RiceBioS: Identification of Biotic Stress in Rice Crops Using Edge-as-a-Service

The identification of biotic stress of rice crops using handheld sensing devices is a challenge, as computationally intensive machine learning models are difficult to be executed in these devices. This challenge is exacerbated in farmers’ fields located in remote regions with limited internet connectivity. Thus, an individualiased plant-specific solution to detect biotic stress due to crop infections is required in farms adopting digital agricultural practices. The existing biotic stress detection solutions are deficient in their ability to make decisions in real-time. It is required to have a system that is capable of making decisions at the edge in handheld devices having limited computational capability. This paper proposes RiceBioS, an AI-based deep learning-enabled handheld device for identifying biotic stress in rice crops using the computational capabilities of handheld devices. RiceBioS adopts Edge-as-a-Service (EaaS) as an approach for classifying rice crop images into two categories – healthy and stressed. The biotic stress condition is further diagnosed into two types of infections, fungal (rice blast) and bacterial (bacterial leaf blight of rice) by pruning the shrunk deep learning classification model and incorporating an automated RoI detection and feature extraction workflow, which makes use of adaptive thresholding and hierarchial masking techniques to perform dimensionality reduction. While RiceBioS demonstrates a test accuracy of 93.25%, it exhibits a negligible tradeoff on a smartphone after deployment. This cutting edge solution helps the farmers make informed decisions based on real-time insights provided by the user-friendly mobile application interface of RiceBioS.

I. Introduction

The factors which directly or indirectly affect the productivity of crops are climatic conditions, temperature change, soil nutrient condition, water sufficiency, pests and diseases. One third of the total affected crops are due to biotic stress crop infections [1]. The untimely pest attacks and inaccurate crop insights that farmers receive lead to wrong agricultural inputs resulting in biotic stress in crops as depicted in Fig. 1. This establishes the fact that when biotic stress leads to crop infections is a problem that needs to be addressed. The stress undergone by rice crops during every calendar year not only hits the production globally at the macro level but majorly affects the life of a farmer at the micro level. The relevance of this research can directly be correlated with the impact that rice crop yield and its productivity has on human population (on the demand side) and on the farmer community (on the supply side). Fig. 1.

Challenges in identification of biotic stress in rice crops.