Agricultural Advisory Diagnostics Using a Data-Based Approach

Agricultural Advisory Diagnostics Using a Data-Based Approach: Test Case in an Intensively Managed Rural Landscape in the Ganga River Basin, India

Adla, Soham (Technische Universität München)
Gupta, Surya (ETH Zürich)
Karumanchi, Sri Harsha (Kritsnam Technologies Private Limited)
Tripathi, Shivam (Indian Institute of Technology Kanpur)
Disse, Markus (Technische Universität München)
Pande, S. (TU Delft Water Resources)

2022

Low technology adoption through agricultural extension may be a consequence of providing generic information without sufficient adaptation to local conditions. Data-rich paradigms may be disruptive to extension services and can potentially change farmer-advisor interactions. This study fills a gap in pre-existing, generic advisory programs by suggesting an approach to “diagnose” farm-specific agricultural issues quantitatively first in order to facilitate advisors in developing farm-centric advisories. A user-friendly Farm Agricultural Diagnostics (FAD) tool is developed in Microsoft Excel VBA that uses farmer surveys and soil testing to quantify current agricultural performance, classify farms into different performance categories relative to a localized performance target, and visualize farm performance within a user-friendly interface. The advisory diagnostics approach is tested in Kanpur, representative of an intensively managed rural landscape in the Ganga river basin in India. The developed open-source tool is made available online to generate data-based agricultural advisories. During the field testing in Kanpur, the tool identifies 24% farms as nutrient-limited, 34% farms as water-limited, 27% farms with nutrient and water co-limitations, and the remaining farms as satisfactory compared to the localized performance target. It is recommended to design advisories in terms of water and nutrient recommendations which can fulfill the farm needs identified by the tool. The tool will add data-based value to pre-existing demand based advisory services in agricultural extension programs. The primary users of the tools are academic, governmental and non-governmental agencies working in the agricultural sector, whose rigorous scientific research, soil testing capacity, and direct stakeholder engagement, respectively, can be harnessed to generate more data-based and customized advisories, potentially improving farmer uptake of agricultural advisories.

advisory diagnostics
agricultural extension
data-based advisory
soil quality index
water use efficiency

http://resolver.tudelft.nl/uuid:d2f1060d-3238-47c0-bf1c-644d10597e62

https://doi.org/10.3389/frwa.2021.798241

2624-9375

Frontiers in Water, 3

Institutional Repository

journal article

© 2022 Soham Adla, Surya Gupta, Sri Harsha Karumanchi, Shivam Tripathi, Markus Disse, S. Pande