Agro-Technological Systems in Traditional Agriculture Assistance: A Systematic Review

Montalvo-Romero, Nayeli; Montiel-Rosales, Aarón; Purroy-Vásquez, Rubén; Quechulpa-Pérez, Pompeyo

doi:10.1109/access.2023.3329087

Cited by 3 publications

(1 citation statement)

References 167 publications

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“…The systematic review by Montalvo-Romero et al [33] on agro-technological systems and Paz Silva et al's [34] development of a soil moisture monitoring system based on metamaterial-inspired sensors highlight the diverse approaches being pursued in the sector. From comprehensive reviews to specific technological innovations, the field is witnessing a significant expansion in both scope and depth.…”

Section: In-depth Review Of Models Used For Multimodal Analysis Of Cr...mentioning

confidence: 99%

PAMICRM: Improving Precision Agriculture Through Multimodal Image Analysis for Crop Water Requirement Estimation Using Multidomain Remote Sensing Data Samples

Munaganuri,

Rao

2024

IEEE Access

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The growing necessity for sustainable agriculture in the face of escalating global food demands and climate change underscores the importance of optimizing crop water usage. Current methodologies for estimating crop water requirements, primarily relying on traditional remote sensing and empirical models, face limitations in precision, adaptability to diverse crop types, and dynamic environmental conditions. This paper introduces an innovative machine learning model designed to accurately estimate crop water requirements and optimize irrigation scheduling using remote sensing data samples. The model's robustness stems from its sophisticated pre-processing technique, employing a Grey Wolf Optimized (GWO)-based Non-Local Means (NLM) algorithm for denoising images sourced from various remote sensing technologies. Subsequently, these refined images undergo a transformation into multidomain features through the integration of a Vision Transformer, Fourier, Entropy, Color Map, and Gabor Maps. This multi-faceted approach ensures a comprehensive analysis of the data, capturing intricate details pertinent to crop water requirements.A key innovation in our model is the implementation of the Dual Elephant Herding Optimization (DEHO) Process. This optimizer adeptly selects features by minimizing intra-class differences and maximizing interclass variance, thereby enhancing the model's discriminative capabilities. The selected features are then classified into distinct irrigation schedule classes using a Deep Dyna Q Graph Convolutional Network (DDQGCN). This network not only augments the efficiency of classifying images from diverse sources but also bolsters the model's capability to adapt to varying crop types and environmental conditions. The efficacy of the proposed model is further augmented by incorporating vector autoregressive moving average with eXogenous inputs (VARMAx) algorithms. This addition enables the conversion of output into temporal features, facilitating precise predictions of soil quality and the dynamic adjustment of irrigation schedules. Empirical testing of this model across different geographies on mango, rice, and cotton crops demonstrated significant improvements over existing methods. The model exhibited an 8.5% increase in precision, 8.3% in accuracy, 4.9% in recall, 5.5% in Area Under the Curve (AUC), and 4.5% in specificity, alongside a 3.5% reduction in response delays. Particularly noteworthy is the model's enhanced pre-emption capabilities, reflected in a 2.9% higher precision of pre-emption, 2.5% greater accuracy, 1.5% increased recall, 2.4% higher AUC of pre-emption, 1.5% improved specificity, and a 1.9% reduction in delay compared to existing methodologies.

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Section: In-depth Review Of Models Used For Multimodal Analysis Of Cr...mentioning

confidence: 99%

PAMICRM: Improving Precision Agriculture Through Multimodal Image Analysis for Crop Water Requirement Estimation Using Multidomain Remote Sensing Data Samples

Munaganuri,

Rao

2024

IEEE Access

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Simulating the Effects of Land Use Regulations on Agricultural Land Values

Rawat,

Ramachandran,

Gupta

et al. 2024

Mathematical Modeling in Agriculture

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Agro-Technological Systems in Traditional Agriculture Assistance: A Systematic Review

Montalvo-Romero,

Montiel-Rosales,

Purroy-Vásquez

et al. 2023

IEEE Access

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Guaranteeing food security from agriculture in an uncertain context, derived from the effects of multiple factors, is a challenge. Traditional agricultural production is the one that faces the greatest challenges, derived from the scarce evolution in agricultural practices, despite being the one that contributes the most to the availability of food, at 80%. This systematic review aims to identify and analyze agrotechnological systems belonging to precision agriculture, which may be potentially adaptable to traditional rural agriculture. Contributions that improved crop yields from scientific and technological studies were analyzed. The PRISMA statement was used as a formal outline to collect and analyze 114 studies from the period 2018-2023. From the review, it was identified that there is a growing trend in the adoption of intelligent systems that help producers in the management of crops, accentuated in the increase of crop yield, in the determination of product quality, and in the management of water resources, mainly. Likewise, it was identified that the preponderant approach is the monitoring and control of crop development. This is achieved through emerging technologies, such as the Internet of Things, artificial intelligence, and machine learning, with information mainly collected by sensors embedded in drones, algorithms, decision support systems, sensors, and Arduino technology systems. Finally, this review shows that there are five viable systems that can be adapted to traditional agriculture to strengthen agricultural production. Therefore, the adoption of scientific-technological contributions from precision agriculture contributes to ensuring food security.INDEX TERMS Agricultural applications, food security, precision agriculture.

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Agro-Technological Systems in Traditional Agriculture Assistance: A Systematic Review

Cited by 3 publications

References 167 publications

PAMICRM: Improving Precision Agriculture Through Multimodal Image Analysis for Crop Water Requirement Estimation Using Multidomain Remote Sensing Data Samples

PAMICRM: Improving Precision Agriculture Through Multimodal Image Analysis for Crop Water Requirement Estimation Using Multidomain Remote Sensing Data Samples

Simulating the Effects of Land Use Regulations on Agricultural Land Values

Agro-Technological Systems in Traditional Agriculture Assistance: A Systematic Review

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