استفاده از رگرسیون کوآنتایل در بررسی برخی خصوصیات منحنی شیردهی گاوهای شیری ایران

نوع مقاله : مقاله پژوهشی

نویسندگان

1 بخش علوم دام، دانشکده کشاورزی، دانشگاه بیرجند

2 مؤسسه تحقیقات علوم دامی، سازمان تحقیقات، آموزش و ترویج کشاورزی

چکیده

هدف از پژوهش کنونی، بررسی ویژگی‌های  منحنی شیردهی گاوهای شیری ایران با استفاده از رگرسیون کوآنتایل (چندکی) بود. داده­های مورد استفاده شامل 15647867 رکورد روز آزمون شیر بود که از 984690 رأس گاو در 579 گله موجود در 26 استان کشور گردآوری شدند. ابتدا، رکوردهای روز آزمون شیر در ترکیب­های مختلف نوبت زایش–فصل زایش (و مشتمل بر 20 ترکیب) با استفاده از یک مدل خطی تجزیه و تحلیل شدند. سپس، در هر یک از ترکیبات مزبور، میانگین حداقل مربعات رکوردهای روز آزمون شیر در فاصله­ روزهای 4 تا 305 شیردهی، در تابع خطی شده گامای وود و با روش رگرسیون کوآنتایل، مورد استفاده قرار گرفتند. نتایج نشان داد با بالا رفتن چندک­های رکوردهای روز آزمون شیر، مقدار تولید شیر در اوج شیردهی، افزایش می­یابد. زمان رسیدن به اوج شیردهی و میزان تداوم شیردهی در چندک­های پایینی، بزرگ­تر از چندک­های بالایی رکوردهای روز آزمون شیر بودند. در تمامی چندک­ها، کمترین و بیشترین میانگین زمان رسیدن به اوج شیردهی (92/50 و 36/93 روز) و میزان تداوم شیردهی (64/6 و 37/7) به­ترتیب مربوط به گاوهایی بود که در پاییز زایش داشتند و در دوره­های شیردهی سوم یا اول بودند (05/0P<). در رابطه با مقدار تولید شیر در اوج شیردهی، گاوهای زایمان کرده در بهار که دوره­ اول شیردهی را شروع کرده بودند، کمترین میانگین (84/31 کیلوگرم) و گاوهای زایمان کرده در پاییز که دوره­ چهارم شیردهی را شروع کرده بودند، بیشترین میانگین (43/40 کیلوگرم) را دارا بودند (05/0P<). با توجه به نتایج تحقیق حاضر، چنان­چه قرار باشد در امر ارزیابی ژنتیکی گاوهای شیری ایران برای صفت تولید شیر از اطلاعات دوره­های مختلف شیردهی استفاده شود، ضروری خواهد بود تا تغییرات یاد شده در صفات شیردهی، مدنظر قرار گیرند، به­ویژه هنگامی که از مدل­های روز آزمون جهت تجزیه ژنتیکی منحنی شیردهی استفاده می­ شود.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

The use of quantile regression to evaluate some lactation curve characteristics of Iranian dairy cows

نویسندگان [English]

  • Z. Hesami Zostami 1
  • S. H. Farhangfar 1
  • M. A. Abbasi 2
  • H. Naeemipour Younesi 1
1 Animal Science Department, Agriculture Faculty, University of Birjand, Birjand, Iran
2 Animal Science Research Institute of IRAN (ASRI), Agricultural Research, Education & Extension Organization (AREEO), Karaj, Iran
چکیده [English]

Introduction: Over recent decades, numerous mathematical models have been developed to represent the lactation curve of dairy animals. These models are categorized into parametric and non-parametric types, with the three-parameter Wood's gamma incomplete function being extensively utilized for dairy cows. By using the parameters from Wood's model, key lactation characteristics such as peak time, peak yield, and persistency can be determined. These features are considered economic traits, suitable for genetic selection. Previous studies have primarily focused on employing mathematical models to calculate these characteristics based on the average of test day milk records. However, they can also be computed for individual quantiles of test day milk records (TDMR). To our knowledge, no research has yet explored the use of quantile regression for modeling the lactation curve of Iranian dairy cows. Therefore, the primary objective of this study was to assess certain lactation curve characteristics of Iranian dairy cows using the quantile regression technique.
Materials and methods: The data for this study were sourced from the Animal Breeding Centre of Iran. Initially, the dataset was merged and refined using SPSS software. The final dataset included TDMR data from 984,690 dairy cows across 579 herds in 26 provinces nationwide. A total of 15,647,867 TDMR records were collected from the first five parities of cows calving between 1995 and 2021. The TDMR was initially analyzed using a fixed linear model tailored to 20 different combinations of parity and calving season. For each combination, the least squares means of TDMR, measured from 4 to 305 days in milk, were applied to Wood’s incomplete gamma function (y=atbe-ct) in a quantile-based approach. This parametric three-parameter model (a, b, c) is extensively used to describe lactation curves. The linearized form of Wood’s model was fitted to these means using the Quantreg procedure in SAS software, estimating parameters across quantiles from 5 to 95 in increments of 5. Based on these parameters, lactation characteristics such as peak time, peak yield, and persistency were calculated across all parity-calving season combinations. Statistical comparisons of the combination means were conducted using SPSS software.
Results and discussion: The results of this research indicate that peak time, peak yield, and the persistency of the lactation curve in Iranian dairy cows vary across different quantiles of TDMR, parities, and calving seasons. The findings reveal that peak yield increases with higher TDMR quantiles. Conversely, peak time and persistency are greater in the lower TDMR quantiles compared to the upper ones. Across the TDMR quantiles, the minimum (50.92 days) and maximum (93.36 days) peak times, as well as persistency values (6.64 and 7.37), were observed in cows that calved in autumn and began their first or third lactation period (P<0.05). Regarding peak yield, cows that calved in spring and started their first lactation had a lower mean yield (31.84 kg), while the highest mean yield (40.43 kg) was noted in cows that calved in autumn and began their fourth lactation period (P<0.05). As anticipated, cows in their first parity exhibited greater lactation persistency compared to others. Peak yield was significantly correlated with peak time (-0.9520) and persistency (-0.9516) (P<0.0001), suggesting that cows with lower milk yield at peak time tend to reach their peak later and maintain higher persistency post-peak.
Conclusions: The research findings reveal that the peak time, peak yield, and persistency of the lactation curve in Iranian dairy cows differ across the quantiles of test-day milk records. Specifically, peak time and persistency are higher in the lower quantiles compared to the upper ones. Additionally, these lactation characteristics vary across different parities and calving seasons. Based on these results, it is recommended that these variations be considered when using records from various parities for the genetic evaluation of Iranian dairy cows. This consideration is crucial when employing test-day models for genetic analysis of the lactation curve.

کلیدواژه‌ها [English]

  • Lactation characteristics
  • Milk production
  • Quantile regression
  • Wood function
  • Dairy cow

مراجع

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تحقیقات تولیدات دامی
دوره 15، شماره 2
تیر 1405
صفحه 1-17

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