Agriculture, Volume 11, Issue 10 (October 2021) – 122 articles

Rice is a primary food for more than three billion people worldwide and cultivated on about 12% of the world’s arable land. However, more than 88% production is observed in Asian countries, including Pakistan. Due to higher population growth and recent climate change scenarios, it is crucial to get timely and accurate rice yield estimates and production forecast of the growing season for governments, planners, and decision makers in formulating policies regarding import/export in the event of shortfall and/or surplus. This study aims to quantify the rice yield at various phenological stages from hyper-temporal satellite-derived-vegetation indices computed from time series Sentinel-II images. Different vegetation indices (viz. NDVI, EVI, SAVI, and REP) were used to predict paddy yield. The predicted yield was validated through RMSE and ME statistical techniques. The integration of PLSR and sequential time-stamped vegetation indices accurately predicted rice yield (i.e., maximum R² = 0.84 and minimum RMSE = 0.12 ton ha⁻¹ equal to 3% of the mean rice yield). Moreover, our results also established that optimal time spans for predicting rice yield are late vegetative and reproductive (flowering) stages. The output would be useful for the farmer and decision makers in addressing food security. Full article

The antioxidant and antifungal activities of crude hydro-ethanolic extract from Capparis spinosa L. (Capparidaceae) leaves and their fractions, obtained by liquid-liquid extraction (LLE) using solvents with increasing polarity (hexane, diethyl ether, ethyl acetate, butanol, and water), were investigated. The crude extract and the obtained fractions were characterized by colorimetric analysis, pyrolysis-gas chromatography (GC)-mass spectroscopy (MS), Fourier Transform Infrared Spectroscopy, and their antioxidant and antifungal capacity were determined. It was observed that the ethyl acetate fraction was enriched in polyphenols, the butanol fraction resulted in purified from proteins and the residual aqueous fraction contains more hydrophobic compounds. The evaluation of the antioxidant activity revealed that the ethyl acetate fraction possesses an interesting capacity 1,1-diphenyl-2-picrylhydrazyl(DPPH) radical scavenging with a percentage of inhibition of 84.02% at a concentration of 2 mg/mL and better ferric reducing antioxidant power (FRAP) 4.275 ± 0.011 mmol/g of dry sample than the other fractions tested. Regarding the antifungal activity, the diethyl ether fraction showed the highest activity against Aspergillus niger with 58.78% of inhibition. The results obtained in this work showed the relevance of the valorization of the leaves of Capparis spinosa L., given its richness in bioactive molecules can be regarded as a natural source of antioxidant and antifungal and may be considered in the future to replace synthetic preservatives in food, pharmaceutic products and cosmetic. Full article

The urgent need to implement agricultural systems that provide greater sustainability and resilience to the challenges of the climate change process has meant that alternative paradigms for agri-food systems and agriculture have become more relevant in recent times. In this study, we present the building process and consolidation of an agro-ecological project (Extiercol) in a rural area of southern Spain, with a prolonged depopulation process and close connections to nearby urban areas. Through participatory action research, the specific objectives of this study are (1) to describe the agroecological collective process from its creation by a youth association to its establishment as a viable agricultural project; (2) to identify the drivers for the development of this type of transition process towards agricultural sustainability and (3) to analyse urban-rural alliances in the establishment of agroecological projects. Finally, the replicability of this project was assessed, with a special focus on the main barriers to be addressed in order to implement this agricultural system such as difficult to land access or a negative perception of sustainable management by farmers. Through this study we have shown how the connection between the food production area and nearby urban areas can be achieved through an agroecological project. Full article

In Huang-Huai-Hai plain of China, farmers collect the maize straw for livestock during maize harvest to increase their revenue. To maintain the sustainable productivity of the soil, all straw after the wheat harvest is returned to the field. This straw brings difficulties in the no-till seeding for maize after wheat harvest, and thus it is necessary to develop efficient no-till seeders that can cope with heavy residue and improve sowing quality. In this work, we designed a wide-strip-till no-till pneumatic maize (WNPM) seeder to satisfy the need in this plain. The key parameters of the opposite-placed anti-blocking mechanism of the WNPM seeder were determined via the discrete element method (DEM) technology, while the parameters of the pneumatic maize seed meter were specified using the coupled simulation of computational fluid dynamics (CFD) and DEM. We also carried out field experiment to test the performance of our machine. Under the operating speed of 8 km/h, the soil disturbance was 38.2%. Moreover, the straw cleaning rate achieved 94.4% in the seeding belt while the residue cover index of the seed plot was over 58%, and the seeding performance was improved significantly. The qualified seed spacing index, uniformity variation coefficient, qualified index of sowing depth and variation coefficient of sowing depth were 96.6%, 19.1%, 95.1% and 3.2%, respectively. In general, the WNPM seeder improves the working efficiency of maize sowing because both the reliable working speed and the sowing quality were increased. These results are of considerable importance for crop production in Huang-Huai-Hai plain of China. Full article

