Special Issue "Selected Papers from the 1st International Electronic Conference on Agronomy (IECAG2021)"

A special issue of Agronomy (ISSN 2073-4395).

Deadline for manuscript submissions: 25 March 2022.

Special Issue Editor

Prof. Dr. Youssef Rouphael
E-Mail Website
Guest Editor
Department of Agricultural Sciences, University of Naples Federico II, 80055 Portici, Italy
Interests: greenhouse crops; vegetables production; hydroponics and aquaponics; plant nutrition; microgreens; sprouts; edible flowers; functional foods, grafting; microbial and non-microbial biostimulants; biofortification; vegetable quality related to preharvest factors; LED; urban agriculture; organic farming
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear colleagues,

Welcome to the 1st International Electronic Conference in Agronomy: A Global Perspective on 21st Century Agronomy: Research Opportunities and Challenges Ahead (https://sciforum.net/conference/IECAG2021), to be held from 3-17 May 2021. We are looking forward to seeing you at our event. The Special Issue will publish selected papers from the Proceedings volume associated with our event on sciforum.net, an online platform for hosting scholarly e-conferences and discussion groups.

Through 1st Electronic Conference in Agronomy, we aim to promote and advance the exciting and rapidly changing field of agronomy. Topics of interest include, but are not limited to, the following:

  • S1. Crop Breeding and Genetics
  • S2. Soil and Nutrition section
  • S3. Horticultural and Floricultural Crops
  • S4. Grassland and Pasture Science
  • S5. Weed Science and Weed Management
  • S6. Farming Sustainability
  • S7. Precision and Digital Agriculture

Prof. Dr. Youssef Rouphael
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agronomy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • food quality and safety
  • post-harvest technology
  • environmental impact on agriculture
  • renewable agricultural resources' reutilization
  • biofortification
  • biostimulants
  • vegetable grafting
  • plant stress
  • circular economy
  • hydroponics
  • sustainable agriculture
  • plant genomics
  • biochar
  • nitrogen management
  • food and agribusiness supply chains

Published Papers (6 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Jump to: Review

Article
Effect of Differently Matured Composts from Willow on Growth and Development of Lettuce
Agronomy 2022, 12(1), 175; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy12010175 - 11 Jan 2022
Viewed by 131
Abstract
Soil amendments from peats, brown coals and composts produced from segregated biodegradable waste or biomass from fallow land can increase soil fertility and improve soil productivity. The aim of the study was to determine the possibility of using willow (Salix viminalis L.) [...] Read more.
Soil amendments from peats, brown coals and composts produced from segregated biodegradable waste or biomass from fallow land can increase soil fertility and improve soil productivity. The aim of the study was to determine the possibility of using willow (Salix viminalis L.) biomass composts as a substrate component in horticulture. The objects of the research were composts produced from willow carried out in a pile under aerobic conditions. The addition of hay and mineral nitrogen (Nmin) was used to improve process efficiency. In order to verify the type and determine fertilizing value, basic chemical parameters were analyzed (pH, total contents of C, N and P) and a pot experiment was established to analyze the germination and growth of lettuce (Lactuca sativa L.). Changes in pH, an increase in total nitrogen content (TN), phosphorus (TP) and a decrease in TOC was observed in the investigated samples. Results of the experiment showed that the highest yield was obtained from the pots with the mixture of willow, hay and Nmin. Matured composts significantly stimulated the germination and growth of the test plants. It can be concluded that the addition of hay and Nmin significantly improved composting process and increased the fertilizing value of the investigated composts. Full article
Show Figures

