D2CNN: Double-staged deep CNN for stress identification and classification in cropping system

Bhuvaneswari Swaminathan and Subramaniyaswamy Vairavasundaram

Agricultural Systems, 2024, vol. 216, issue C

Abstract: Paddy crop stress can significantly reduce the quality and quantity of agricultural goods and severely affect food production safety. Untimely stress and inaccurate crop insights lead to farmers applying the wrong agricultural inputs resulting in resource wastage. It is estimated that one-third of crop damage occurs due to biotic stress, caused by any living being, and abiotic stress, caused by environmental factors. In severe cases, crop stresses can lead to no grain harvest. Therefore, the automatic detection and diagnosis of paddy crop stress is widely desired for sustainable agriculture.

Keywords: Paddy leaf stress; Stage-wise model; Deep convolutional neural network; Image recognition; Whale optimization technique (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:agisys:v:216:y:2024:i:c:s0308521x24000362

DOI: 10.1016/j.agsy.2024.103886

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