داده‌کاوی برخی سازه‌های مؤثر بر سخت‌زایی در گاوهای شیری ایران

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانش‌آموخته کارشناسی ارشد، گروه علوم دامی، دانشکده کشاورزی، دانشگاه یاسوج

2 دانشیار، گروه علوم دامی، دانشکده کشاورزی، دانشگاه یاسوج

چکیده

داده‌کاوی، به کشف روابط و الگوهای پنهان و ناپیدا در میان حجم عظیمی از داده‌ها می‌پردازد که بدون استفاده از آن، ممکن است این روابط هیچ­گاه آشکار نشوند. تعیین سازه‌های مؤثر بر سخت‌زایی در گاوهای شیری می‌تواند به ضعف مدیریتی صنعت گاو شیری و مشکلات ناشی از آن کمک کند. بنابراین ضروری است که از بین سازه‌های ژنتیکی و غیر ژنتیکی مختلف مؤثر بر سخت‌زایی، مهم‌ترین آن‌ها شناسایی و مدیریت شوند. الگوریتم انتخاب ویژگی یکی از روش‌های داده‌کاوی است که می‌تواند در این زمینه مفید باشد. هدف از این پژوهش تعیین مهم‌ترین سازه‌های مؤثر بر سخت‌زایی گاوهای شیری هلشتاین با استفاده از الگوریتم انتخاب ویژگی بود. کل رکوردها برابر با 413205 به همراه 14 ویژگی مربوط به رکوردهای تولیدمثلی و تولیدی بود. داده با چهار روش مهم الگوریتم انتخاب ویژگی (Best-First،Greedy-Stepwise Genetic-search و Ranker) و نه مدل مختلف (CFS-Subset-Eval ،Gain-Ratio-Attribute- Eval و ...) برای تعیین مهم‌ترین عوامل مؤثر بر سخت‌زایی ارزیابی شدند. نتایج نشان داد روش Genetic-search الگوریتم انتخاب ویژگی، مناسب‌ترین روش برای انتخاب عوامل مؤثر بر سخت‌زایی با استفاده از دسته‌بندی Naive Bayes Tree با کم‌ترین میزان خطا (AMS= 0.011, ARAE=0.001) بود. مهم‌ترین سازه‌های مؤثر بر سخت‌زایی به ‌ترتیب تولید شیر، سن مادر هنگام زایش، شکم زایش، طول دوره آبستنی، شیر تصحیح شده بر اساس چهار درصد چربی، فاصله زایش، فصل زایش، نوع زایش، نسبت چربی به پروتئین، جنس گوساله، وزن گوساله و روزهای باز بودند. انتظار می‌رود با در نظر گفتن سازه‌های مزبور، سخت‌زایی در گاوهای شیری بهتر مدیریت شود. 

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Data mining of some factors affecting dystocia in Iranian dairy cows

نویسندگان [English]

  • M. Montazeri-Najafabadi 1
  • M. Ghaderi-Zefrehei 2
1 Graduated MSc, Department of Animal Sciences, Faculty of Agriculture, Yasouj University, Yasouj, Iran
2 Associate Professor, Department of Animal Sciences, Faculty of Agriculture, Yasouj University, Yasouj, Iran
چکیده [English]

Data mining explores hidden and invisible relationships and patterns in the vast amount of data without which these relationships may never be revealed. Determining the factors affecting dystocia in dairy cattle can help to find the weaknesses of the management of the dairy cattle industry and the resulting problems. Therefore, it is necessary to identify and manage the most important of the various genetic and non-genetic factors that affecting dystocia. The feature selection algorithm is one of the data mining methods that can be useful in this field. This study aimed to determine the most important factors affecting the dystocia of Holstein dairy cows using the feature selection algorithm. The total records were 413205, along with 14 features related to reproductive and production records. Data analyzed with four important methods of feature selection algorithm (Best-First, Greedy-Stepwise Genetic-search, and Ranker) and nine different models (CFS-Subset-Eval, Gain-Ratio-Attribute-Eval, etc.) to determine the most important factors. The results showed that the genetic-search method using Naive Bayes Tree classification of the feature selection was the most appropriate method for selecting the factors affecting dystocia with the lowest error rate (AMS = 0.011, ARAE = 0.001). The most important factors affecting dystocia were milk production, dam age at parturition, parity, gestational length, corrected milk based on 4% fat, calf sex, calf weight, the season of calving, type of calving, fat-to-protein percentage ratio, and open days. It is expected that by considering these factors, dystocia can be better managed in dairy cattle enterprises.

کلیدواژه‌ها [English]

  • Feature selection algorithm
  • Reproduction
  • Dystocia
  • Dairy cow

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تحقیقات تولیدات دامی
دوره 10، شماره 1
خرداد 1400
صفحه 13-24

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