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

2021 ◽  
pp. 1-7
Author(s):  
Evans Kemboi ◽  
S. M. Feroze ◽  
Ram Singh ◽  
Jabir Ahmed ◽  
Hehlangki Tyngkan
Keyword(s):  
Milk Production ◽  
Milk Yield ◽  
Management Practices ◽  
Total Yield ◽  
Stocking Density ◽  
Farming System ◽  
Smallholder Farming ◽  
Yield Gap ◽  
The North ◽  
Yield Gaps

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.

scholarly journals Economics of Milk Production and Yield Differentials among the Marginal Women Farmers of Jharkhand State in India

2019 ◽  
pp. 1-11
Author(s):  
Aniketa Horo ◽  
B. S. Chandel
Keyword(s):  
Milk Production ◽  
Milk Yield ◽  
Total Yield ◽  
Fixed Cost ◽  
Yield Gap ◽  
Potential Yield ◽  
Average Productivity ◽  
Net Returns ◽  
Yield Gaps ◽  
Crossbred Cow

Aim: To determine the economics of milk production and yield gaps of crossbred cow, buffalo and indigenous cow in Jharkhand State of India. Study Design: The study was designed to cater the scope of production economics in reality by suggesting ways to bridge the yield gaps. Place and Duration of Study: The present study was conducted using 130 beneficiary farmers in Hazaribagh and Khunti districts of Jharkhand during the 2016-17 agricultural year. Methodology: As per the technique of the yield gap analysis, developed by Gomez (1977), the total yield gap is the sum of Yield Gap I (YG I) and Yield Gap II (YG II). The various cost components were identified under fixed cost and variable cost. Gross returns and net returns were then calculated accordingly. Results: The sampled households were post-stratified into two groups: Group 1 abbreviated as G1, having less than or equal to 2 lactating animals and Group 2 as G2, having more than two lactating animals. The proportion of G1 and G2 households were about 79 and 21 per cent, respectively. The results of data analysis reflected that milk yield gap between potential yield and actual yield (YG II) was higher than yield gap between experimental yield and potential yield (YG I) for both household groups across all the type of dairy animals. The YG II in crossbred cow was more than two times higher on G1 farm as compared to G2 farm while it was more than five times higher in local cow. The average productivity of crossbred (9.23 litres/ day) was much higher than the average productivity of buffalo (6.09 litres) and local cow (4.98 litres/day). Conclusion: Overall value of total yield gap (TYG) entails that if all the constraints regarding the milk production were tackled then the milk yield of the two districts could be increased by about 43 per cent. Buffalo was providing higher net returns per day per animal (Rs. 7.39) in comparison to crossbred (Rs. 5.19). Net returns both for per day and per litre were negative in case of local cow. The study reveals that the marginal farmers can become economically stable by incorporating dairying (crossbred and buffalo) as a component in their farming system.

Management practices for tropical grasses and their effects on pasture and milk production

1981 ◽  
Vol 21 (109) ◽  
pp. 196 ◽  
Author(s):  
TM Davison ◽  
RT Cowan ◽  
PK O'Rourke
Keyword(s):  
Milk Production ◽  
Milk Yield ◽  
Management Practices ◽  
Total Yield ◽  
Cow Milk ◽  
Panicum Maximum ◽  
Rotational Grazing ◽  
Pasture Management ◽  
Pasture Yield ◽  
Friesian Cows

