Exploring the Potential of Proximal Remote Sensing in Plant Stress Phenotyping: A Comprehensive Review
Teena Patel *
Department of Plant Breeding and Genetics, Jawaharlal Nehru Krishi Vishwa Vidyalaya, Jabalpur, M.P. India.
Anita Babbar
Department of Plant Breeding and Genetics, Jawaharlal Nehru Krishi Vishwa Vidyalaya, Jabalpur, M.P. India.
Karishma Behera
Department of Plant Breeding and Genetics, Jawaharlal Nehru Krishi Vishwa Vidyalaya, Jabalpur, M.P. India.
Vijay Kumar Katara
Department of Plant Breeding and Genetics, Jawaharlal Nehru Krishi Vishwa Vidyalaya, Jabalpur, M.P. India.
Kumar Jai Anand
Department of Plant Breeding and Genetics, Jawaharlal Nehru Krishi Vishwa Vidyalaya, Jabalpur, M.P. India.
R. G. Vyshnavi
Department of Plant Physiology, Jawaharlal Nehru Krishi Vishwa Vidyalaya, Jabalpur, M.P. India.
Surbhi Pachori
Department of Plant Breeding and Genetics, Jawaharlal Nehru Krishi Vishwa Vidyalaya, Jabalpur, M.P. India.
Nagesh Bichewar
Department of Genetics and Plant Breeding, Professor Jayashankar Telangana State Agricultural University, Rajendranagar, Hyderabad, India.
*Author to whom correspondence should be addressed.
Abstract
The global challenge of feeding the world demands attention due to the projected population increase to 10.9 billion by 2050. Abiotic and biotic stressors, such as heat, drought, diseases, and pests, further compound the difficulties faced in achieving sufficient agricultural output. Early detection of crop stress is vital to mitigate yield loss and find appropriate agrotechnical solutions. However, the complex interactions between abiotic and biotic stressors and their impact on plant growth and yield present challenges in plant phenotyping and breeding. This review discusses recent advances in remote sensing technologies which offer promising solutions to overcome these challenges. Low-cost, reliable sensors and technologies facilitate data collection and interpretation, paving the way for proximal sensing and high-throughput phenotyping platforms. These automated platforms, equipped with imaging devices, enable non-destructive data collection and monitoring of plant properties over time. Optical methods like hyperspectral sensors, RGB imaging, remote sensing, and chlorophyll fluorescence contribute to the early identification of plant stress causes, facilitating the development of control strategies. By providing accurate and timely information on crop stress, these technologies offer essential support in enhancing agricultural productivity and ensuring food security for a growing global population.
Keywords: Remote sensing technologies, proximal sensing, high-throughput phenotyping, imaging devices, hyperspectral sensors, agricultural productivity, food security