A review on detection and differentiation of maize diseases and pests by imaging sensors

Abstract

Maize (Zea mays) is one of the most important cereal crops globally, providing food, feed, and fuel for humans and animals. However, the production of maize is frequently challenged by various stresses that can severely impact crop yield and quality. Early detection and identification are critical for implementing timely and effective control measures to reduce their impact. Therefore, it is essential to establish effective disease and pest monitoring and management strategies to ensure sustainable maize production and maintain food security. Conventional detection methods relying on visual assessments by human experts are time-consuming, labour-intensive, and subjective. The emergence of imaging sensors, computer vision technologies, and high throughput platforms has revolutionised the detection and differentiation of crop diseases, offering a non-invasive and rapid approach. In this publication, we present a review on imaging sensors for the detection and differentiation of symptoms on maize caused by diseases and pests. The main advantages and limitations of each imaging sensor, along with its applications and case studies for maize disease detection, are introduced and discussed. Recent advances in the visible, near-infrared, and hyperspectral imaging for maize disease detection are highlighted, and the importance of different sensors is discussed. The goal is to provide a comprehensive overview of the current state-of-the-art in this field, highlighting the potential of imaging sensors for improving maize production and identifying future research directions in this area.