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

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

Deadline for manuscript submissions: closed (25 March 2022) | Viewed by 25770

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Prof. Dr. Youssef Rouphael

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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
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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

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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.

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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

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Published Papers (9 papers)

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Editorial

Jump to: Research, Review

4 pages, 199 KiB

Open AccessEditorial

Advances and Sustainable Practices for the Rapidly Changing Field of Agronomy

by Youssef Rouphael

Agronomy 2022, 12(9), 2074; https://doi.org/10.3390/agronomy12092074 - 30 Aug 2022

Cited by 2 | Viewed by 1475

Abstract

Human welfare is strictly linked to the Earth’s natural resources, which are heavily exploited, thus making food production systems unsustainable [...] Full article

(This article belongs to the Special Issue Selected Papers from the 1st International Electronic Conference on Agronomy (IECAG2021))

Research

Jump to: Editorial, Review

14 pages, 975 KiB

Open AccessArticle

Assessing the Contribution of EC_a and NDVI in the Delineation of Management Zones in a Vineyard

by Catarina Esteves, David Fangueiro, Ricardo P. Braga, Miguel Martins, Manuel Botelho and Henrique Ribeiro

Agronomy 2022, 12(6), 1331; https://doi.org/10.3390/agronomy12061331 - 31 May 2022

Cited by 9 | Viewed by 2748

Abstract

Precision fertilization implies the need to identify the variability of soil fertility, which is costly and time-consuming. Remotely measured data can be a solution. Using this strategy, a study was conducted, in a vineyard, to delineate different management zones using two indicators: apparent soil electrical conductivity (EC_a) and normalized difference vegetation index (NDVI). To understand the contribution of each indicator, three scenarios were used for zone definition: (1) using only NDVI, (2) only EC_a, or (3) using a combination of the two. Then the differences in soil fertility between these zones were assessed using simple statistical methods. The results indicate that the most beneficial strategy is the combined use of the two indicators, as it allowed the definition of three distinct zones regarding important soil variables and crop nutrients, such as soil total nitrogen, Mg²⁺ cation, exchange acidity, and effective cation exchange capacity, and some relevant cation ratios. This strategy also allowed the identification of an ionic unbalance in the soil chemistry, due to an excess of Mg²⁺, that was harming crop health, as reported by NDVI. This also impacted EC_a and NDVI relationship, which was negative in this study. Overall, the results demonstrate the advantages of using remotely sensed data, mainly more than one type of sensing data, and suggest a high potential for differential crop fertilization and soil management in the study area. Full article

(This article belongs to the Special Issue Selected Papers from the 1st International Electronic Conference on Agronomy (IECAG2021))

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18 pages, 2986 KiB

Open AccessArticle

Comparison of Proximal Remote Sensing Devices of Vegetable Crops to Determine the Role of Grafting in Plant Resistance to Meloidogyne incognita

by Yassine Hamdane, Adrian Gracia-Romero, Maria Luisa Buchaillot, Rut Sanchez-Bragado, Aida Magdalena Fullana, Francisco Javier Sorribas, José Luis Araus and Shawn C. Kefauver

Agronomy 2022, 12(5), 1098; https://doi.org/10.3390/agronomy12051098 - 30 Apr 2022

Cited by 2 | Viewed by 2716

Abstract

Proximal remote sensing devices are novel tools that enable the study of plant health status through the measurement of specific characteristics, including the color or spectrum of light reflected or transmitted by the leaves or the canopy. The aim of this study is to compare the RGB and multispectral data collected during five years (2016–2020) of four fruiting vegetables (melon, tomato, eggplant, and peppers) with trial treatments of non-grafted and grafted onto resistant rootstocks cultivated in a Meloidogyne incognita (a root-knot nematode) infested soil in a greenhouse. The proximal remote sensing of plant health status data collected was divided into three levels. Firstly, leaf level pigments were measured using two different handheld sensors (SPAD and Dualex). Secondly, canopy vigor and biomass were assessed using vegetation indices derived from RGB images and the Normalized Difference Vegetation Index (NDVI) measured with a portable spectroradiometer (Greenseeker). Third, we assessed plant level water stress, as a consequence of the root damage by nematodes, using stomatal conductance measured with a porometer and indirectly using plant temperature with an infrared thermometer, and also the stable carbon isotope composition of leaf dry matter.. It was found that the interaction between treatments and crops (ANOVA) was statistically different for only four of seventeen parameters: flavonoid (p < 0.05), NBI (p < 0.05), NDVI (p < 0.05) and the RGB CSI (Crop Senescence Index) (p < 0.05). Concerning the effect of treatments across all crops, differences existed only in two parameters, which were flavonoid (p < 0.05) and CSI (p < 0.001). Grafted plants contained fewer flavonoids (

