Mr. Pankaj Nagar will present his MTP2 as per the details below:

Date: 26 June 2026

Time: 1530–1700 hrs

Venue: C-TARA Conference Room No.1

Title: Multilayer Farming System in Sagar, Madhya Pradesh: Classification and Decision Support

Guide: Prof. Amit Y. Arora

Examiners: Prof. Subhankar Karmakar, Prof. Parameshwar D. Udmale

Abstract:

Multilayer Farming Systems (MFS) have emerged as a promising strategy for enhancing land productivity, resource-use efficiency, and income generation for smallholder farmers. However, the adoption of such systems remains limited due to the complexity of crop selection and resource management, as well as the lack of decision-support tools tailored to local farming conditions. Three research gaps motivate this study:

(1) The indigenous multilayer farming model practised in the Sagar region of Madhya Pradesh has not been systematically documented and analysed.

(2) Limited empirical evidence exists on the microclimatic effects of the grass-canopy trellis system used in these farms, particularly regarding light interception and its implications for understory crops.

(3) No decision-support framework currently exists to assist farmers in selecting suitable multilayer crop combinations under local constraints of soil, water, labor, and capital.

The study adopts a mixed-methods approach combining field observations, farmer surveys, microclimatic measurements, and computational modelling. A structured classification matrix of multilayer crop combinations was developed from field data and practitioner knowledge. Light interception under the grass canopy was quantified using field measurements, while soil-water dynamics were assessed using a biophysical water balance framework. These datasets were integrated into a prototype Multilayer Farming System Decision Support System (MFS-DSS), which evaluates crop combinations based on biophysical feasibility, labour requirements, and economic performance.

The research contributes to the systematic documentation of the Sagar MFS model, provides empirical evidence of its microclimatic functioning, and demonstrates the potential of constraint-based decision support to improve the planning and adoption of multilayer farming systems under smallholder conditions.