Land suitability evaluation for irrigating wheat by Geopedological approach and Geographic Information System: A case study of Qazvin plain, Iran

Mousavi, Sayed Roholla; Sarmadian, Fereydoon; Alijani, Zohreh; Taati, Abass

doi:10.18393/ejss.297251

Cited by 7 publications

(4 citation statements)

References 11 publications

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“…Researchers can refer to Sys et al. (1991) ; Mousavi et al. (2017) , and Taghizadeh-Mehrjardi et al.…”

Section: Methodsmentioning

confidence: 99%

“…The FAO-agro-climatic model is a widely used approach that incorporates genetic potential plant and climate data, including radiation, temperature, and land potential, to determine the expected production. Researchers can refer to Sys et al (1991); Mousavi et al (2017), and Taghizadeh-Mehrjardi et al (2020) for a more comprehensive understanding of the calculation process involved in determining the potential yield of irrigated wheat using the FAO model. Furthermore, for quantifying the yield gap the relation proposed by Fischer et al (2014) yield gaps was applied and the value is expressed as a percentage of actual and potential yield as (Equation 5):…”

Section: Attainable Potential Of Wheat and Yield Gapmentioning

confidence: 99%

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Spatial prediction of winter wheat yield gap: agro-climatic model and machine learning approaches

Mousavi,

Jahandideh Mahjenabadi,

Khoshru

et al. 2024

Front. Plant Sci.

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This study aimed to identify the most influential soil and environmental factors for predicting wheat yield (WY) in a part of irrigated croplands in southwest Iran, using the FAO-Agro-Climate method and machine learning algorithms (MLAs). A total of 60 soil samples and wheat grain (1 m × 1 m) in 1200 ha of Pasargad plain were collected and analyzed in the laboratory. Attainable WY was assessed using the FAO method for the area. Pearson correlation analysis was used to select the best set of soil properties for modeling. Topographic attributes and vegetation indices were used as proxies of landscape components and cover crop to map actual WY in the study area. Two well-known MLAs, random forest (RF) and artificial neural networks (ANNs), were utilized to prepare an actual continuous WY map. The k-fold method was used to determine the uncertainty of WY prediction and quantify the quality of prediction accuracy. Results showed that soil organic carbon (SOC) and total nitrogen (TN) had a positive and significant correlation with WY. The SOC, TN, normalized different vegetation index (NDVI), and channel network base level (CHN) were recognized as the most important predictors and justifying more than 50% of actual WY. The ANNs outperformed the RF algorithm with an R2 of 0.75, RMSE of 400 (kg ha−1), and RPD of 2.79, according to statistical indices. The uncertainty analysis showed that the maximum uncertainty of the prediction map [400 (kg ha−1)] was very low compared to the mean value [4937 (kg ha−1)] of WY map. Calculation yield gap using the FAO-agro-climatic model showed that the average yield gap of the region was about 50% of actual yield. The findings of this study demonstrated that integrating simulated attainable crop growth using crop model and a set of soil and environmental covariates with the ANNs algorithm can effectively predict WY gaps in large areas with acceptable and reasonable accuracy. The study emphasizes that the implementation of efficient management practices has the potential to enhance agricultural production in the study area and similar regions. These results represent a significant advancement of sustainable agriculture and provide valuable insights for ensuring global food security.

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“…Researchers can refer to Sys et al. (1991) ; Mousavi et al. (2017) , and Taghizadeh-Mehrjardi et al.…”

Section: Methodsmentioning

confidence: 99%

Section: Attainable Potential Of Wheat and Yield Gapmentioning

confidence: 99%

Spatial prediction of winter wheat yield gap: agro-climatic model and machine learning approaches

Mousavi,

Jahandideh Mahjenabadi,

Khoshru

et al. 2024

Front. Plant Sci.