Since management practices profoundly influence soil characteristics, the adoption of sustainable agro-ecological practices is essential for soil health conservation. We compared soil health in organic and conventional fields in the Abruzzi region (central Italy) by using (1) the soil biology quality (QBS) index (which expresses the level of specialisation in soil environment shown by microarthropods) and (2) microarthropod diversity expressed by Hill numbers. QBS values were calculated using both the original formulation based on only presence/absence data and a new abundance-based version. We found that organic management improves soil biology quality, which encourages the use of organic farming to maintain soil health. Including arthropod abundance in QBS calculation does not change the main outcomes, which supports the use of its original, speedier formulation. We also found that agricultural fields included in protected areas had greater soil health, which shows the importance of the matrix in determining agricultural soil health and highlights the importance of land protection in preserving biodiversity even in managed soils. Finally, we found that soil biology quality and microarthropod community structure are distinctly influenced by certain physical and chemical characteristics of the soil, which supports the use of microarthropods as biological indicators. Full article

The paper aims at testing an innovative organic fertilizer obtained from waste by processing a mixture of marine algae biomass, sewage municipal sludge and farmyard manure. Design of this polycomposite fertilizer is based on adequate conceptual and experimental models by taking into account the complex interactions among these three biomasses. In the first step a detail physico-chemical analysis has been performed on the composition of the three raw materials and also on the soil. In the second phase similar analyses have been carried out on representative samples of soil treated with the compost as compared with untreated soil samples. Analytical methods applied were FT-IR spectroscopy in correlation with organic/inorganic and total carbon (TOC/TIC/TC) analysis. The efficiency of applying this compost on the field at large scale has been assessed by means of fatty acid content of the oleaginous plants cultivated. Based on correlation between production quality and chemical composition of the composted soil, the optimal proportions of the mixture of the three organic wastes will be selected for designing an eco-friendly fertilizer able to improve agrochemical properties of the soil. Full article

Recent Society 5.0 efforts by the Government of Japan are aimed at establishing a sustainable human-centered society by combining new technologies such as sensor networks, edge computing, Internet of Things (IoT) ecosystems, artificial intelligence (AI), big data, and robotics. Many research works have been carried out with an increasing emphasis on the fundamentals of wireless sensor networks (WSN) for different applications; namely precision agriculture, environment, medical care, security, and surveillance. In the same vein, almost all of the known authentication techniques rely on the single gateway node, which is unsuitable for the current sensor nodes that are broadly distributed in the real world. Despite technological advances, resource constraints and vulnerability to an attacker physically capturing some sensor nodes have remained an important and challenging research field for developing wireless sensor network user authentication. This work proposes a new authentication scheme for agriculture professionals based on a multi-gateway communication model using a fuzzy extractor algorithm to support the Society 5.0 environment. The scheme provides a secure mutual authentication using the well-established formal method called BAN logic. The formal security verification of the proposed scheme is validated with the AVISPA tool, a powerful validation method for network security applications. In addition, the security of the scheme was informally analyzed to demonstrate that the scheme is secure from different attacks, e.g., sensor capture, replay, and other network and physical attacks. Furthermore, the communication and computation costs of the proposed scheme are evaluated and show better performance than the existing authentication schemes. Full article

New Zealand hill country sheep and beef farms contain land of various slope classes. The steepest slopes have the lowest pasture productivity and livestock carrying capacity and are the most vulnerable to soil mass movements. A potential management option for these areas of a farm is the planting of native shrubs which are browsable and provide erosion control, biodiversity, and a source of carbon credits. A bioeconomic whole farm model was developed by adding a native shrub sub-model to an existing hill country sheep and beef enterprise model to assess the impacts on feed supply, flock dynamics, and farm economics of converting 10% (56.4 hectares) of the entire farm, focusing on the steep slope areas, to native shrubs over a 50-year period. Two native shrub planting rates of 10% and 20% per year of the allocated area were compared to the status quo of no (0%) native shrub plantings. Mean annual feed supply dropped by 6.6% and 7.1% causing a reduction in flock size by 10.9% and 11.6% for the 10% and 20% planting rates, respectively, relative to 0% native shrub over the 50 years. Native shrub expenses exceeded carbon income for both planting rates and, together with reduced income from sheep flock, resulted in lower mean annual discounted total sheep enterprise cash operating surplus for the 10% (New Zealand Dollar (NZD) 20,522) and 20% (NZD 19,532) planting scenarios compared to 0% native shrubs (NZD 22,270). All planting scenarios had positive Net Present Value (NPV) and was highest for the 0% native shrubs compared to planting rates. Break-even carbon price was higher than the modelled carbon price (NZD 32/ New Zealand Emission Unit (NZU)) for both planting rates. Combined, this data indicates planting native shrubs on 10% of the farm at the modelled planting rates and carbon price would result in a reduction in farm sheep enterprise income. It can be concluded from the study that a higher carbon price above the break-even can make native shrubs attractive in the farming system. Full article