Two experiments examined the effect different pasture management strategies had on individual cow milk yield during the summer wet season. In control treatments pasture was continuously grazed. In managed pastures the aim was to produce swards with a high leaf and low stem content. The grasses Panicum maximum cv. Gatton and Brachiaria decumbens were used in both experiments. Experiment one consisted of three pasture treatments; the stock were 1 8 Friesian cows. The control treatment was grazed continuously with no pasture management and was compared with two subjectively applied management treatments in which pasture was either slashed or stocked at variable rates in an attempt to increase pasture quality. The experiment lasted 17 weeks. Each time pastures were slashed or extra cows were added milk yield per cow fell. The lower each grass was slashed or the greater the number of cows added to a paddock the greater the fall in milk yield. Measurements of pasture yield, height and structural composition showed that slashing and variable stocking could increase the leaf percentage in the pasture, but not without seriously decreasing total leaf yield. In experiment two, 24 Friesian cows were used to compare the following treatments over a 10-week period (a) control-continuous grazing, (b) rotational grazing using a 2-week grazing, 2-week spelling regime and (c) rotational grazing with slashing after each grazing period. Milk yields averaged 10.6, 9.8 and 9.6 kg/cow day1, respectively (P> 0.05), and 10.1 and 9.9 kg/cow day-1 for B. decumbens and P. maximum pastures (P> 0.05). As in the first experiment, leaf percentage was increased by management treatments, but not without decreasing total pasture yield to the level where it limited milk production. Leaf yields could only be increased with an associated increase in total pasture yield. It was concluded that grazing management decisions should be based on total pasture on offer rather than any percentage component of total yield.

scholarly journals Wheat yield gaps across smallholder farming systems in Ethiopia

2021 ◽  
Vol 41 (1) ◽  
Author(s):  
João Vasco Silva ◽  
Pytrik Reidsma ◽  
Frédéric Baudron ◽  
Moti Jaleta ◽  
Kindie Tesfaye ◽  
...  
Keyword(s):  
Stochastic Frontier Analysis ◽  
Stochastic Frontier ◽  
Wheat Yield ◽  
Farming Systems ◽  
Smallholder Farming ◽  
Yield Gap ◽  
Frontier Analysis ◽  
Ecological Zones ◽  
Relative Contribution ◽  
Yield Gaps

AbstractWheat yields in Ethiopia need to increase considerably to reduce import dependency and keep up with the expected increase in population and dietary changes. Despite the yield progress observed in recent years, wheat yield gaps remain large. Here, we decompose wheat yield gaps in Ethiopia into efficiency, resource, and technology yield gaps and relate those yield gaps to broader farm(ing) systems aspects. To do so, stochastic frontier analysis was applied to a nationally representative panel dataset covering the Meher seasons of 2009 and 2013 and crop modelling was used to simulate the water-limited yield (Yw) in the same years. Farming systems analysis was conducted to describe crop area shares and the availability of land, labour, and capital in contrasting administrative zones. Wheat yield in farmers’ fields averaged 1.9 t ha− 1 corresponding to ca. 20% of Yw. Most of the yield gap was attributed to the technology yield gap (> 50% of Yw) but narrowing efficiency (ca. 10% of Yw) and resource yield gaps (ca. 15% of Yw) with current technologies can nearly double actual yields and contribute to achieve wheat self-sufficiency in Ethiopia. There were small differences in the relative contribution of the intermediate yield gaps to the overall yield gap across agro-ecological zones, administrative zones, and farming systems. At farm level, oxen ownership was positively associated with the wheat cultivated area in zones with relatively large cultivated areas per household (West Arsi and North Showa) while no relationship was found between oxen ownership and the amount of inputs used per hectare of wheat in the zones studied. This is the first thorough yield gap decomposition for wheat in Ethiopia and our results suggest government policies aiming to increase wheat production should prioritise accessibility and affordability of inputs and dissemination of technologies that allow for precise use of these inputs.

The effects of days-open on milk yield and on breeding policy post partum

1979 ◽  
Vol 29 (1) ◽  
pp. 109-119 ◽  
Author(s):  
R. Bar-Anan ◽  
M. Soller
Keyword(s):  
Milk Production ◽  
Milk Yield ◽  
Post Partum ◽  
Economic Value ◽  
Total Yield ◽  
Annual Production ◽  
Initial Yield ◽  
Days Open

