Machine learning approaches for estimation of the fraction of absorbed photosynthetically active radiation and net photosynthesis rate of maize using multi-spectral sensor.

The fraction of absorbed photosynthetically active radiation (FAPAR) and the photosynthesis rate (Pn) of maize canopies were identified as essential photosynthetic parameters for accurately estimating vegetation growth and productivity using multispectral vegetation indices (VIs). Despite their importance, few studies have compared the effectiveness of multispectral imagery and various machine learning techniques in estimating these photosynthetic traits under high vegetation coverage. In this study, seventeen multispectral VIs and four machine learning (ML) algorithms were utilized to determine the most suitable model for estimating maize FAPAR and Pn during the and seasons at Tamil Nadu Agricultural University, Coimbatore, India.

Genome-wide identification and expression analysis of the plant specific LIM genes in Gossypium arboreum under phytohormone, salt and pathogen stress.

Asiatic cotton (Gossypium arboreum) cultivated as 'desi cotton' in India, is renowned for its climate resilience and robustness against biotic and abiotic stresses. The genome of G. arboreum is therefore, considered as a valued reserve of information for discovering novel genes or gene functions for trait improvements in the present context of cotton cultivation world-wide.

Morpho-physiological and molecular characterization of drought tolerance traits in genotypes under drought stress.

Drought stress is one of the major abiotic stresses affecting lint yield and fibre quality in cotton. With increase in population, degrading natural resources and frequent drought occurrences, development of high yielding, drought tolerant cotton cultivars is critical for sustainable cotton production across countries. Six genotypes identified for drought tolerance, wider adaptability and better fibre quality traits were characterized for various morpho-physiological and biochemical characters and their molecular basis was investigated under drought stress.

Rapid detection of Tobacco streak virus (TSV) in cotton (Gossypium hirsutum) based on Reverse Transcription Loop Mediated Isothermal Amplification (RT-LAMP).

Tobacco Streak Virus (TSV) belongs to the genus Ilarvirus of the family Bromoviridae an emerging pathogen posing threat to the crop species worldwide. Identification of symptoms due to TSV infection by visual observation of plants often results in misdiagnosis as symptoms produced by this virus can match with those reflecting physiological and nutritional disorders affecting cotton. Development of diagnostic tools with rapidity will have immense role to play in detection and management of the emerging virus.

Mitochondria COI-based genetic diversity of the cotton leafhopper Amrasca biguttula biguttula (Ishida) populations from India.

Amrasca biguttula biguttula (Ishida), the cotton leafhopper, is a polyphagous insect pest of Asia and Southeast Asian countries. We sequenced a mitochondrial COI gene fragment from 67 individuals of cotton leafhopper collected from 7 major cotton growing states of North, Central, and South India. Genetic divergence analysis of leaf hopper population across India confirmed the presence of single species.