Figure 1

Article
Spatial Prediction of Agrochemical Properties on the Scale of a Single Field Using Machine Learning Methods Based on Remote Sensing Data
Agronomy 2021, 11(11), 2266; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy11112266 - 09 Nov 2021
Cited by 1 | Viewed by 524
Abstract
Creating accurate digital maps of the agrochemical properties of soils on a field scale with a limited data set is a problem that slows down the introduction of precision farming. The use of machine learning methods based on the use of direct and [...] Read more.
Creating accurate digital maps of the agrochemical properties of soils on a field scale with a limited data set is a problem that slows down the introduction of precision farming. The use of machine learning methods based on the use of direct and indirect predictors of spatial changes in the agrochemical properties of soils is promising. Spectral indicators of open soil based on remote sensing data, as well as soil properties, were used to create digital maps of available forms of nitrogen, phosphorus, and potassium. It was shown that machine learning methods based on support vectors (SVMr) and random forest (RF) using spectral reflectance data are similarly accurate at spatial prediction. An acceptable prediction was obtained for available nitrogen and available potassium; the variability of available phosphorus was modeled less accurately. The coefficient of determination (R2) of the best model for nitrogen is R2SVMr = 0.90 (Landsat 8 OLI) and R2SVMr = 0.79 (Sentinel 2), for potassium—R2SVMr = 0.82 (Landsat 8 OLI) and R2SVMr = 0.77 (Sentinel 2), for phosphorus—R2SVMr = 0.68 (Landsat 8 OLI), R2SVMr = 0.64 (Sentinel 2). The models based on remote sensing data were refined when soil organic matter (SOC) and fractions of texture (Silt, Clay) were included as predictors. The SVMr models were the most accurate. For Landsat 8 OLI, the SVMr model has a R2 value: nitrogen—R2 = 0.95, potassium—R2 = 0.89 and phosphorus—R2 = 0.65. Based on Sentinel 2, nitrogen—R2 = 0.92, potassium—R2 = 0.88, phosphorus—R2 = 0.72. The spatial prediction of nitrogen content is influenced by SOC, potassium—by SOC and texture, phosphorus—by texture. The validation of the final models was carried out on an independent sample on soils from a chernozem zone. For nitrogen based on Landsat 8 OLI R2 = 0.88, for potassium R2 = 0.65, and for phosphorus R2 = 0.31. Based on Sentinel 2, for nitrogen R2 = 0.85, for potassium R2 = 0.62, and for phosphorus R2 = 0.71. The inclusion of SOC and texture in remote sensing-based machine learning models makes it possible to improve the spatial prediction of nitrogen, phosphorus and potassium availability of soils in chernozem zones and can potentially be widely used to create digital agrochemical maps on the scale of a single field. Full article
Show Figures

Figure 1

Article
Mitigation of High-Temperature Damage by Application of Kaolin and Pinolene on Young Olive Trees (Olea europaea L.): A Preliminary Experiment to Assess Biometric, Eco-Physiological and Nutraceutical Parameters
Agronomy 2021, 11(9), 1884; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy11091884 - 20 Sep 2021
Cited by 1 | Viewed by 637
Abstract
Various products are used to mitigate the negative effects of abiotic stress in olive trees. The aim of the research was to examine an anti-transpirant product (Vapor Gard®, V) and a kaolin- based product (Manisol, K) effect on the growth of [...] Read more.
Various products are used to mitigate the negative effects of abiotic stress in olive trees. The aim of the research was to examine an anti-transpirant product (Vapor Gard®, V) and a kaolin- based product (Manisol, K) effect on the growth of two-year-old olive tree seedlings under high temperature. The study was conducted in a greenhouse on trees of a native cultivar of Campania (cv. Salella) grown in pot during the growing season from May to September 2020. The experimental design included two products: di-1-p-menthene (product V) and kaolin (product K), applied five times at 20 day intervals compared with a control. The following biometric, physiological, and nutraceutical parameters were evaluated: stomatal conductance, chlorophyll a fluorescence, Soil Plant Analysis Development (SPAD) index, relative water content (RWC), shoots growth, total leaf area per plant, trunk cross-sectional area, dry matter partitioning, total polyphenols, and antioxidant activity. The results obtained showed that the application of di-1-p-menthene (V) was able to induce a significant improvement of shoots growth (+37.22%) and trunk cross-sectional area (+46.60%) and a reduction of the stomatal conductance and an increase of leaf RWC values. Application with kaolin had positive effects on the total polyphenol content, with an increase over the control of 240.33% and higher antioxidant activity values. Further studies are necessary to determine the effect of these products on the biometric, physiological and nutraceutical parameters of mature olive trees cultivated in open field conditions. Full article
Show Figures

