Comparison between data mining methods to assess calving difficulty in cattle

Abstract

Comparison between data mining methods to assess calving diffi culty in cattle ¤ Comparación entre métodos de minería de datos para evaluar la difi cultad al parto en ganado AbstractBackground: Dystocia in cattle results in adverse consequences (increased calf morbidity and mortality, decreased fertility, and milk production, lower cow survival and reduced welfare) leading to considerable economic losses. Objective: To classify calvings in dairy cattle according to their diffi culty using selected data mining methods [classifi cation and regression trees (CART), chi-square automatic interaction detection trees (CHAID) and quick, unbiased, effi cient, statistical trees (QUEST)], and to identify the most signifi cant factors aff ecting calving diffi culty. The results of data mining methods were compared with those of a more traditional generalized linear model (GLM). Methods: A total of 1,342 calving records of Polish HolsteinFriesian black-and-white heifers from four farms were used. Calving diffi culty was divided into three categories (easy, moderate and diffi cult). Results: The percentages of calvings correctly classifi ed by CART, CHAID, QUEST, and GLM were as follows: 35.14, 18.92, 19.82, and 43.24% (easy), 68.70, 73.91, 81.74, and 41.74% (moderate), and 77.27, 85.45, 73.64, and 81.82% (diffi cult), respectively. The most important factors aff ecting calving diffi culty were bull's rank (based on the mean calving diffi culty score of its daughters), calving age, farm category (based on its mean milk yield) and calving season. Conclusion: All classifi cation models were satisfactory and could predict the class of calving diffi culty.

Classification and regression tree analysis to predict calving ease in Sussex heifers using pelvic area dimensions and morphological traits

“…Dystocia (birth difficulty) in cows leads to various hostile consequences for the dam and its progeny [ 1 ]. These include increased calf morbidity and mortality, decreased fertility and milk production, low cow survival, health welfare, and economic losses [ 2 , 3 ].…”

“…CART predictions can be used as an aid to a farmer in the decision-making process regarding herd management [ 8 ]. CART might be used by dairy cattle farmers as a classification model to predict the class of dystocia [ 1 ]. Zaborski et al [ 9 ] indicated that data mining algorithms are useful for discovering dystocia in Polish Holstein Friesian black and white cattle.…”

The use of a rule-based module as a decision support system for dystocia detection in dairy cows

“…The proportion of correctly indicated difficult calvings in heifers by RBM was also higher than that diagnosed by QUEST. In the case of heifers (Zaborski et al, 2017), the proportions of correctly identified easy, moderate and difficult calvings on the independent test set by CART were 35.14%, 68.70% and 77.27%. The total accuracy was 60.41%.…”

“…Only five of the above predictors (SIRE, AGE, HERD, SEX, CLVS) were used for heifers. A detailed description of the dataset is given in Zaborski et al (2016Zaborski et al ( , 2017.…”

“…The "if-then" rules used in the present study were extracted from the three types of decision trees (classification and regression trees -CART, chi-square automatic interaction detector trees -CHAID and quick, unbiased, efficient statistical trees -QUEST). Details about the development of these models are presented in Zaborski et al (2016Zaborski et al ( , 2017. The total number of rules utilized by the RBM system was 46 (15 for heifers and 31 for cows).…”