Increasing milk production is one of the key concerns in animal production. Traditional breeding has gotten limited achievement in the improvement of milk production because of its moderate heritability. Milk production traits are controlled by many genes. Thus, identifying candidate genes associated with milk production traits may provide information that can be used to enhance the accuracy of animal selection for moderately heritable traits like milk production. The genomic selection can enhance the accuracy and intensity of selection and shortening the generation interval. The genetic progress of economically important traits can be doubled with the accuracy of selection and shortening of generation interval. Genome-wide association studies (GWAS) have made possible the screening of several single nucleotide polymorphisms (SNPs) in genes associated with milk production traits in dairy cattle. In addition, RNA-sequencing is another well-established tool used to identify genes associated with milk production in dairy cattle. Although it has been widely accepted that these three methods (GWAS, RNA-seq and DNA sequencing) are considered the first step in the screening of genes, however, the outcomes from GWAS, DNA-sequencing and RNA-seq still need further verification for the establishment of bonafide causal variants via genetic replication as well as functional validation. In the current review, we have highlighted genetic markers identified (2010-to date) for their associations with milk production traits in dairy cattle. The information regarding candidate genes associated with milk production traits provided in the current review could be helpful to select the potential genetic markers for the genetic improvement of milk production traits in dairy cattle. Full article

Powdery mildew on barley, caused by the pathogen Blumeria graminis f. sp. hordei, occurs worldwide and can result in severe yield loss. Germplasm of barley, including landraces, commercial cultivars, wild relatives and breeding lines are stored in more than 200 institutions. There is a need for characterization of this germplasm in terms of resistance to biotic and abiotic stresses. This is necessary in order to use specific accessions in breeding programs. In the present study, 129 barley landraces originated from Turkey and provided by the ICARDA genebank were tested for resistance to powdery mildew. Seedling resistance tests after inoculation with 19 differentiated isolates of B. graminis f. sp. hordei were used to postulate the presence of resistance genes. From the 129 landraces studied, plants of 19 (14.7%) of them showed resistance to infection with powdery mildew. Based on preliminary tests from these 19 landraces, 25 resistant single plant lines were selected for testing with differential powdery mildew isolates. Seven lines were resistant to all 19 isolates used. However, only one line (5583-1-4) showed resistance scores of zero against all isolates used. It is likely that this line possesses unknown, but highly effective genes for resistance. In five resistant lines it was not possible to postulate the presence of specific resistance genes. In 19 lines the presence of the genes Mlp, Mlk, Mlh, Mlg, Ml(CP), Mlat, Mla3, Mla6, Mla7 and Mla22 were postulated. These new sources of highly effective powdery mildew resistance in barley landraces from Turkey could be successfully used in breeding programs. Full article

Fresh-cut vegetables are prone to microbiological contamination and oxygenation during handling and storage. In this study, fresh-cut amaranth was subjected to various gas ratios (5–15% O₂, 5–15% CO₂, 80% N₂) for 12 days. Chlorophyll content, ascorbic acid content, antioxidant enzyme activity, microbial population, and physiological and biochemical indicators were measured to evaluate the impact of atmospheric packaging. Suitable atmospheric packaging could slow the respiration of amaranth, delay the decline in physiological and biochemical characteristics, maintain the antioxidant enzyme activity, promote the sensorics, and prolong the shelf life by 2 days. According to the analysis of the results, modified atmospheric packaging (10% O₂, 10% CO₂, 80% N₂) retarded the decline in fresh-cut amaranth quality, provided effective antioxidative browning, and inhibited Pseudomonas fluorescens development. Full article