ABSTRACTThe effects of days-open on milk yields in current lactations and in following lactations were estimated from 71 911 current and 68 693 following lactation records. Yields were expressed as 305-day, total and annual records, where annual record = 365 × (total yield/days between calvings).The data were grouped according to current days-open, corrected for initial yield differences and analysed separately for heifers and cows in Moshav (moderate-yielding) and Kibbutz (high-yielding) herds. Current 305-day records increased by 15 to 18 kg milk/day-open up to 90 days-open, and 2 to 3 kg/day-open thereafter. In contrast, the effects of increasing days-open on annual yields were generally small and negative, being positive only for heifers up to 90 days-open. Thus 305-day records heavily under-rated annual yields of fertile cows. For current lactations, 70 to 100 days-open for heifers and 30 to 50 days-open for cows resulted in the highest annual production. Yields in following lactations were positively associated with days-open in the previous lactation. The effect was highest in high-yielding herds, suggesting that high-yielding cows respond positively to some rest between calvings.Combining the effects of days-open on current and following lactation yields and on the calf crop: in high-yielding herds heifers had the highest productivity when mated not earlier than 70 days post partum, while in moderately-yielding herds days-open did not affect productivity. Cows in high-yielding herds achieved highest productivity at 41 to 90 days-open, while cows in moderately-yielding herds were most productive when mated as early as possible.A comparison of the economic value of sire fertility and sire transmitting ability for milk production showed that fertility may often be over-rated.

A report on management practices and milk production from jersey cows raised in Ibadan

2015 ◽  
Vol 11 (2) ◽  
pp. 98-104
Author(s):  
OA Olorunnisomo ◽  
AA Oni ◽  
JO Abiola
Keyword(s):  
Milk Production ◽  
Milk Yield ◽  
Management Practices ◽  
Cooling System ◽  
Zebu Cattle ◽  
Tropical Condition ◽  
Jersey Cattle ◽  
Lactation Length ◽  
The University ◽  
University Of Ibadan

In order to kick-start milk production and upgrade genetic base of local zebu cattle at the University of Ibadan, four in-calf Jersey heifers and one bull were acquired in September 2012, from a pure herd of Jersey cattle maintained on a private farm in Shonga, Kwara State, Nigeria. Management at Shonga was based on an intensive, zero-grazing system. The animals were apparently in a good state of health at the time of procurement. At the University of Ibadan, management was also intensive, with partial grazing, fortified grass silage and concentrates supplementation. Health management of Jersey cattle involved preventive and curative measures. Calving occurred within 7 and 156 days of arrival at Ibadan. Two out of four heifers calved successfully while two had still-births. Calves were allowed to suckle their dams for 14 days after calving and bottle-fed from milk collected from their dams afterwards. Milking was done twice daily at 7am and 4pm using a portable milking machine. Milk yield averaged 8.8 kg/cow/day with lactation length ranging between 93 and 246 days. Average composition of milk was 13.69, 3.60, 4.73, 0.65 and 4.71% for total solids, protein, fat, ash and carbohydrate respectively. In order to maximize milk production from Jersey cattle under the humid tropical condition of Ibadan, there is need to maintain a high plane of nutrition, adopt a preventive healthcare system and incorporate a cooling system to ameliorate the effects of high ambient temperatures.Key words: calving age, dairy cattle, lactation length, milk composition, milk yield

scholarly journals Unravelling the variability and causes of smallholder maize yield gaps in Ethiopia

Food Security ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 83-103 ◽  
Author(s):  
Banchayehu Tessema Assefa ◽  
Jordan Chamberlin ◽  
Pytrik Reidsma ◽  
João Vasco Silva ◽  
Martin K. van Ittersum
Keyword(s):  
Stochastic Frontier Analysis ◽  
National Level ◽  
Total Yield ◽  
Maize Yield ◽  
Sub Saharan Africa ◽  
Yield Gap ◽  
Potential Yield ◽  
Frontier Analysis ◽  
Yield Gaps ◽  
Maize Yields

