V₄ > V₇ > V₁₁ > V₉ > V₈ > V₃ > V₆. These results suggest that screening for drought-tolerant genotypes may be a more viable option to minimize drought-induced effects on wheat in drought-prone regions. Full article

(This article belongs to the Special Issue Molecular Genetic Improvement of Crop Drought Tolerance)

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19 pages, 2659 KiB

Open AccessEditor’s ChoiceArticle

Impact of Diversified Chemical and Biostimulator Protection on Yield, Health Status, Mycotoxin Level, and Economic Profitability in Spring Wheat (Triticum aestivum L.) Cultivation

by Bozena Lozowicka, Piotr Iwaniuk, Rafal Konecki, Piotr Kaczynski, Nurlan Kuldybayev and Yerlan Dutbayev

Agronomy 2022, 12(2), 258; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12020258 - 20 Jan 2022

Cited by 24 | Viewed by 2759

Abstract

Biostimulators with chemical protection are a challenge in sustainable agriculture to obtain high yield, healthy, and pesticide-free wheat. The aim of this four-year spring wheat field experiment was to assess the effectivity of using herbicide, mixed fungicides protection, and a humic biostimulator. The [...] Read more.

Biostimulators with chemical protection are a challenge in sustainable agriculture to obtain high yield, healthy, and pesticide-free wheat. The aim of this four-year spring wheat field experiment was to assess the effectivity of using herbicide, mixed fungicides protection, and a humic biostimulator. The following treatments were tested: biostimulator (S), sulfosulfuron (H), H + S, H + propiconazole + cyproconazole/spiroxamin + tebuconazole + triadimenol (H + F1 + F2), and H + F1 + F2 + S. Evaluations of wheat yield and fungal diseases (Septoria tritici blotch, eyespot, sharp eyespot, Fusarium spp.) were performed using visual and qPCR methods. Thirteen mycotoxins were analyzed by LC–MS/MS. Infestations of six weeds were examined visually. Temperatures and precipitation data of the vegetative seasons were monitored. Precipitation most affected the occurrence of leaf diseases despite the same chemical/biostimulator treatments (up to 48% Septoria tritici blotch severity for the S treatment). The highest mean yield was obtained for H + F1 + F2 + S (5.27 t ha⁻¹), while the lowest level of mycotoxins was obtained for H + F1 + F2 (221.68 µg kg⁻¹). For H + S, a greater reduction of mycotoxins was determined compared to the H treatment (27.18%), as well as a higher severity of eyespot (18%) and sharp eyespot (24%). In 2017–2020, the most effective reduction of weed infestation and Fusarium spp. DNA on ears was indicated for H + F1 + F2 (16 g and 0.88 pg g⁻¹ DNA, respectively). The greatest saved production value (196.15€) was determined for H + F1 + F2 + S. Full article

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14 pages, 1784 KiB

Open AccessEditor’s ChoiceArticle

The Effect of NaCl Stress on the Response of Lettuce (Lactuca sativa L.)

by Włodzimierz Breś, Tomasz Kleiber, Bartosz Markiewicz, Elżbieta Mieloszyk and Monika Mieloch

Agronomy 2022, 12(2), 244; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12020244 - 19 Jan 2022

Cited by 31 | Viewed by 5244

Abstract

In recent decades, increasing human pressure has caused the gradual deterioration of the physical and chemical properties of water and soil. Salinity is an important factor influencing the quality of water. The aim of this comprehensive research was to determine the effect of [...] Read more.

In recent decades, increasing human pressure has caused the gradual deterioration of the physical and chemical properties of water and soil. Salinity is an important factor influencing the quality of water. The aim of this comprehensive research was to determine the effect of increasing concentrations of sodium chloride, which is a salinity inducer, on the yield, photosynthesis efficiency (expressed with chlorophyll fluorescence measurement) and content of selected nutrients in the leaves of hydroponically grown lettuce (Lactuca sativa L.). Experiments were conducted at the following concentrations of NaCl: 0 (control treatment), 10, 20, 40, and 60 mmol L⁻¹. Studies were conducted in two independent seasons: spring and autumn. The plants exposed to NaCl stress modified their chemical composition by lowering the uptake of (for 60 mmol L⁻¹ NaCl in relation to control): N (−11%), K (−35.7%), and Mg (−24.5%), while increasing the sodium content (+2400%). The Na:K ratio was significantly narrowed (from 76:1 to 2.6:1). The increase in the Cl level in the lettuce leaves may also have caused a decrease in the content of nitrates. As a result of disturbed ionic balance, the RWC was significantly reduced (−6.2%). As a result of these changes, the yield of the biomass of the aerial parts decreased (more than two-fold for the highest NaCl concentration in relation to control) whereas the dry matter content increased (+32%). The measurement of fluorescence showed significant changes at the PSII level. Salinity modified the energy flow rate (F₀, F_M, F_V, F_V/F_M) as well as the specific energy flows through the reaction centre (ABS/RC, TR₀/RC, ET₀/RC, DI₀/RC). The PSII functioning index, calculated on the basis of energy absorption (PI_Abs), also changed. The salinity induced with NaCl significantly worsened the physiological reactions of the plants in the PSII, changed the ionic balance, which resulted in a significantly lower yield of the plants. Due to increasing water quality problems, it will be necessary to use, in agriculture on a much larger scale than before, saline water treatment systems (e.g., highly effective nanofiltration and/or reverse osmosis). Full article

