Advances in the Cultivation and Production of Leguminous Plants

A special issue of Agriculture (ISSN 2077-0472). This special issue belongs to the section "Crop Production".

Deadline for manuscript submissions: 25 July 2024 | Viewed by 996

Special Issue Editors


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Guest Editor
Institute of Agroecology and Plant Production, Wrocław University of Environmental and Life Sciences, Grunwaldzki Sq. 24 A, 50-363 Wrocław, Poland
Interests: protein crops; oilseed crops; innovative and modern cultivation; crop quality; biostimulants in agricultural production

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Guest Editor
Department of Crop Production, College of Natural Sciences, Poland University of Rzeszow, Rzeszów, Poland
Interests: legumes; sustainable agriculture; abiotic stress; plant physiology; plant fertilization; plant product quality
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Special Issue Information

Dear Colleagues,

Leguminous plants are a crucial source of food and feed protein globally. However, recent climate changes, including droughts, floods, and storms, have frequently led to reduced yields and productivity of these plants. In the future, this may pose local or even global threats of shortages in high-protein food and feed. Additionally, the adverse impact of prevalent weeds, diseases, and pests may further increase the risk of low yields and deteriorating seed and/or vegetative (green) mass quality in leguminous plants. Efforts to mitigate cultivation risks can be made through breeding and selection of more resistant/tolerant varieties that thrive and yield better in less favourable environmental conditions, seed inoculation with symbiotic bacteria, optimization of water and nutrient utilization by plants, modern agricultural techniques, and the use of innovative yield-enhancing agents. Attention must also be paid to the quality of the harvested yield, both in terms of nutritional value and safety for industrial processing (non-nutritive components). Progress in the cultivation and production of legumes is essential for ensuring food and feed security in many regions of the world. It stands as one of the most significant challenges facing contemporary global agriculture. This Special Issue aims to showcase advancements in agrotechnology and the comprehensive production of leguminous plants, resulting in increased yield size and quality. It addresses challenges related to the adaptation of these plants to changing climate conditions and underscores the importance of leguminous plants in sustainable agriculture, including their role as nitrogen factories (biological fixation of atmospheric N).

Prof. Dr. Marcin Kozak
Prof. Dr. Ewa Szpunar-Krok
Guest Editors

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 submissions that pass pre-check are 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. Agriculture 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 2600 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

  • legumes in agroecosystems
  • minor leguminous plants
  • innovative cultivation
  • seeds and green matter production
  • yield quality
  • biological progress
  • plant protection
  • yield-stimulating products
  • sustainable intensification
  • adaptation to changing climate conditions

Published Papers (1 paper)

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Research

18 pages, 4497 KiB  
Article
Research on Factors Affecting Global Grain Legume Yield Based on Explainable Artificial Intelligence
by Yadong Li, Rujia Li, Rongbiao Ji, Yehui Wu, Jiaojiao Chen, Mengyao Wu and Jianping Yang
Agriculture 2024, 14(3), 438; https://doi.org/10.3390/agriculture14030438 - 07 Mar 2024
Viewed by 733
Abstract
Grain legumes play a significant global role and are integral to agriculture and food production worldwide. Therefore, comprehending and analyzing the factors that influence grain legume yield are of paramount importance for guiding agricultural management and decision making. Traditional statistical analysis methods present [...] Read more.
Grain legumes play a significant global role and are integral to agriculture and food production worldwide. Therefore, comprehending and analyzing the factors that influence grain legume yield are of paramount importance for guiding agricultural management and decision making. Traditional statistical analysis methods present limitations in interpreting results, but explainable artificial intelligence (AI) provides a visual representation of model results, offering insights into the key factors affecting grain legume yield. In this study, nine typical grain legume species were selected from a published global experimental dataset: garden pea (Pisum sativum), chickpea (Cicer arietinum), cowpea (Vigna unguiculata), garden vetch (Vicia sativa), faba bean (Vicia faba), lentil (Lens culinaris), pigeon pea (Cajanus cajan), peanut (Arachis hypogaea), and white lupine (Lupinus albus). Seven commonly used models were constructed for each legume species, and model performance evaluation was conducted using accuracy, AUC, recall, precision, and F1 score metrics. The best classification model was selected for each grain legume species. Employing Decision Tree analysis, Feature Importance Evaluation, and SHapley Additive exPlanations (SHAP) as explainable techniques, our study conducted both individual and comprehensive analyses of nine leguminous crops. This approach offers a novel perspective, unveiling not only the unique responses of each crop to the influencing factors but also demonstrating the common factors across different crops. According to the experimental results, XGboost (XGB) and Random Forests (RF) are the best-performing models among the nine types of grain legumes, and the classification accuracy of a specific species is as high as 87.33%. Insights drawn from the feature importance map reveal that several factors, including aerial biomass, precipitation, sunshine duration, soil conditions, growth cycle, and fertilization strategy, have a pivotal influence. However, it was found from the SHAP graph that the responses of various crops to these factors are not the same. This research furnishes novel perspectives and insights into understanding the factors influencing grain legume yields. The findings provide a robust scientific foundation for agricultural managers, experts, and policymakers in the pursuit of optimizing pulse yields and advancing agricultural sustainability. Full article
(This article belongs to the Special Issue Advances in the Cultivation and Production of Leguminous Plants)
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