Use of correlation, regression and logistic models for the losses estimation of dairy industry from the heat stress

UDC 636.2.034:[57.045: 001.891.573]

DOI: 10.31521/2313-092X/2019-1(101)-11


D.-V. Pasiechko
ORCID ID: 0000-0002-6411-693X
ORCID ID: 0000-0003-1220-2972
L. Dashevska
ORCID ID: 0000-0003-3727-6484


      Due to global warming, frequency of heat stress in farm animals is increasing. As a result, dairy cattle industry loses a lot of money because of under-received products. In order to minimize economic losses, it is necessary to implement measures to counter heat stress, which are preceded by level of loss estimation. Foreign researchers use complex multi-factor models and expensive software to obtain the most accurate estimates. Ukrainian dairy farms do not always have financial ability to order estimation services or carry them out by themselves, moreover, a very high level of accuracy may be unnecessary to prove the feasibility of implementation certain countermeasures. Thus, it is expedient to conduct estimation of heat stress losses using Excel program, meteorological data and databases to monitor the productivity of a farm.
       The research was conducted on the basis of dairy farm “Askaniiske” on livestock cows of Ukrainian black-and-white dairy breed during 2016…2018 period. Relationship between stress level in the environment and in cowsheds was studied. Impact of heat stress on milk yield cows and probability of conception at insemination were investigated. Temperature-humidity index and formula of accumulated level of stress developed by us were used to estimate heat stress level. Correlation-regression model was done according to generally accepted method. Accuracy of estimation was determined on the basis of loss comparison calculation according to N.R. St-Pierre method. It is established that in order to estimate the level of heat stress on a farm, it is necessary to combine estimation according to meteorological data with estimation of microclimate data. Developed models of estimation impact of heat stress on milk yield cows can be used for establishing economic feasibility of countermeasures use. At the same time, their accuracy is relatively low and they are useful for estimation of losses only during the period for which they were done. Model for predicting of insemination success is appropriate to use in conditions of strong stress.
       Thus, despite a number of disadvantages, this method can be used for rough estimation of stress losses and subsequent justification of countermeasures implementation.


       Keywords: heat stress, modeling, dairy cattle, milk yield, insemination.


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