Avinash Agarwal

Robot-based 3D-multispectral monitoring of soybean in a spatially heterogenous agrivoltaic environment

The paper uses a robot-mounted 3D-multispectral imaging system to monitor soybean growth and spectral reflectance in an agrivoltaic environment, revealing growth variations and stress symptoms in different genotypes.

Synergistic 3D, multispectral, and thermal image analysis via supervised machine learning for improved detection of root rot symptoms in hydroponically-grown flat-leaf parsley

This study uses supervised machine learning to combine 3D, multispectral, and thermal imaging data for improved detection of root rot in hydroponic parsley.

Infrared thermography for plant stress detection in vertical farms: Investigating spatiotemporal variations and exploring solutions via machine learning

This study uses infrared thermography and machine learning to detect plant stress in vertical farms, finding that binary models trained on medial stress levels provide reliable probabilistic stress estimates despite spatiotemporal variations.

Two-fold Red Excess (TREx): A simple and novel digital color index that enables non-invasive real-time health assessment of green-leaved as well as anthocyanin-rich crops

This paper develops a new digital color index, TREx, to assess plant health in both green-leaved and anthocyanin-rich crops using RGB data, showing strong correlation with chlorophyll measurements.

Assessing nutritional pigment content and plant health status of green and red leafy vegetables by image analysis: Catching the 'red herring' of plant digital color processing

This study develops digital color analysis models to accurately assess pigment content and plant health in green and red leafy vegetables, showing that certain color features correlate strongly with chlorophyll and anthocyanin levels.