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An Optimal Decision Support System Based on Crop Dynamic Model for N-Fertilizer Treatment
The efficient handling of nitrogen has become a critical issue in modern agriculture, from a financial standpoint, as well as in regard to reducing the environmental impacts of using an excessive amount of nitrogen fertilizer. Manure compost is useful for maintaining or raising soil chemical levels...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9570642/ https://www.ncbi.nlm.nih.gov/pubmed/36236710 http://dx.doi.org/10.3390/s22197613 |
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author | Singh, Abhaya Pal Yerudkar, Amol Liuzza, Davide Liu, Yang Glielmo, Luigi |
author_facet | Singh, Abhaya Pal Yerudkar, Amol Liuzza, Davide Liu, Yang Glielmo, Luigi |
author_sort | Singh, Abhaya Pal |
collection | PubMed |
description | The efficient handling of nitrogen has become a critical issue in modern agriculture, from a financial standpoint, as well as in regard to reducing the environmental impacts of using an excessive amount of nitrogen fertilizer. Manure compost is useful for maintaining or raising soil chemical levels without excessive [Formula: see text] accumulation; however, for the best grain yield, it should be combined with N fertilizer. Via this study, we aimed to develop an optimal decision support system that indicates when to initiate fertilization based on nitrogen-limited (N-limited) crop growth dynamics. An optimal nitrogen fertilizer (N-fertilizer) management system increases crop yield while maintaining a balance between fertilizer supply and crop demand. This study used the N-limited crop growth model (LINTUL3) to develop an optimal decision support system. In this work, we formulated and resolved two optimization challenges: (i) maximization of biomass growth; and (ii) maximization of growth with the least cost paid on N-fertilizer and its application. Furthermore, two case studies were developed based on the number of fields: (i) optimization for a single field, and (ii) optimization for multiple fields. In the case of multiple fields, it is hypothesized that a fertilizer treatment for one field can leak to other fields and affect the nitrogen dynamics of different fields. Finally, numerical simulations were carried out supporting the theory developed in the paper. The simulations showed that when the proposed work was employed to achieve the goal of optimal nitrogen management for a crop, a [Formula: see text] to [Formula: see text] increase in biomass growth under certain scenarios was attained. |
format | Online Article Text |
id | pubmed-9570642 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-95706422022-10-17 An Optimal Decision Support System Based on Crop Dynamic Model for N-Fertilizer Treatment Singh, Abhaya Pal Yerudkar, Amol Liuzza, Davide Liu, Yang Glielmo, Luigi Sensors (Basel) Article The efficient handling of nitrogen has become a critical issue in modern agriculture, from a financial standpoint, as well as in regard to reducing the environmental impacts of using an excessive amount of nitrogen fertilizer. Manure compost is useful for maintaining or raising soil chemical levels without excessive [Formula: see text] accumulation; however, for the best grain yield, it should be combined with N fertilizer. Via this study, we aimed to develop an optimal decision support system that indicates when to initiate fertilization based on nitrogen-limited (N-limited) crop growth dynamics. An optimal nitrogen fertilizer (N-fertilizer) management system increases crop yield while maintaining a balance between fertilizer supply and crop demand. This study used the N-limited crop growth model (LINTUL3) to develop an optimal decision support system. In this work, we formulated and resolved two optimization challenges: (i) maximization of biomass growth; and (ii) maximization of growth with the least cost paid on N-fertilizer and its application. Furthermore, two case studies were developed based on the number of fields: (i) optimization for a single field, and (ii) optimization for multiple fields. In the case of multiple fields, it is hypothesized that a fertilizer treatment for one field can leak to other fields and affect the nitrogen dynamics of different fields. Finally, numerical simulations were carried out supporting the theory developed in the paper. The simulations showed that when the proposed work was employed to achieve the goal of optimal nitrogen management for a crop, a [Formula: see text] to [Formula: see text] increase in biomass growth under certain scenarios was attained. MDPI 2022-10-08 /pmc/articles/PMC9570642/ /pubmed/36236710 http://dx.doi.org/10.3390/s22197613 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Singh, Abhaya Pal Yerudkar, Amol Liuzza, Davide Liu, Yang Glielmo, Luigi An Optimal Decision Support System Based on Crop Dynamic Model for N-Fertilizer Treatment |
title | An Optimal Decision Support System Based on Crop Dynamic Model for N-Fertilizer Treatment |
title_full | An Optimal Decision Support System Based on Crop Dynamic Model for N-Fertilizer Treatment |
title_fullStr | An Optimal Decision Support System Based on Crop Dynamic Model for N-Fertilizer Treatment |
title_full_unstemmed | An Optimal Decision Support System Based on Crop Dynamic Model for N-Fertilizer Treatment |
title_short | An Optimal Decision Support System Based on Crop Dynamic Model for N-Fertilizer Treatment |
title_sort | optimal decision support system based on crop dynamic model for n-fertilizer treatment |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9570642/ https://www.ncbi.nlm.nih.gov/pubmed/36236710 http://dx.doi.org/10.3390/s22197613 |
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