The water buffalo (Bubalus bubalis) is known for its unique utilization of low-quality fibrous feeds and outstanding digestion performance, highlighting its role as an animal model in studying fiber fractions degradation. Among roughage, lignin attracted wide attention in ruminant nutrition studies, which affects animal digestibility. Therefore, the present study aims to investigate the functional relation between three lignin monomeric compositions of coniferyl alcohol (G), ρ-coumaryl alcohol (H) and sinapyl alcohol (S) and ruminal fiber degradation in water buffalo. Hence, three female water buffaloes (Nili-Ravi × Mediterranean, five years old, 480 ± 20 kg) were assigned for an in vivo study by utilizing the nylon-bag method, examining eight kinds of roughage. All the experimental roughage types were analyzed for the effective degradability (ED) of neutral detergent fiber (NDF), acid detergent fiber (ADF), acid detergent lignin (ADL), cellulose (CEL) and hemicellulose (HC) fractions. Then, prediction models for the roughage fiber degradation were established based on the characteristics of lignin monomer content. The results showed that S, S/G and S/(G+S+H) were positively correlated with the ED of NDF, ADF, CEL and HC; H/S was negatively correlated. For the effective degradability of ADL (ADLD), S and S/(G+S+H) were positively correlated with it; H, H/G, H/S and H/(G+S+H) were negatively correlated. The model with the highest fitting degree was ADLD = 0.161 − 1.918 × H + 3.152 × S (R² = 0.758, p < 0.01). These results indicated that the lignin monomer composition is closely related to the utilization rate of roughage fiber. S-type lignin monomer plays a vital role in the fiber degradation of roughage. The experiment found the effect of lignin monomer composition on the degradation of fiber fractions using buffalo as the experimental animal and constructed prediction models, providing a scientific basis for building a new technological method using lignin composition to evaluate buffalo roughage. Furthermore, the capacity of ADL degradation of buffalo was proved in this experiment. In order to further explore the ability of lignin degradation by the buffalo, the DNA of rumen microorganisms was extracted for sequencing. The top three composition of rumen microorganisms at the genus level were Prevotella_1, 226, Rikenellaceae_RC9_gut_group and Ruminococcaceae_UCG-011. Six strains with lignin degradation ability were screened from buffalo rumen contents. This experiment also revealed that the buffalos possess rumen microorganisms with lignin degradation potential. Full article

When an octopus grasps something, the rigidity of its tentacle can change greatly, which allowing for unlimited freedom, agility, and precision. Inspired by this, a three-finger flexible bionic robot gripper was designed for apple picking. First, a flexible chamber finger was designed to drive the gripper finger to elongate, shorten, and bend, which works through a process of inflating and deflating. Further, we proposed a three-finger mode to achieve two kinds of motion states: grasping and relaxing, by simulating the movement of an octopus grasping at something. In this paper, we evaluated the bending property of the designed flexible bionic gripper through an apple grasping experiment. The experimental results show that the 100.0 g bionic gripper can load an apple with a weight of 246.5~350.0 g and a diameter of 69.0~99.0 mm, and the grasping success rate is 100%. It has a good grasping performance. Compared to other soft grippers, the proposed bionic flexible gripper has the advantages of being lightweight, and having good cushioning, low driving air pressure, and a strong grasping force. Full article

Monitoring of sows’ health is the key to preventing and controlling diseases in sows, and it guarantees optimal rearing conditions for piglets. The aim of this study was to investigate the relationship between the health status of sows shortly after parturition, and to analyze thermographic images of the mammary gland and the sows’ performance. Clinical examination of a total of 513 db.Viktoria hybrid sows was bundled individually using a modified score system. According to this, animals were divided into three health classes: healthy, clinically suspicious, and diseased. Simultaneously, the mammary glands were investigated by infrared thermography. Total born piglets (TBP), number of piglets born alive (NBA), and the daily weight gain of the piglets were significantly lower in the diseased group (p < 0.05). Regarding the results of the thermographic images of the mammary gland, significantly higher mean value of the warmest pixels was found in the diseased group (38.3 °C ± 0.57), while the significantly lowest value was reported in the healthy group (37.2 °C ± 0.54; p < 0.05). The results of this study show that thermography of the mammary gland at birth contains information that can help to identify diseased animals whose disease has negative effects on their piglets. Full article