\bar{x}

= 1.37) and showed lower CSI (

\bar{x}

= 11.65) than non-grafted plants (

\bar{x}

= 1.98 and

\bar{x}

= 17.28, respectively, p < 0.05 and p < 0.05) when combining all five years and four crops. We conclude that the grafted plants were less stressed and more protected against nematode attack. Leaf flavonoids content and the CSI index were robust indicators of root-knot nematode impacts across multiple crop types. Full article

(This article belongs to the Special Issue Selected Papers from the 1st International Electronic Conference on Agronomy (IECAG2021))

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11 pages, 23787 KiB

Open AccessArticle

Effect of Differently Matured Composts from Willow on Growth and Development of Lettuce

by Jakub Bekier, Elżbieta Jamroz, Józef Sowiński, Katarzyna Adamczewska-Sowińska and Andrea Kałuża-Haładyn

Agronomy 2022, 12(1), 175; https://doi.org/10.3390/agronomy12010175 - 11 Jan 2022

Cited by 9 | Viewed by 2644

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.) 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

(This article belongs to the Special Issue Selected Papers from the 1st International Electronic Conference on Agronomy (IECAG2021))

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16 pages, 2553 KiB

Open AccessArticle

Spatial Prediction of Agrochemical Properties on the Scale of a Single Field Using Machine Learning Methods Based on Remote Sensing Data

by Ilnas Sahabiev, Elena Smirnova and Kamil Giniyatullin

Agronomy 2021, 11(11), 2266; https://doi.org/10.3390/agronomy11112266 - 9 Nov 2021

Cited by 16 | Viewed by 2806

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 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 R²_SVMr = 0.90 (Landsat 8 OLI) and R²_SVMr = 0.79 (Sentinel 2), for potassium—R²_SVMr = 0.82 (Landsat 8 OLI) and R²_SVMr = 0.77 (Sentinel 2), for phosphorus—R²_SVMr = 0.68 (Landsat 8 OLI), R²_SVMr = 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

(This article belongs to the Special Issue Selected Papers from the 1st International Electronic Conference on Agronomy (IECAG2021))

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14 pages, 3173 KiB

Open AccessArticle

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

by Aurora Cirillo, Stefano Conti, Giulia Graziani, Christophe El-Nakhel, Youssef Rouphael, Alberto Ritieni and Claudio Di Vaio

Agronomy 2021, 11(9), 1884; https://doi.org/10.3390/agronomy11091884 - 20 Sep 2021

Cited by 10 | Viewed by 2955

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 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

(This article belongs to the Special Issue Selected Papers from the 1st International Electronic Conference on Agronomy (IECAG2021))

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10 pages, 640 KiB

Open AccessArticle

Effect of Shungite Application on the Temperature Sensitivity of Allium cepa Respiration under Two Soil Water Regimes

by Elena Ikkonen, Svetlana Chazhengina, Olga Bakhmet and Valeria Sidorova

Agronomy 2021, 11(7), 1302; https://doi.org/10.3390/agronomy11071302 - 26 Jun 2021

Viewed by 2195

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 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 (V_t) of onion leaves, but not roots, under low (13 °C) and high (33 °C) measurement temperature. Shungite application affected leaf V_t only at 13 °C: it increased the V_t 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 V_t 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

(This article belongs to the Special Issue Selected Papers from the 1st International Electronic Conference on Agronomy (IECAG2021))

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12 pages, 1000 KiB

Open AccessEditor’s ChoiceArticle

Durum Wheat Yield and N Uptake as Affected by N Source, Timing, and Rate in Two Mediterranean Environments

by Silvia Pampana and Marco Mariotti

Agronomy 2021, 11(7), 1299; https://doi.org/10.3390/agronomy11071299 - 26 Jun 2021

Cited by 18 | Viewed by 2565

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 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—N_O), the other based on action programme prescriptions of the two NVZs (Action Programme—N_AP). Grain yield and yield components were determined, together with N uptake. The results showed that: (i) grain and biomass production were reduced with N_AP 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

(This article belongs to the Special Issue Selected Papers from the 1st International Electronic Conference on Agronomy (IECAG2021))

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Review

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28 pages, 3937 KiB

Open AccessReview

VISmaF: Synthetic Tree for Immersive Virtual Visualization in Smart Farming. Part I: Scientific Background Review and Model Proposal

by Mariano Crimaldi, Fabrizio Cartenì and Francesco Giannino

Agronomy 2021, 11(12), 2458; https://doi.org/10.3390/agronomy11122458 - 2 Dec 2021

Cited by 7 | Viewed by 3737

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 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

(This article belongs to the Special Issue Selected Papers from the 1st International Electronic Conference on Agronomy (IECAG2021))

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