(This article belongs to the Section Horticultural and Floricultural Crops)

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24 pages, 2257 KiB

Open AccessEditor’s ChoiceArticle

Soil Nutrient Retention and pH Buffering Capacity Are Enhanced by Calciprill and Sodium Silicate

by Ji Feng Ng, Osumanu Haruna Ahmed, Mohamadu Boyie Jalloh, Latifah Omar, Yee Min Kwan, Adiza Alhassan Musah and Ken Heong Poong

Agronomy 2022, 12(1), 219; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12010219 - 17 Jan 2022

Cited by 33 | Viewed by 5582

Abstract

In the tropics, warm temperatures and high rainfall contribute to acidic soil formation because of the significant leaching of base cations (K⁺, Ca²⁺, Mg²⁺, and Na⁺), followed by the replacement of the base cations with [...] Read more.

In the tropics, warm temperatures and high rainfall contribute to acidic soil formation because of the significant leaching of base cations (K⁺, Ca²⁺, Mg²⁺, and Na⁺), followed by the replacement of the base cations with Al³⁺, Fe²⁺, and H⁺ ions at the soil adsorption sites. The pH buffering capacity of highly weathered acid soils is generally low because of their low pH which negatively impacts soil and crop productivity. Thus, there is a need to amend these soils with the right amount of inorganic liming materials which have relatively high neutralizing values and reactivity to overcome the aforementioned problems. Soil leaching and the pH buffering capacity studies were conducted to determine whether the co-application or co-amendment of a calcium carbonate product (Calciprill) and sodium silicate can improve soil nutrient retention and pH buffering capacity of the Bekenu series (Typic Paleudults). A 30 day soil leaching experiment was carried out using a completely randomized design with 16 treatments and 3 replications after which the leached soil samples were used for a pH buffering capacity study. The Calciprill and sodium silicate treatments significantly improved soil pH, exchangeable NH₄⁺, available P, exchangeable base cations, Effective Cation Exchange Capacity (ECEC), and pH buffering capacity in comparison with the untreated soil. The improvements were attributed to the alkalinity of Calciprill and sodium silicate due to their high inherent K⁺, Ca²⁺, Mg²⁺, and Na⁺ contents. The neutralizing effects of the amendments impeded the hydrolysis of Al³⁺ (96.5%), Fe²⁺ (70.4%), and Mn²⁺ (25.3%) ions resulting in fewer H⁺ ions being produced. The co-application of Calciprill and sodium silicate reduced the leaching of Ca²⁺ (58.7%) and NO₃⁻ (74.8%) from the amended soils. This was due to the ability of sodium silicate to reduce soil permeability and protect the Calciprill and available NO₃⁻ from being leached. This also improved the longevity of Calciprill to enhance the soil pH buffering capacity. However, the amounts of NH₄⁺, P, and base cations leached from the amended soils were higher compared with the un-amended soils. This was due to the high solubility of sodium silicate. The most suitable combination amendment was 7.01 g Calciprill and 9.26 g sodium silicate (C2S5) per kilogram soil. It is possible for farmers to adopt the combined use Calciprill and sodium silicate to regulate soil nutrient retention and improve the soil pH buffering capacity of highly weathered acidic soils. This will enhance soil and crop productivity. Full article

(This article belongs to the Topic Soil Fertility and Plant Nutrition for Sustainable Agriculture)

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15 pages, 2369 KiB

Open AccessEditor’s ChoiceArticle

The Effect of the Application of Stimulants on the Photosynthetic Apparatus and the Yield of Winter Wheat

by Kamil Kraus, Helena Hnilickova, Jan Pecka, Marie Lhotska, Alena Bezdickova, Petr Martinek, Lenka Kucirkova and Frantisek Hnilicka

Agronomy 2022, 12(1), 78; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12010078 - 30 Dec 2021

Cited by 5 | Viewed by 2412

Abstract

The use of stimulation preparations seems to be a promising means for mitigating the effects of abiotic and biotic stressors. Their significance includes plant organism stimulation and metabolism optimisation, water regime, and nutrition during periods of stress. They help bridge it over and [...] Read more.

The use of stimulation preparations seems to be a promising means for mitigating the effects of abiotic and biotic stressors. Their significance includes plant organism stimulation and metabolism optimisation, water regime, and nutrition during periods of stress. They help bridge it over and create conditions for rapid regeneration. In a field experiment, the effect of the application of stimulation preparations on cultivars Triticum aestivum L. with different genetic composition was evaluated (donor of blue aleurone colour KM-72-18; donor of a multi-row spike (MRS) KM-94-18). Our results show a predominantly positive effect of the application of stimulants on the yield and thousand-grain weight (TKW). The results obtained were influenced by the year, based on different temperatures and precipitation. Higher yields were achieved in 2020 with higher total precipitation during the grain filling period and with a higher maximum quantum yield of the photosystem II (Fv/Fm). In 2019, this period was significantly dry and warm, which was reflected in a lower yield and TKM, higher proline content in the leaves, and lower Fv/Fm values. In both experimental years, there was a higher yield of the cultivar with blue aleurone (KM-72-18). In the case of cultivars with coloured grains, the promising use of the content substances in cultivars as natural means of increasing resistance to abiotic and biotic stressors seems to be promising. Full article

(This article belongs to the Special Issue Alternative Cropping Systems for Climate Change)

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