Composição do leite de vacas alimentadas com diferentes fontes de compostos nitrogenados

Effect of replacing soybean meal with peanut meal on milk production and fat composition in lactating dairy cows

The objective of this study was to evaluate the effects of replacing soybean meal with peanut meal on milk production, chemical and fatty acid composition, nutritional quality indicators of the lipid fraction, and the economic viability of the diets. Twelve crossbred cows in the initial lactation third, with a bodyweight of 545 ± 37 kg and average milk production of 28 kg/day of milk were distributed in a 4 × 4, triple Latin square design. The treatments consisted of diets with substitution levels of soybean meal for peanut meal (0; 330; 670; and 1000 g/kg in DM). The peanut meal inclusion to replace soybean meal in the diets provided a decreasing linear effect for the protein (P = 0.02) and casein (P = 0.01) concentration in milk. Milk production, total solids concentration, feed efficiency, fatty acid composition, and nutritional quality indicators of the milk lipid fraction were not influenced by the substitution levels. The diet cost per kg DM decreased due to the peanut meal inclusion as a protein source. The partial or total substitution of soybean meal for peanut meal in the feedlot cows diet reduces the cost of feed, without affecting milk production and total solids yield.

Production and composition of milk per Holstein and Jersey cow from two farms in northwest Rio Grande do Sul

ABSTRACT The aim of the present study was to monitor cow milk quality and composition in two farms in the Noroeste Rio-grandense mesoregion, located in the municipalities of Palmeira das Missões and Pinhal - RS. Both herds were mixed, with animals of the Holstein (70%) and Jersey (30%) breeds. The following overall parameters were evaluated: body condition score (BCS), udder dirtiness, and calving order, and the following milk composition factors were measured: total dry extract (TDE), defatted dry extract (DDE), milk lactose, fat, and protein contents, casein, milk urea nitrogen (MUN), and somatic cell count (SCC). Multivariate statistical analysis was performed, and four factors were identified representing combinations of the measured variables. The first factor comprised negative relationships between milk production and cow breed, milk fat content, and milk protein content. The second factor comprised the positive relationships between lactation days and body condition score and milk protein content. The third factor represented the negative relationships between milk lactose content and SCC score, calving order, and BCS. The fourth factor was composed of the positive relationship between delivery order and udder dirtiness. Cluster analysis revealed that individual cows could be categorized into three groups. Monitoring the breed, calving order, body condition score, lactation days, milk production, fat, protein, and lactose contents, somatic cell counts, and udder dirtiness in cows allows greater control of the herd, allowing potential shortcomings to be rectified quickly and economic losses to production to be minimized.