This study aims to use advanced machine learning techniques supported by Principal Component Analysis (PCA) to estimate body weight (BW) in buffalos raised in southeastern Mexico and compare their performance. The first stage of the current study consists of body measurements and the process of determining the most informative variables using PCA, a dimension reduction method. This process reduces the data size by eliminating the complex structure of the model and provides a faster and more effective learning process. As a second stage, two separate prediction models were developed with Gradient Boosting and Random Forest algorithms, using the principal components obtained from the data set reduced by PCA. The performances of both models were compared using R², RMSE and MAE metrics, and showed that the Gradient Boosting model achieved a better prediction performance with a higher R² value and lower error rates than the Random Forest model. In conclusion, PCA-supported modeling applications can provide more reliable results, and the Gradient Boosting algorithm is superior to Random Forest in this context. The current study demonstrates the potential use of machine learning approaches in estimating body weight in water buffalos, and will support sustainable animal husbandry by contributing to decision making processes in the field of animal science.

Objective: This study was conducted to evaluate the effect of offering (OSF) or not (NSF) supplemental feed at milking on temperament (TS), udder hygiene (UHS) and body condition (BCS) scores, and milk yield per milking (MYM), milk quality traits, and profitability of primiparous Anatolian buffalo cows at 90 days of lactation confined in closed-tied (CB) or semi-open free-stall (OB) barns.Methods: In Experiment I, 108 cows were selected to encompass four treatments (OBOSF, OB-NSF, CB-OSF, and CB-NSF) of 27 cows, considering barn type (OB and CB) and supplementary feed (OSF and NSF) at milking. In Experiment II, 60 OB cows were selected to encompass one of five groups of 12 cows each: i) no supplemental feed (CON), ii) commercial concentrate (CC), iii) CC + corn silage (CCS), iv) CCS + alfalfa hay (CSA), or v) CC + ryegrass silage (CRS) at milking.Results: The TS and UHS of the OB and OSF cows were lower (better) than those of the CB and NSF cows, respectively. The OSF increased milk protein, lactose, and solids-not-fat but decreased milk freezing point and electrical conductivity compared with the NSF. The MYM and milk fat of the OB-OSF cows were higher than those of the OB-NSF and CBNSF cows. The TS and UHS of the cows negatively correlated with MYM and some milk chemicals (fat, protein, and solids-not-fat), but BCS correlated positively. The TS and milk electrical conductivity of the CCS, CSA, and CRS cows were lower than those of the CON and CC cows, but BCS, MYM, and milk fat were higher. Partial budget analysis identified a higher net profit for supplemental feed-offered groups (OB-OSF, CCS, CSA, and CRS).Conclusion: Offering roughage with concentrates at milking for indoor primiparous buffalo cows is more conducive to well-being, milk yield, milk quality, and economy.

This study aimed to evaluate whether supplemental feeding at milking (SFAM) positively influences the quantitative−qualitative milk parameters due to improving some welfare assessment traits of multiparous Anatolian buffalo cows confined in semi-open free-stall barns. A total of 76 Anatolian buffalo cows at approximately 90 days in milk were selected to encompass four groups (OSF-2nd, NSF-2nd, OSF-≥3rd and NSF-≥3rd), considering offering (OSF) or not (NSF) supplemental feed at milking and the parity (2nd) and (≥3rd). Data of evaluated variables such as the following ones—(i) subjectively scored welfare assessment traits (temperament, udder hygiene and body condition), (ii) milk yield per milking (MYM), (iii) milk components, and (iv) milk physical traits—were analysed using a linear mixed model and principal component (PC) analysis. The OSF improved the temperament, udder hygiene and body condition scores compared to the NSF. The MYM, the fat content and the fat-to-protein ratio of the OSF were higher than those of the NSF, but milk mineral and electrical conductivity of the OSF were lower than those of the NSF. The parity of cows did not affect the evaluated variables. Four parameters (milk density value and lactose, solids-not-fat and protein contents) could be identified in the PC2 versus PC1 plot. In conclusion, the SFAM enhanced the milk yield and qualitative milk parameters due to improving the welfare status of indoor buffalo cows, regardless of parity.

This study aimed to evaluate the milk components and somatic cell count (SCC) of Anatolian buffalo cows at different stages of lactation (days 15th, 30th, 45th and 60th of lactation) by determining the effects of the age of the cow, calving season and specific gravity of colostrum (SGC) on these milk quality traits. The experiment was conducted using 62 healthy lactating primiparous and multiparous Anatolian buffalo cows at two private farms in Samsun, Türkiye. The SGC values at the second hour (first milking) after birth were measured using a colostrometer, and the milk components were analyzed using a milk analyser. In addition, the SCC in milk was measured with a portable cell counter. The data are divided into three groups: age (≤80 mo and >80 mo), calving season (spring and summer) and SGC (

Herd management and nutrition strategies against increasing negative effects of global warming on farm animals have been the subject of significant debates in recent years. The fact that the changes in the environmental conditions are directly related to the habitats of the animals and the conditions inside the barn can affect the farm animals negatively. Although effects of heat stress differ according to species, especially high-yielding dairy cattle exposed to heat stress, respond with various interactive mechanism such as physiological, biochemical, immunological, anatomical and behavioral. Therefore, with the selection practices that have been going on for many years to improve the yield characteristics of the animals significantly increased. In this respect, the increased heat load in the body of dairy cattle due to the high productivity decreases their tolerance to environmental conditions. This situation adversely affects the productivity of cows with high breeding value. Yield losses, varying according to some factors about heat stress, can be partially explained by decreasing feed intake as a result of a series of hormonal responses affecting appetite center. However, the physiological requirements of cattle must be defined in order to develop appropriate strategies to reduce or eliminate the negative effects of heat stress. In this review, the variations in physiological, biochemical and behavioral mechanisms originating from heat stress in dairy cattle and the care, nutrition and herd management strategies that can be applied to eliminate or reduce the negative effects were discussed.

The aim of this study was to determine the relationships of udder surface temperature (UST) with milk components, and somatic cell count (SCC) in dairy cows during the hot season. The study was carried out with 115 lactating dairy cows (Holstein, Simmental, and Holstein × Simmental) at a private dairy farm in Samsun, Turkey, with monthly visits. The UST was measured from the udder surface before cleaning and milking. At the same time, a portable cell counter and an automatic milk analyzer were used to determine the components and the SCC of the raw milk. The UST values of the cows changed significantly. Increased UST had an adverse effect on milk solids-non-fat (SNF), protein, lactose, and density levels. LogSCC values of cow groups with UST ≤35.0°C, 35.1-36.0°C, >36.0°C were found to be 4.475±0.0803, 4.774±0.1244, and 4.981±0.1491 respectively. The UST negatively correlated with SNF, protein, lactose, density, and freezing point, but positively correlated with LogSCC. As a result, performing UST measurements before milking may be beneficial to monitor udder health and to obtain high quality milk.