ABSTRACT
Abiotic stress is a key threat to food security. Proximal and remote sensors are being used globally to identify abiotic stress in crops. The outputs of these sensors are multi and hyperspectral data where the latter measure the spectral changes in the agricultural crop conditions more accurately. The first part of this paper will give a brief review about abiotic stress, various stress sensing techniques with their advantages and disadvantages and the importance of hyperspectral data in stress studies. The second part will describe thermal, fluorescence and reflectance sensing techniques, which are used for water and nutrient stress identification. This paper emphasizes the reflectance techniques. Finally the use of frontier technologies like artificial intelligence (AI) and machine learning for crop stress detection will be discussed.
