Abstract
Deep learning techniques, and in particular Convolutional Neural Networks (CNNs), have led to significant progress in image processing. Since 2016, many applications for the automatic identification of crop diseases have been developed. These applications could serve as a basis for the development of expertise assistance or automatic screening tools. Such tools could contribute to more sustainable agricultural practices and greater food production security. To assess the potential of these networks for such applications, we survey 19 studies that relied on CNNs to automatically identify crop diseases. We describe their profiles, their main implementation aspects and their performance. Our survey allows us to identify the major issues and shortcomings of works in this research area. We also provide guidelines to improve the use of CNNs in operational contexts as well as some directions for future research.
Highlights
Plant health and food safety are closely linked
The literature search was conducted through SCOPUS for works that matched keywords such as “deep learning,” “deep neural network,” or “convolutional neural network,” along with keywords regarding “diseases,” and “plants” or “crops.” The references of the selected articles were checked
We identified some of the major issues and shortcomings of works that used Convolutional Neural Networks (CNNs) to automatically identify crop diseases
Summary
Plant health and food safety are closely linked. The Food and Agriculture Organization of the United Nations (FAO) estimates that pests and diseases lead to the loss of 20–40% of global food production, constituting a threat to food security (Food and Agriculture Organization of the United Nation, International Plant Protection Convention, 2017). The use of such substances is not environmentally harmless Applying these substances negatively impacts biodiversity, including insect, bird, and fish populations, as well as soil, air, and water quality (Risebrough, 1986; Gill and Garg, 2014; Goulson, 2014; Sanchez-Bayo and Goka, 2014; Knillmann and Liess, 2019). Their use constitutes a risk to human health, with both acute and chronic effects (Weisenburger, 1993; Bassil et al, 2007; Kim et al, 2016). The quantity of pesticides used is increasing worldwide, with +78% of tons of active ingredients used between 1990 and 2016 (Food and Agriculture Organization of the United Nation, 2018)
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