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Section: Attainable Potential Of Wheat and Yield Gapmentioning

confidence: 99%

Applications of Artificial Intelligence, Machine Learning, and Deep Learning in Plant Breeding

Orlov

2024

Frontiers Research Topics

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Frontiers is more than just an open access publisher of scholarly articles: it is a pioneering approach to the world of academia, radically improving the way scholarly research is managed. The grand vision of Frontiers is a world where all people have an equal opportunity to seek, share and generate knowledge. Frontiers provides immediate and permanent online open access to all its publications, but this alone is not enough to realize our grand goals. Frontiers journal seriesThe Frontiers journal series is a multi-tier and interdisciplinary set of openaccess, online journals, promising a paradigm shift from the current review, selection and dissemination processes in academic publishing. All Frontiers journals are driven by researchers for researchers; therefore, they constitute a service to the scholarly community. At the same time, the Frontiers journal series operates on a revolutionary invention, the tiered publishing system, initially addressing specific communities of scholars, and gradually climbing up to broader public understanding, thus serving the interests of the lay society, too. Dedication to qualityEach Frontiers article is a landmark of the highest quality, thanks to genuinely collaborative interactions between authors and review editors, who include some of the world's best academicians. Research must be certified by peers before entering a stream of knowledge that may eventually reach the public -and shape society; therefore, Frontiers only applies the most rigorous and unbiased reviews. Frontiers revolutionizes research publishing by freely delivering the most outstanding research, evaluated with no bias from both the academic and social point of view. By applying the most advanced information technologies, Frontiers is catapulting scholarly publishing into a new generation. What are Frontiers Research Topics?Frontiers Research Topics are very popular trademarks of the Frontiers journals series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area.

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“…El enfoque geopedológico también ha contribuido al uso y manejo sustentable de tierras mediante estudios de procesos de erosión y sedimentación, evaluación de superficies para riego y caracterización biofísica para el manejo integral de cuencas (Saint-Laurent et al, 2008;Mousavi et al, 2017;Reyna-Bowen et al, 2017). Los mapas de geoformas y suelos, y la base de datos morfométricos, físicos y químicos, aportan información valiosa para la zonificación ecológica de cultivos, reservas ecológicas, áreas de protección y mejoramiento ambiental (Zinck, 2012).…”

Section: Introductionunclassified

Formas del terreno a escala detallada en planicies aluviales y lomeríos de llanura costera tropical utilizando el enfoque geopedológico (Huimanguillo, Tabasco)

López-Castañeda¹,

Zavala-Cruz²,

Palma-López³

et al. 2022

BSGM

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El uso no sustentable de los recursos naturales ha contribuido al deterioro de los ecosistemas, a la pérdida de biodiversidad, y a la degradación de suelos en México. En Tabasco, el deterioro ambiental es evidente por la degradación química y física de suelos. En este contexto, la cartografía geomorfológica contribuye a mitigar la problemática al generar un marco geoespacial para la ordenación del territorio, y así orientar el uso y manejo de los recursos naturales. Sin embargo, esta información a nivel microrregional es escasa. El objetivo del trabajo fue generar cartografía detallada de las formas del terreno en planicies y lomeríos con uso agropecuario en el municipio de Huimanguillo, Tabasco, en una superficie de 29 398 ha. Se aplicó la primera fase del enfoque geopedológico y se generó cartografía de paisajes geomorfológicos, relieve/modelados, litología/facies y formas de terreno, mediante el análisis de atributos morfográficos y morfométricos, que se complementa con la fotointerpretación de ortofotomapas y verificación de campo. El 49 % del área de estudio corresponde al paisaje geomorfológico de planicie, contiene relieves de llanura de inundación y depresiones sobre sedimentos aluviales, prevalecen las formas del terreno albardón del río, napa de desborde y cubeta de decantación; tienen buen drenaje superficial, excepto las cubetas que se inundan seis meses. El área restante corresponde al paisaje geomorfológico de lomerío, con relieves de loma y depresión sobre sedimentos detríticos; dominan las formas de ladera, cumbre, depresión interloma y pie de vertiente. Se zonificaron nuevas formas del terreno como depresión interloma, gota de lágrima, hombro y pozo petrolero; sobresalen las depresiones en posiciones topográficas elevadas, por contener humedales inundados hasta ocho meses. El estudio aporta información que puede contribuir al ordenamiento de los usos agropecuarios y forestales, para mitigar la degradación de los recursos naturales en planicies y lomeríos tropicales.

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Land suitability evaluation for irrigating wheat by Geopedological approach and Geographic Information System: A case study of Qazvin plain, Iran

Cited by 7 publications

References 11 publications

Spatial prediction of winter wheat yield gap: agro-climatic model and machine learning approaches

Spatial prediction of winter wheat yield gap: agro-climatic model and machine learning approaches

Applications of Artificial Intelligence, Machine Learning, and Deep Learning in Plant Breeding

Formas del terreno a escala detallada en planicies aluviales y lomeríos de llanura costera tropical utilizando el enfoque geopedológico (Huimanguillo, Tabasco)

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