Bottom ash (BA), a byproduct of coal combustion from electric power plants with a porous surface texture and high pH, may influence the physical and chemical properties of upland arable soil associated with nitrous oxide (N₂O) emission from upland soil. This study evaluated the use of BA in mitigating N₂O emissions from upland arable soil and increasing the crop yield. In a field experiment, N₂O emitted from the soil was monitored weekly in a closed chamber over a 2-year period (2018–2019). BA was applied to upland soil at the rates of 0, 200, and 400 Mg·ha⁻¹. Cumulative N₂O emission significantly decreased with increasing BA application rate; it decreased by 55% with a BA application rate of 400 Mg·ha⁻¹ compared with the control. Yield-scaled N₂O emission decreased with increasing BA application rates of up to 200 Mg·ha⁻¹. Water-filled pore spaces (WFPS) were 70.2%, 52.9%, and 45.3% at the rates of 0, 200, and 400 Mg·ha⁻¹, respectively, during the growing season. For economic viability and environmental conservation, we suggest that BA application at a rate of 200 Mg·ha⁻¹ reduces N₂O emissions per unit of crop production. Full article

The accurate detection of canopy characteristics is the basis of precise variable spraying. Canopy characteristics such as canopy density, thickness and volume are needed to vary the pesticide application rate and adjust the spray flow rate and air supply volume. Canopy thickness is an important canopy dimension for the calculation of tree canopy volume in pesticide variable spraying. With regard to the phenomenon of ultrasonic waves with multiple reflections and the further analysis of echo signals, we found that there is a proportional relationship between the canopy thickness and echo interval time. In this paper, we propose a method to calculate canopy thickness using echo signals that come from ultrasonic sensors. To investigate the application of this method, we conducted a set of lab-based experiments with a simulated canopy. The results show that we can accurately estimate canopy thickness when the detection distance, canopy density, and canopy thickness range between 0.5and 1.5 m, 1.2 and 1.4, and 0.3and 0.6 m, respectively. The relative error between the estimated value and actual value of the simulated canopy thickness is no higher than 8.8%. To compare our lab results with trees in the field, we measured canopy thickness from three naturally occurring Osmanthus trees (Osmanthus fragrans Lour). The results showed that the mean relative errors of three Osmanthus trees are 19.2%, 19.4% and 18.8%, respectively. These results can be used to improve measurements for agricultural production that includes both orchards and facilities by providing a reference point for the precise application of variable spraying. Full article

Beyond the use of 2D images, the analysis of 3D images is also necessary for analyzing the phenomics of crop plants. In this study, we configured a system and implemented an algorithm for the 3D image reconstruction of red pepper plant (Capsicum annuum L.), as well as its automatic analysis. A Kinect v2 with a depth sensor and a high-resolution RGB camera were used to obtain more accurate reconstructed 3D images. The reconstructed 3D images were compared with conventional reconstructed images, and the data of the reconstructed images were analyzed with respect to their directly measured features and accuracy, such as leaf number, width, and plant height. Several algorithms for image extraction and segmentation were applied for automatic analysis. The results showed that the proposed method showed an error of about 5 mm or less when reconstructing and analyzing 3D images, and was suitable for phenotypic analysis. The images and analysis algorithms obtained by the 3D reconstruction method are expected to be applied to various image processing studies. Full article

The identification of agricultural food production systems has gained importance in order to protect both human health and the environment. The importance of organic production system of agriculture which involves the application of natural processes and substances, and limits or completely eliminates the use of synthesized means is emphasized. Knowledge of the mineral composition in tomato samples can be used as a potent tool in the identification of chemical markers as potential indicators of the farming system. A set of tomato samples taken from two factorial randomized trials were comprehended eight different varieties, belonging to four tomato types: large—BEEF and CLUSTER, and mini and midi—CHERRY and PLUM tomatoes, cultivated under two different farming systems: integral (IPM) and organic (O) were characterized based on the composition of the minerals. A total of 44 elements were quantified. To establish criteria for the classification of the samples and confirm a unique set of parameters of variation among the types of production, sophisticated chemometric techniques were used. The results indicate that the accumulation of elements varies between 8 tomato varieties and 2 different growing systems. The contents of Al, Mn, As, Pb, and some of the rare-earth elements (REEs) are able to distinguish between production types. Examination of different hybrids, which belong to different types in two production systems: organic and integral within Zeleni hit (official Enza and Vitalis trial and breeding station), was done with the aim of reaching a methodology of diversification, ie complete traceability of organic production, and to contribute to distinguishing types of agricultural systems and enhancing the possibility of acquiring a valuable authenticity factor about the type of agricultural production system employed for the cultivation of tomatoes. Full article

