Yield gap in milk production is considerable in Indian Himalayan state of Meghalaya

Abstract

Yield gaps in milk production are here defined as the differentials between the actual yield obtained by the dairy farmer and the potential farm yield (production achieved by the top 10% of farmers: Gap 2) as well as the differential between this potential farm yield and the yield registered in the research stations (Gap 1). Assessment of yield gaps provides valuable information on potential production enhancement and drivers behind yield gaps. Milk production can be increased by narrowing the predominant large yield gaps in resource-poor smallholder farming system. Hence, this study assessed the milk yield gap and factors affecting the yield gap in Ri-Bhoi district of Meghalaya, a state located in the north-eastern Himalayan region of India. This research paper provides a scope for exploring the possibilities for improving dairy production in the state as well as contributing to literature through incorporating crucial determinants responsible for milk yield gap. A sample of 81 respondents was drawn purposely from two blocks of the district. The results indicated that the average number of cattle per household was 9.38 in standard animal units. The total yield gap was estimated at 6.20 l (91.06%) per day, composed of 0.80 l (11.76%) per day of yield gap I and 5.40 l (79.30%) per day of yield gap II. This demonstrates that the top performing farms were achieving a production level not dissimilar to that obtained on the research stations, but many were doing far less well. The size of cattle shed, dairy farming experience, concentrate price and human labour were the important determinants of the yield gap. Hence, encouraging the right stocking density of cattle, training on the preparations of home-made concentrates, access to cheap and quality concentrates, incorporating training and experience sharing on proper dairy management practices and use of technology could benefit the dairy farmers of the region.

Estimation of milk yield gap and factors associated in local cattle of Meghalaya: Application of ANCOVA model

“…In WKH, actual farm yield was observed to be 0.79 L/day to make the YG-2 of 27.85% whereas, in SWKH, the actual farm yield was 0.99 L/day raising the YG-2 to 37.37%. These results were in conformity with Kemboi et al 2021 in which they found total yield gap (91.06%) per day, composed of (11.76%) per day of yield gap-1 and (79.30%) per day of yield gap-2 and further explained that the top performing farms were achieving a production level not dissimilar to that obtained on the research stations, but many were doing far less well. After computing and summing up these, the total yield gap turned out to be 244.83% in the state of Meghalaya while it was 279.75% and 203.03% in districts of WKH and SWKH, respectively.…”

“…In case of pregnant heifer, standard animal unit was observed only in WKH, although it was very low (0.04 SAU). Contrary to it, similar study of Kemboi et al 2021 in Meghalaya indicated that the average number of cattle per household was 9.38 in standard animal units.…”

Evaluating Yield Gap and Yield Improvement Potential in the Dairy Sector of Pakistan

“…The scant literature on the dairy yield gap tends to examine mixed crop and livestock farmers in Sub-Saharan Africa (Henderson, et al 2016), cross-bred cattle in the North-Eastern state of India (Paul and Chandel, 2010), milk production in the Indian Himalayan state of Meghalaya (Kemboi, et al 2021), attainable bovine milk yields in Ethiopia and India (Mayberry, et al 2017) and genetic yield potential of milk in Pakistan (Iqbal & Ahmad, 1999).…”