Small-scale dairy systems (SSDS) in Mexico represent over 78% of dairy farms and 37% of milk production. In the central highlands, many SSDS base the feeding of herds on irrigated cultivated pastures (mostly cut-and-carry), straws, and large amounts of commercial concentrates that result in high feeding costs and low economic sustainability. Intensive grazing may result in lower feeding costs when compared with cut-and-carry strategies. The high protein content of pasture may meet requirements of dairy cows with moderate milk yield (16–20 kg milk/cow.day), so that lower protein supplements, like ground maize grain, may substitute for commercial concentrates. An on-farm experiment following a participatory rural research approach was undertaken with seven farmers evaluating commercial concentrate (CC) or ground maize grain (MG) as supplement; and two pasture managements, grazing (G) or cut-and-carry (C) of irrigated ryegrass/white clover pastures to assess productive performance and feeding costs. Six farmers participated with four milking cows each and one farmer with two groups of four milking cows in a 2 by 2 factorial experiment. Daily milk yield per cow before the experiment was used as covariate. The experiment lasted 12 weeks. There is a trend in G for higher protein content in milk (P < 0.10). CC showed higher body condition score than MG with a significant interaction for body condition score with the highest body condition score in CCC (P < 0.05). Feeding costs were 15% higher per kg of milk yield and 19% per kg of energy-corrected milk under cut-and-carry but no statistical differences were detected (P > 0.05) in comparison with the grazing strategy. Supplementing with home-grown ground maize grain resulted in 28.5% higher margins per kg of milk produced. Implementing grazing involves less work burden for small-scale dairy farmers, and combined with home-grown grains as supplement is a viable option that may reduce feeding costs in these systems.
The aim of this study was to use dietary factors, including the type of fats, and animal characteristics, to predict enteric methane (CH4) emissions from dairy cows under Canadian conditions. For this purpose, 193 individual observations from six different trials assessing the impact of dietary modification on enteric CH4 production were analyzed. Animal [milk yield (MY), milk fat content, milk protein content, days in milk, body weight (BW), and dry matter intake (DMI)] and dietary variables [organic matter, crude protein, neutral detergent fiber (NDF), acid detergent fiber (ADF), starch, ether extract (EE), rumen-inert fat, and unprotected fat (EE – rumen-inert fat)] were tested. A 5-fold cross validation was used to obtain the following equation: CH4 (g d−1) = −1260.4 + 1.9 × MY (kg d−1) + 62.8 × milk fat (%) –18.4 × milk protein (%) + 11.0 × DMI (kg d−1) + 0.3 × BW (kg) + 58.3 × NDF (% of DM) − 0.8 × NDF2 (% of DM) + 1.9 × starch (% of DM) − 2.5 × EE – rumen-inert fat (% of DM). The mean estimate from the proposed equation (474 g CH4 cow−1 d−1; r = 0.83, RMSE = 40.0) was close to the observed mean emission (476 g CH4 cow−1 d−1). The proposed model has a higher precision to predict CH4 emission from cows fed typical Canadian diets than other models, and it can be used to evaluate CH4 mitigation strategies.
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