Due to the growing world population, the challenge for the agriculture industry is to produce the right amount of food. This is not possible without the use of fertilizers. Unfortunately, apart from having a positive effect on the yield parameters, they can also adversely affect the natural environment. The use of fertilizers in excess or in a poorly digestible form causes the migration of fertilizer components beyond the reach of the plant root system. In this way, nutrients enter the groundwater, surface water and the atmosphere, contaminating them. The consequence of such actions is further climate warming and the deterioration of water status and air quality. Suspension fertilizers are an interesting proposition that meets the requirements of modern agriculture. They combine the advantages of liquid and solid fertilizers. The liquid form ensures better digestibility of the nutrients, especially in periods of drought, and the concentration of the ingredients is comparable to that of solid fertilizers. At the same time, production costs are lower, which is related to the simplification of the technological process and the possibility of using cheaper raw materials. A valuable advantage of fertilizer suspension is the possibility of using hydrated waste substances in their production. Full article

Assessing the potential drivers of farmers using pesticidal plants for crop protection is essential for wider adoption. However, few studies have focused on collaborative assessments of the underlying trade-offs when using pesticidal plant extracts for pest control. Smallholder farmers in northern Tanzania involved in farmer driven research assessing pesticidal plants evaluated the costs, benefits, trade-offs and areas for future investment. A questionnaire was used to collect demographic information from 77 farmers and their views on pest problems and crop protection in common bean production. This was followed by small focus group discussions (n = 9) using a participatory framework to elucidate the costs and benefits of adopting pesticidal plant technology. A multiple correspondence analysis showed that pesticidal plant use was associated with men greater than 50 years old, and synthetic pesticide use was associated with younger aged farmers and women. Farmers who used synthetics generally did not report the presence of common pest species found in common bean production, whereas farmers who used pesticidal plants were associated with more frequent reports of pest species. This participatory cost–benefit analysis highlighted that tools and processing challenges were the main costs to using pesticidal plants. The main benefit reported when using pesticidal plants was a general improvement to family health. Farmers expressed overall a positive outcome when using pesticidal plants for crop protection and recommended that future investments focus on improving access to tools and education regarding plant processing and extraction to improve uptake of the technology by smallholder farmers. Full article

While food production and consumption processes worldwide are characterized by geographical and social distance, alternative food networks aim to reconnect producers and consumers. Our study proposes a framework to distinguish multiple dimensions of proximity in the context of Community Supported Agriculture (a type of alternative food network) and to quantitatively evaluate them. In a principal component analysis, we aggregated various detailed proximity items from a multinational survey using principal component analysis and examined their relationship with the attractiveness of Community Supported Agriculture in a multiple regression analysis. Our findings highlight the importance of relational proximity and thus of increasing trust, collaboration, and the sharing of values and knowledge within and across organizations in the food system. Rather than focusing on spatial proximity, increasing relational proximity might support alternative food networks, such as Community Supported Agriculture. Full article

This study aimed to estimate the environmental impact of barley production in the Basque Country, Northern Spain, using cradle-to-gate life cycle assessment (LCA) methodology, as well as to assess how methodological choices (i.e., the use of IPCC 2019 Guidelines versus allocation methods) can influence such estimation. The production of mineral fertiliser and the direct emissions of nitrous oxide (N₂O) resulting from the application of nitrogen (N) fertiliser were identified as the two main contributors (40% and 30% of all greenhouse gas emissions, respectively) to the environmental impact of barley production. Pertaining to GHG emissions themselves, the use of calcium ammonium nitrate fertiliser was found to be the main contributor. Therefore, the optimization of N fertiliser application was established as a key process to reduce the environmental impact of barley production. The fertiliser-related release of N and phosphorous (P) to the environment was the main contributor to particulate matter formation, terrestrial acidification, and terrestrial and marine eutrophication. The incorporation of environmental data on NH₃, NO_x, NO₃⁻, and PO₄³⁻ to the LCA led to a more accurate estimation of barley production impact. A sensitivity analysis showed that the use of economic allocation, compared to mass allocation, increased the estimation of climate change-related impact by 80%. In turn, the application of the IPCC 2019 Refinement Guidelines increased this estimation by a factor of 1.12 and 0.86 in wet regions and decreased in dry regions, respectively. Our results emphasise the importance of the choice of methodology, adapted to the specific case under study, when estimating the environmental impact of food production systems. Full article

