Farming system typology construction for the adoption of new technologies in north-west India - SHARMA, KARTIK; WALIA, SOHAN SINGH; KAUR, JASHANJOT; BHAGAT, RAKSHIT; LAYEK, JAYANTA (The Indian Journal of Agricultural Sciences, 2025)
The modern agricultural sector is facing significant challenges, viz. productivity, sustainability and profitability due to shrinking landholdings and limited resource base. Therefore, a study was carried in 2020 and 2021 at Punjab Agricultural University, Ludhiana, Punjab, to investigate farm typologies in the north-west part of India using multivariate techniques [Principal Component Analysis (PCA) and cluster analysis (CA) (small diversified farms (Cluster I), larger crop-dominated farms (Cluster II), moderate-sized mixed farms (Cluster III), and large commercial farms (Cluster IV)] surveying 95 farm households in two districts (Tarn Taran and Patiala) of Punjab. By examining socio-economic factors and enterprise contributions, it identifies farm diversity to enhance technology adoption, improve incomes and recommend targeted policy interventions to the farmers. Using multivariate statistical techniques, structural and functional farm characteristics were analysed to construct specific farm typologies. The sequential application of PCA and CA revealed that the surveyed farmers had an average landholding of 17 acres, with a pre-dominant focus on cereal cultivation (cropping intensity: 163.7%) and crop income accounted for 94.1% of total earnings, with dairy and other agricultural allied enterprises contributing minimally. The PCA identified three principal components that explained 51.5% of the variance, emphasizing cropping intensity, income distribution, and livestock dynamics. Cluster analysis grouped households into four typologies i.e. (small diversified farms (Cluster I), larger crop-dominated farms (Cluster II), moderate-sized mixed farms (Cluster III), and large commercial farms (Cluster IV)] surveying 95 farm households in two districts (Tarn Taran and Patiala) of Punjab, each cluster exhibited variations in landholding size, labour utilization, crop-livestock integration, and income composition. Cluster-specific recommendations include technical support, diversification strategies and market-oriented interventions to enhance productivity and sustainability. This typology-based classification integrates socioeconomic and resource characteristics, offering a sustainable framework for targeted agricultural policies and interventions.