AbstractEthiopia has achieved the second highest maize yield in sub-Saharan Africa. Yet, farmers’ maize yields are still much lower than on-farm and on-station trial yields, and only ca. 20% of the estimated water-limited potential yield. This article provides a comprehensive national level analysis of the drivers of maize yields in Ethiopia, by decomposing yield gaps into efficiency, resource and technology components, and accounting for a broad set of detailed input and crop management choices. Stochastic frontier analysis was combined with concepts of production ecology to estimate and explain technically efficient yields, the efficiency yield gap and the resource yield gap. The technology yield gap was estimated based on water-limited potential yields from the Global Yield Gap Atlas. The relative magnitudes of the efficiency, resource and technology yield gaps differed across farming systems; they ranged from 15% (1.6 t/ha) to 21% (1.9 t/ha), 12% (1.3 t/ha) to 25% (2.3 t/ha) and 54% (4.8 t/ha) to 73% (7.8 t/ha), respectively. Factors that reduce the efficiency yield gap include: income from non-farm sources, value of productive assets, education and plot distance from home. The resource yield gap can be explained by sub-optimal input use, from a yield perspective. The technology yield gap comprised the largest share of the total yield gap, partly due to limited use of fertilizer and improved seeds. We conclude that targeted but integrated policy design and implementation is required to narrow the overall maize yield gap and improve food security.

Milk yield and milk composition from grazing primiparous non-dairy crossbred ewes

2006 ◽  
Vol 57 (4) ◽  
pp. 377 ◽  
Author(s):  
J. E. Morgan ◽  
N. M. Fogarty ◽  
S. Nielsen ◽  
A. R. Gilmour
Keyword(s):  
Weight Gain ◽  
Milk Production ◽  
Milk Yield ◽  
Milk Fat ◽  
Total Yield ◽  
Milk Composition ◽  
Ewe Lambs ◽  
Daily Milk Yield ◽  
Sire Breed ◽  
Daily Milk

Milk production and milk composition were studied in 520 primiparous Merino crossbred ewes that were the progeny of 30 sires from several maternal crossing breeds including Border Leicester, Coopworth, Finnsheep and East Friesian. The ewes were born in 3 years (1997, 1998, and 1999), with 3 sires used in every year to provide genetic links. The crossbred ewe lambs were randomly assigned to autumn or spring joining groups and mated to Poll Dorset rams to lamb at 12 or 19 months of age. Ewes were milked on 3 days during their first lactation at approximately 3, 4, and 12 weeks after lambing. On each milking day, each ewe was initially injected with oxytocin, milked out by machine, and then hand-stripped. This procedure was repeated approximately 4 h later, with the milk weight and time recorded to extrapolate to daily milk yield, and composition of the milk was determined. Daily milk yield was analysed using REML mixed models procedures and 3 measures of milk production were predicted: peak milk yield at 21 days of lactation, total milk yield from 21 to 90 days of lactation, and length of lactation (days for daily yield to decline to 600 g/day). Milk composition traits (%fat, %protein, %lactose) and proportion of machine milk yield were analysed with similar models. Sire breed, number of lambs born and suckled, season, and ewe weight gain from mid-pregnancy until lamb weaning were all significant (P < 0.01) for daily yield, which declined from 2.1 kg/day at 21 days to 0.7 kg/day at 90 days of lactation. The Finnsheep-cross ewes had lower peak milk yield (1.84 ± 0.08 v. 2.09–2.19 ± 0.1 kg/day) and lower total yield of lactation (21–90 days) than all the other breed-cross ewes (78 ± 3 v. 92–107 ± 5 kg). The East Friesian-cross ewes had significantly longer lactations (128.8 ± 10.9 days) than the Border Leicester (98.1 ± 4.4 days) and Coopworth (93.7 ± 4.2 days), with the Finnsheep-cross ewes the shortest (80.1 ± 3.1 days). The East Friesian-cross ewes had the greatest and the Finnsheep-cross ewes the least total yield of lactation (107 ± 5 and 78 ± 3 kg, respectively). There were significant differences in peak milk yield for ewes bearing and suckling single lambs, twin-born and single-raised lambs, and twin-born and raised lambs (1.86 ± 0.04, 2.03 ± 0.09, and 2.37 ± 0.07 kg/day, respectively). There was a significant decline in daily milk yield with increasing ewe weight gain from mid-pregnancy to lamb weaning (–18.1 ± 4.2 g/kg). All the components of milk composition changed from the peak of milk production at 3 weeks to the end of lactation. The East Friesian-cross ewes had significantly lower milk %fat (by approx. 1 percentage point) at both 21 days and 90 days of lactation than ewes by all other sire breeds. The 30 sire progeny mean deviations for daily milk yield ranged from –292 to +276 g/day, with considerable ranges between sires within the sire breeds. The implications for lamb production and breeding programs are discussed.

