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

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  • Swaminathan, Bhuvaneswari
  • Vairavasundaram, Subramaniyaswamy

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.

Suggested Citation

  • Swaminathan, Bhuvaneswari & Vairavasundaram, Subramaniyaswamy, 2024. "D2CNN: Double-staged deep CNN for stress identification and classification in cropping system," Agricultural Systems, Elsevier, vol. 216(C).
    • Handle: RePEc:eee:agisys:v:216:y:2024:i:c:s0308521x24000362
    DOI: 10.1016/j.agsy.2024.103886
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    1. Wang, Hui & Mongiano, Gabriele & Fanchini, Davide & Titone, Patrizia & Tamborini, Luigi & Bregaglio, Simone, 2021. "Varietal susceptibility overcomes climate change effects on the future trends of rice blast disease in Northern Italy," Agricultural Systems, Elsevier, vol. 193(C).
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