Tech-Enabled Dairy Farming: Empowering Small-Holders for Profitable Growth

Abstract

India has achieved the status of being the largest producer of milk for more than three decades now but has been unable to become a net surplus country. As a result, India is still a non-player in the international milk market. There is only one way of looking at the status. The growth rate in milk production over this long period of over 30 years has been unable to outgrow the growth in domestic demand. This means that the existing incentive for enhancing growth in milk production is by way of increase in the price of milk, cow dung and urine at the farm gate and the salvage value of the animal are insufficient vis-a-vis rising cost of inputs. And the industry players of all hues and colors with complete protection from external competition vide appropriate policy have become self-conceited. At the numero uno position, this is simply unacceptable; for the lives of millions of farmers across the country are dependent on it for income and nutrition! Dairy contributed 5.3% of agricultural GDP¹, with milk as the leading agricultural produce! The growth rate in milk production is said to have been 5.6% in 2020, down from 6.5% in 2019. In 2020, the milk production is said to have touched 198.4 million metric tonne¹. Importantly, smallholding dairy farmers contribute more than 90% of the milk produced in India. Dairy animal rearing, a sub-sector of Indian agriculture, is supplementary and symbiotic to agriculture. It adds substantial and a regular income to more than 75 million households in India, directly. Of the several constraints that a smallholding dairy farmer faces, the first and most important one, one that has not been addressed to date, is the lack of credible and timely information on key technical and financial parameters about their own individual animal with the relevant point of reference for comparison. The two when put together automatically establish a self-learning feed-back loop. Interestingly it is also one that is easily surmountable with the information and communication technology available today in terms of hardware and software.

This conceptual research paper focuses on unraveling this blind spot at the individual animal level such that the smallholding dairy farmers are able to enhance their profitability through a process of self-learning. This is attempted by converting cross-sectional data of daily milk production into a longitudinal data i.e. lactation graph and peer pressure. This is to enable the farmer to reduce the risks involved and cost of production and marketing, on her/his own manner and will. The resultant incremental profit is expected to encourage them to produce more milk from their existing animals. A move from sub-optimal to optimal position, in a way. This is expected to be achieved using simple visual tools vide application on one’s smartphone, with the data updated, verified with Participatory Guarantee System (PGS) and be available 24x7 free of cost to each farmer at an individual animal level, as private information along with the mean, median, mode, standard deviation, maximum, minimum of a predefined cohort of animals, as public information.