Agroforestry Research: From Field Data to Master's Thesis

Abhishek's master's research centered on a Melia dubia-based agroforestry system for fodder production in semi-arid regions. The study had three defined objectives: characterizing soil before and after plantation, measuring tree characteristics across the crop cycle, and evaluating the economic outcomes of the system.

He designed the experiment around three crop combinations, selecting seed lucerne and oats as the intercrop species alongside Melia dubia trees. Sowing began in October 2024, with data collection at two points: January and March, capturing how the system evolved across the growing season.

The data collection covered soil characteristics, tree measurements, and crop yield figures. Abhishek processed the raw data using OP Start, a statistical software developed by his university, to derive the study's conclusions.

The findings showed that lucerne performed well under shaded conditions, while oats produced the highest economic yield in the intercrop system. Critically, the agroforestry system as a whole generated higher economic returns than a sole cropping system, supporting the case for agroforestry adoption among farmers in semi-arid regions.

He wrote up the full study as a master's thesis, presenting the findings to an examination panel that included an external examiner, his head of department, and faculty members. The thesis was accepted and contributed to his master's degree.