scholarly journals Practices to Reduce Milk Carbon Footprint on Grazing Dairy Farms in Southern Uruguay: Case Studies

2014 ◽  
Vol 3 (2) ◽  
pp. 1 ◽  
Author(s):  
Carolina Lizarralde ◽  
Valentin Picasso ◽  
C. Alan Rotz ◽  
Monica Cadenazzi ◽  
Laura Astigarraga
Keyword(s):  
Milk Production ◽  
Milk Yield ◽  
Carbon Footprint ◽  
Best Management Practices ◽  
Dry Matter ◽  
Management Practices ◽  
Dairy Farms ◽  
Important Indicator ◽  
Feeding Management ◽  
The Impact

<p>Carbon footprint (CF) is an increasingly important indicator of the impact of a product on climate change. This study followed international guidelines to quantify the CF of milk produced on 24 grazing-based dairy farms in southern Uruguay. Cows grazed all year-round and were supplemented with concentrate feeds. Dairy farms varied in annual milk yield per cow (5672 ± 1245 kg fat and protein corrected milk [FPCM]), milk production per ha (4075 ± 1360 kg FPCM/ha), cow stocking rate (0.71 ± 0.12 cows/ha), feed intake (13.3 ± 2.2 kg dry matter [DM]/cow/day) and percentage of concentrate in the diet (36 ± 12% DM) giving an average CF of 0.99 ± 0.10 kg CO<sub>2</sub> (equivalent [eq]/kg FPCM) over all farms. Total milk production per ha, milk yield per cow and dry matter intake explained most of the variation in CF. Strategies that provide the highest milk production per ha using high yielding cows and a high portion of lactating cows in the herd were identified as the best management practices for reducing CF. Low forage intake in Uruguay is often a consequence of low yielding pastures and high stocking rates. Overall, this study concluded that a reduction in CF is not achieved through increased concentrate intake unless forage consumption is also unconstrained. Improved pasture and feeding management can be used to reduce the CF of milk produced in Uruguay.</p>

A note on regional variations in the seasonality of milk production in dairy cattle

1981 ◽  
Vol 32 (1) ◽  
pp. 105-108 ◽  
Author(s):  
P. D. P. Wood
Keyword(s):  
Dairy Cattle ◽  
Milk Production ◽  
Milk Yield ◽  
Seasonal Variations ◽  
Protein Concentration ◽  
Total Yield ◽  
Seasonal Fluctuation ◽  
Stage Of Lactation ◽  
Daily Milk Yield ◽  
Daily Milk

ABSTRACTMean daily milk yield, fat concentration and protein concentration in the milk of 579 303 British Friesian, 6 608 Shorthorn, 27 374 Ayrshire, 19 529 Jersey and 19 760 Guernsey cattle were recorded monthly from August 1978 to July 1979 inclusive, and classified by breed, parity, stage of lactation, and five geographical areas according to the location of the herd. Parameters of the function Y(n) = anbecn were estimated for each breed/parity/area group for yield, fat concentration and protein concentration (b and c describe the shape of the curve, a is a scalar, n the week of lactation and e the base of natural logarithms). Systematic deviations from the function were associated with the season of production, reflecting the spring and summer flush of milk yield. Fat and protein concentrations also exhibited seasonal variations from the underlying curve. After correction for the seasonal fluctuation in production, there was no variation in total yield, fat concentration or protein concentration associated with the month of calving.

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