Weeds are among the most harmful abiotic factors in agriculture, triggering significant yield loss worldwide. Remote sensing can detect and map the presence of weeds in various spectral, spatial, and temporal resolutions. This review aims to show the current and future trends of UAV applications in weed detection in the crop field. This study systematically searched the original articles published from 1 January 2016 to 18 June 2021 in the databases of Scopus, ScienceDirect, Commonwealth Agricultural Bureaux (CAB) Direct, and Web of Science (WoS) using Boolean string: “weed” AND “Unmanned Aerial Vehicle” OR “UAV” OR “drone”. Out of the papers identified, 144 eligible studies did meet our inclusion criteria and were evaluated. Most of the studies (i.e., 27.42%) on weed detection were carried out during the seedling stage of the growing cycle for the crop. Most of the weed images were captured using red, green, and blue (RGB) camera, i.e., 48.28% and main classification algorithm was machine learning techniques, i.e., 47.90%. This review initially highlighted articles from the literature that includes the crops’ typical phenology stage, reference data, type of sensor/camera, classification methods, and current UAV applications in detecting and mapping weed for different types of crop. This study then provides an overview of the advantages and disadvantages of each sensor and algorithm and tries to identify research gaps by providing a brief outlook at the potential areas of research concerning the benefit of this technology in agricultural industries. Integrated weed management, coupled with UAV application improves weed monitoring in a more efficient and environmentally-friendly way. Overall, this review demonstrates the scientific information required to achieve sustainable weed management, so as to implement UAV platform in the real agricultural contexts. Full article

The leaf is the organ that is crucial for photosynthesis and the production of nutrients in plants; as such, the number of leaves is one of the key indicators with which to describe the development and growth of a canopy. The irregular shape and distribution of the blades, as well as the effect of natural light, make the segmentation and detection process of the blades difficult. The inaccurate acquisition of plant phenotypic parameters may affect the subsequent judgment of crop growth status and crop yield. To address the challenge in counting dense and overlapped plant leaves under natural environments, we proposed an improved deep-learning-based object detection algorithm by merging a space-to-depth module, a Convolutional Block Attention Module (CBAM) and Atrous Spatial Pyramid Pooling (ASPP) into the network, and applying the smooth_L1 function to improve the loss function of object prediction. We evaluated our method on images of five different plant species collected under indoor and outdoor environments. The experimental results demonstrated that our algorithm which counts dense leaves improved average detection accuracy of 85% to 96%. Our algorithm also showed better performance in both detection accuracy and time consumption compared to other state-of-the-art object detection algorithms. Full article

Termites can play a localized prominent role in soil nutrient availability and cycling because mound materials are often enriched in nutrients relative to surrounding soil. Mound materials may thus prove to be useful amendments, though evidently mound spatial arrangement needs to be considered as well. Furthermore, it is not known if gradients of soil properties exist from termite mound to interspace sites. Studying both aspects would be required to decide whether spreading of mounds or spatially differentiated management of surrounding crop to accommodate soil fertility gradients would be valid nutrient-management strategies. Mound abundance and mass were estimated at 9 and 4 mounds ha⁻¹, representing 38.9 and 6.3 t ha⁻¹ on Nitisols and Vertisols, respectively. Soil physical and chemical properties were measured on samples collected from internal and external parts of mounds and adjacent soils at 0.5, 1 and 10 m away from mounds. In general, termite mounds were enriched in plant nutrients and SOC on Vertisols but not on Nitisols. Termite mounds constituted only 0.3 to 1.3% of the 0–15 cm SOM stock on a per ha basis but nevertheless the immediate vicinity of termite mounds was a relative fertile hotspot. Hence, under the studied condition, we suggest spatial arrangement of crop around termite mounds according to soil fertility gradient and spatially differentiated nutrient management strategies. Our result suggests recommendation of termite mound spreading for soil nutrient amendment has to consider plant nutrient stock in termite mounds on per ha basis besides their nutrient enrichment. Interesting topics for future investigation would be growth experiment for different crops with mound materials treatment. It would also be interesting to study the effect mound building termite on soil properties under different soil conditions, slope class and land use. Full article

This paper presents a review of the conducted research in the field of multitemporal classification methods used for the automatic identification of crops and arable land using optical satellite images. The review and systematization of these methods in terms of the effectiveness of the obtained results and their accuracy allows for the planning towards further development in this area. The state of the art analysis concerns various methodological approaches, including selection of data in terms of spatial resolution, selection of algorithms, as well as external conditions related to arable land use, especially the structure of crops. The results achieved with use of various approaches and classifiers and subsequently reported in the literature vary depending on the crops and area of analysis and the sources of satellite data. Hence, their review and systematic conclusions are needed, especially in the context of the growing interest in automatic processes of identifying crops for statistical purposes or monitoring changes in arable land. The results of this study show no significant difference between the accuracy achieved from different machine learning algorithms, yet on average artificial neural network classifiers have results that are better by a few percent than others. For very fragmented regions, better results were achieved using Sentinel-2, SPOT-5 rather than Landsat images, but the level of accuracy can still be improved. For areas with large plots there is no difference in the level of accuracy achieved from any HR images. Full article