Figure 1

Article
Effect of Shungite Application on the Temperature Sensitivity of Allium cepa Respiration under Two Soil Water Regimes
Agronomy 2021, 11(7), 1302; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy11071302 - 26 Jun 2021
Viewed by 533
Abstract
For agricultural soils with low natural fertility, the possibility of using rock powders as an alternative source of nutrients and/or improver of soil physical parameters is under discussion and study. Shungite rocks, carbon-bearing volcanic sedimentary rock, are characterized by a high content of [...] Read more.
For agricultural soils with low natural fertility, the possibility of using rock powders as an alternative source of nutrients and/or improver of soil physical parameters is under discussion and study. Shungite rocks, carbon-bearing volcanic sedimentary rock, are characterized by a high content of carbon and nutrients. This study aimed to evaluate whether shungite application to Umbric Podzols may affect leaf and root mitochondrial respiratory pathways, and the leaf response to temperature change. A pot culture experiment was conducted with Allium cepa L. seedlings, using soil shungite concentrations of 0, 5, 10, and 20 g kg−1 and two soil water regimes: well-watered (WW) and drying-wetting (DW) cycles. Soil water deficit increased total respiration (Vt) of onion leaves, but not roots, under low (13 °C) and high (33 °C) measurement temperature. Shungite application affected leaf Vt only at 13 °C: it increased the Vt rate under WW and decreased one under DW. An increase in the measurement temperature to 33 °C enhanced the sensitivity of leaf respiration to the inhibitor of the alternative respiratory pathway (salicylhydroxamic acid, SHAM). Shungite application increased the contribution of SHAM-sensitive pathway to the leaf Vt rate under WW, but not under the DW regime, regardless of the leaf temperature. In contrast to the SHAM-resistant pathway, the temperature sensitivity of the SHAM-sensitive rate decreased following the decrease in soil water availability. Shungite application increased the temperature sensitivity of both SHAM-sensitive and SHAM-resistant pathways under DW, and significantly decreased these parameters under WW. In summary, the decrease in temperature sensitivity of alternative SHAM-sensitive respiratory pathway with a decrease of soil water availability or shungite-related decrease of both SHAM-sensitive and SHAM-resistant leaf respiration may play an important role in enhancing the resistance of plant respiration to stress temperature. Full article
Show Figures

Figure 1

Article
Durum Wheat Yield and N Uptake as Affected by N Source, Timing, and Rate in Two Mediterranean Environments
Agronomy 2021, 11(7), 1299; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy11071299 - 26 Jun 2021
Cited by 3 | Viewed by 478
Abstract
In nitrate vulnerable zones (NVZs), site-specific techniques are needed to match N availability with durum wheat (Triticum turgidum subsp. durum Desf.) requirements. Enhanced-efficiency fertilizers can improve efficient N supply and reduce leaching, contributing to sustainable agriculture. Two-year field experiments were carried out [...] Read more.
In nitrate vulnerable zones (NVZs), site-specific techniques are needed to match N availability with durum wheat (Triticum turgidum subsp. durum Desf.) requirements. Enhanced-efficiency fertilizers can improve efficient N supply and reduce leaching, contributing to sustainable agriculture. Two-year field experiments were carried out at two Mediterranean nitrate vulnerable zones in Central Italy (Pisa and Arezzo) to study the effects of nitrogen sources, timings, and application rates. The trial compared: (i) three N sources for the first topdressing application (urea, methylene urea, and urea with the nitrification inhibitor DMPP); (ii) two stages for the first topdressing N application (1st tiller visible—BBCH21 and 1st node detectable—BBCH31); (iii) two N rates: one based on the crop N requirements (Optimal—NO), the other based on action programme prescriptions of the two NVZs (Action Programme—NAP). Grain yield and yield components were determined, together with N uptake. The results showed that: (i) grain and biomass production were reduced with NAP at both locations; (ii) urea performed better than slow-release fertilizers; (iii) the best application time depended on the N source and location: in Pisa, enhanced-efficiency fertilizers achieved higher yields when applied earliest, while for urea the opposite was true; in Arezzo different N fertilizers showed similar performances between the two application timings. Different behaviors of topdressing fertilizers at the two localities could be related to the diverse patterns of temperatures and rainfall. Thus, optimal fertilization strategies would seem to vary according to environmental conditions. Full article
Show Figures

Figure 1

Review

Jump to: Research

Review
VISmaF: Synthetic Tree for Immersive Virtual Visualization in Smart Farming. Part I: Scientific Background Review and Model Proposal
Agronomy 2021, 11(12), 2458; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy11122458 - 02 Dec 2021
Viewed by 452
Abstract
Computer-Generated Imagery (CGI) has received increasing interest in both research and the entertainment industry. Recent advancements in computer graphics allowed researchers and companies to create large-scale virtual environments with growing resolution and complexity. Among the different applications, the generation of biological assets is [...] Read more.
Computer-Generated Imagery (CGI) has received increasing interest in both research and the entertainment industry. Recent advancements in computer graphics allowed researchers and companies to create large-scale virtual environments with growing resolution and complexity. Among the different applications, the generation of biological assets is a relevant task that implies challenges due to the extreme complexity associated with natural structures. An example is represented by trees, whose composition made by thousands of leaves, branches, branchlets, and stems with oriented directions is hard to be modeled. Realistic 3D models of trees can be exploited for a wide range of applications including decision-making support, visualization of ecosystem changes over time, and for simple visualization purposes. In this review, we give an overview of the most common approaches used to generate 3D tree models, discussing both methodologies and available commercial software. We focus on strategies for modeling and rendering of plants, highlighting their accordance or not with botanical knowledge and biological models. We also present a proof of concept to link biological models and 3D rendering engines through Ordinary Differential Equations. Full article
Show Figures

Figure 1

Back to TopTop