MohammadTaghi Fayazikia; Mohammad Dadpasand; Hamideh Keshavarzi
Volume 25, Issue 2 , July 2023, , Pages 123-132
Abstract
Introduction Mastitis is one of the most frequent and costly diseases of the dairy cattle industry and causes many economic losses, which negatively affects milk yield and composition, fertility, longevity and welfare of cows. The best solution for reducing the economic and biological consequences is ...
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Introduction Mastitis is one of the most frequent and costly diseases of the dairy cattle industry and causes many economic losses, which negatively affects milk yield and composition, fertility, longevity and welfare of cows. The best solution for reducing the economic and biological consequences is early and accurate prediction of mastitis based on indicator factors. So far, various statistical methods have been used to predict mastitis such as linear and multiple regression, and threshold models. Machine learning is another method that has recently widely been used to predict farm profitability, reproductive traits, longevity and abortion in dairy cow. Machine learning is defined as a set of methods for automatically finding patterns in data and then using those patterns to predict possible future data.Material and Methods In this research, the performance of four machine learning algorithms including random forest, decision tree, Naïve Bayes and logistic regression and two sampling methods, over-sampling and under-sampling, were compared to predict risk of clinical mastitis based on data collected in two Holstein dairy herds in Isfahan province. Final dataset included 393504 records on cows calved during 2007 to 2017 of which 13653 cases (3.47%) were infected and 379851 cases (96.53%) were healthy. Factors related to mastitis, including parity, daily milk production, calving
Navid Golestani; Asghar Mogheiseh; Mojtaba Kafi
Volume 20, Issue 3 , November 2018, , Pages 389-399
Abstract
The aim of this study was to determine the incidence and quantify risk factors associated with repeat breeder (RB) syndrome in Isfahan Holstein dairy cows. Calving and insemination data of parities 1 to 7 on 91727 Holstein dairy cows from 62 herds collected during 1993 to 2013 were used. Cows failed ...
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The aim of this study was to determine the incidence and quantify risk factors associated with repeat breeder (RB) syndrome in Isfahan Holstein dairy cows. Calving and insemination data of parities 1 to 7 on 91727 Holstein dairy cows from 62 herds collected during 1993 to 2013 were used. Cows failed to conceive after three or more regularly spaced services in the absence of detectable abnormalities regarded as RB. A multivariate logistic regression model was used to quantify risk factor associated with repeat breeding. Least squares mean number of services per conception were 2.15 ± 0.15 and 2.54 ± 0.15 for normal and RB cows, and uncorrected values were 2.73 and 3.28 for normal and RB cows, respectively. Herd, milk yield, season of calving and season of first insemination, dystocia, stillbirth, abortion and days from calving to first service were the major factors affecting RB syndrome. Average incidence of repeat breeding was 43.7% (27.8-55.2%). Dystocia and stillbirth increased the odds of being RB by 39% and 11%, respectively (P< 0.01). Risk of being RB in high producing cows increased by 79% compared to cows with low milk yield (P< 0.01). Odds of being RB increased by 28% in cows that was RB in previous parity. Fat yield and length of dry period had no significant effect on being RB. Considering at least 75 days distance between calving and first service, insemination in cool seasons, decreasing dystocia and improving reproduction management of high producing cows, could reduce RB syndrome.
Mohammad Reza Rezvani; Shahram Rahimi; Mohammad Dadpasand
Volume 18, Issue 2 , June 2016, , Pages 335-346
Abstract
In order to investigate antioxidant and antimicrobial effects of pomegranate peel powder (PPP), this research was conducted as completely randomized design arranged in a 2 × 2 factorial experiment using pomegranate peel powder (0 and 2 percent) and soybean oil (SO, zero and six percent in growing ...
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In order to investigate antioxidant and antimicrobial effects of pomegranate peel powder (PPP), this research was conducted as completely randomized design arranged in a 2 × 2 factorial experiment using pomegranate peel powder (0 and 2 percent) and soybean oil (SO, zero and six percent in growing period; zero and eight percent in finishing period). One hundred and sixty 11-day-old Ross 308 broiler chickens assigned to four treatments of four replicate each. The results showed that PPP improved the antibody titer in 39-day broilers, increased fat digestibility, improved lactobacillus and decreased E coli micro flora in ileum and cecum significantly (P ≤ 0.05). The SO decreased DM digestibility and lactobacillus micro flora and E coli in ileum and cecum (P ≤ 0.05). As a conclusion adding PPP to the fat containing diets in comparison to control diets; without PPE and SO, improved antibody titer, beneficial gastric micro flora in ileum and cecum and had not any deleterious effect on overall broiler performance.