Fusarium head blight, caused by a fungus, can cause quality deterioration and severe yield loss in wheat. It produces highly toxic deoxynivalenol, which is harmful to human and animal health. In order to quickly and accurately detect the severity of fusarium head blight, a method of detecting the disease using continuous wavelet analysis and particle swarm optimization support vector machines (PSO-SVM) is proposed in this paper. First, seven wavelet features for fusarium head blight detection were extracted using continuous wavelet analysis based on the hyperspectral reflectance of wheat ears. In addition, 16 traditional spectral features were selected using correlation analysis, including two continuous removal transformed spectral features, six differential spectral features, and eight vegetation indices. Finally, wavelet features and traditional spectral features were used as input features to construct fusarium head blight detection models in combination with the PSO-SVM algorithm, and the results were compared with those obtained using random forest (RF) and a back propagation neural network (BPNN). The results show that, under the same feature variables, the PSO-SVM detection method gave an overall higher accuracy than the BPNN detection method, while the overall accuracy of the RF detection model was the lowest. The overall accuracy of the RF, BPNN and PSO-SVM detection models with wavelet features was higher by 3.7%, 2.9% and 8.3% compared to the corresponding methodological models with traditional spectral features. The detection model with wavelet features combining the PSO-SVM algorithm gave the highest overall accuracies (93.5%) and kappa coefficients (0.903) in the six monitoring models. These results suggest that the PSO-SVM algorithm combined with continuous wavelet analysis can significantly improve the accuracy of fusarium head blight detection on the wheat ears scale. Full article

Accurate fruit segmentation in images is the prerequisite and key step for precision agriculture. In this article, aiming at the segmentation of grape cluster with different varieties, 3 state-of-the-art semantic segmentation networks, i.e., Fully Convolutional Network (FCN), U-Net, and DeepLabv3+ applied on six different datasets were studied. We investigated: (1) the segmentation performance difference of the 3 studied networks; (2) The impact of different input representations on segmentation performance; (3) The effect of image enhancement method to improve the poor illumination of images and further improve the segmentation performance; (4) The impact of the distance between grape clusters and camera on segmentation performance. The experiment results show that compared with FCN and U-Net the DeepLabv3+ combined with transfer learning is more suitable for the task with an intersection over union (IoU) of 84.26%. Five different input representations, namely RGB, HSV, L*a*b, HHH, and YCrCb obtained different IoU, ranging from 81.5% to 88.44%. Among them, the L*a*b got the highest IoU. Besides, the adopted Histogram Equalization (HE) image enhancement method could improve the model’s robustness against poor illumination conditions. Through the HE preprocessing, the IoU of the enhanced dataset increased by 3.88%, from 84.26% to 88.14%. The distance between the target and camera also affects the segmentation performance, no matter in which dataset, the closer the distance, the better the segmentation performance was. In a word, the conclusion of this research provides some meaningful suggestions for the study of grape or other fruit segmentation. Full article

This study evaluated productivity dynamics and identified sources of productivity growth in Italian tomato production and processing. We used a stochastic frontier input distance function with four error components—heterogeneity, statistical noise, persistent and transient inefficiency—and a four-step estimation procedure with a system generalized method of moments (GMM) estimator in the first step to address the endogeneity problem. The results reveal significant differences in the productivity and efficiency of tomato production and processing. Moreover, there are considerable differences among the different sizes of tomato producers, with the main variations observed for scale efficiency. While tomato processors operate at an optimal production size, tomato producers are characterized by considerable economies of scale, especially small producers. These results thus suggest that there is significant opportunity for technical efficiency improvements at both stages of the value chain. Finally, due to improvements made to scale efficiency, extensive productivity growth was observed for the group of small tomato producers. Full article

Global warming has led to increases in the frequency and intensity of typhoons. In recent years, super typhoons have had a greater impact on agriculture in the black soil farmland of Northeast China, posing serious threats to crop growth. Planting trees as windbreaks and to reduce erosion is common in this region, but their protective effects against crop damage from typhoons is still unknown. This paper studied the protective effect of different shelterbelt structures on crops that encountered a super typhoon. The results show that the distance between shelterbelt rows and shelterbelt porosity have significant influences on the starting lodging distance of crops behind the shelterbelt. Increasing the shelterbelt distance between shelterbelt rows or reducing shelterbelt porosity can enhance their protective effects on crops. Among the main crops, rice has the strongest lodging resistance, followed by soybeans, with maize being the least resistant. The protective effect of mixed tree and shrub shelterbelts is better than that of single tree species shelterbelts. Dead or missing trees reduce the shelterbelt protective effect. These results provide strategies for reducing the impact of more intense and frequent super typhoons. Full article