里岔黑猪和巴里杂交猪母猪100kg体重日龄校正方法的比较

doi:10.3864/j.issn.0578-1752.2023.06.013

摘要/Abstract

摘要：

【目的】比较3种达100 kg体重日龄（D_100kg）的校正系数CF的校正效果，为种猪场根据自身实际情况选择合适的D_100kg校正系数CF提供参考。【方法】以里岔黑猪群体及其与巴克夏杂交1代（巴里1代）和2代（巴里2代）共1 344头猪只为研究对象，利用其生长肥育期体重和日龄的数据，以始测体重≥25 kg、终测体重在80—125 kg、过始测点和终测点直线的斜率在群体平均斜率±2个标准差之内等标准进行质控，然后按照下面描述的三种方法估计里岔黑猪、巴里1代、巴里2代以及它们混合群体达100 kg校正系数CF，并评估它们的校正效果。一是回归校正系数（CF_reg）：利用测定期间个体i的体重和日龄数据，拟合体重对日龄的一元回归方程，把其斜率记b₁_i；然后利用它终测点和原点（日龄和体重均为0）作一条直线，把其斜率记为b₂_i；b₁_i/b₂_i的平均数就是CF_reg。二是两点校正系数（CF_2point）：利用个体i初测点和终测点作一条直线，得到斜率b₁_i，斜率b₂_i及CF_2point计算方法与CF_reg计算方法相同。三是单点校正系数（CF_1point）：拟合所有个体的终测体重对终测日龄的一元回归方程，得到斜率b₁；第二条直线斜率与CF_reg相同；b₁ / b₂_i的平均数就是CF_1point。分别将CF_reg、CF_2point和CF_1point代入校正公式，计算出相应的D_100kg._CF_.reg、D_100kg.2point和D_100kg.1point。根据前面拟合的日龄对体重的一元回归，计算个体达100kg的回归日龄（D_100kg.reg），并计算它与其他D_100kg的相关系数和离差。根据相关系数和离差的大小，评估3种方法的优劣。为比较3种校正系数的群体适用性，用某个群体的CF去校正其他3个群体的D_100kg，并根据其校正日龄与该群体D_100kg.reg相关系数的高低来评估其群体适用性的优劣。通过分析终测体重和校正误差之间的关系，探究终测体重对D_100kg的影响。考虑单点校正误差与终测体重之间存在很强的线性关系，利用终测体重对D_100kg.1point进行二次校正，以提高单点校正的准确性。【结果】质控后共1 181头母猪用于后续分析。在同一群体中，CF_reg和CF_2point的值相近，它们极显著大于CF_1point。D_100kg._CF_.reg和D_100kg.2point与D_100kg.reg很接近，相关系数均大于0.98，说明这两种方法的校正效果很好。D_100kg.1point与D_100kg.reg的差异较大，相关系数仅为0.89，校正效果较差。CF_reg和CF_2point的群体适应性很好，均可用于其他群体D_100kg的校正。CF_1point的群体适应性较差，不宜用于其他群体D_100kg的校正。4个群体中，终测体重离目标体重（100 kg）越远，D_100kg._CF_.reg校正误差越大，D_100kg.2point校正误差没有明显的变化。D_100kg.1point的误差与终测体重均存在极显著的负相关，r分别为-0.9812、-0.9627、-0.9786和-0.9352。经过二次校正后，CF_1point校正效果有显著提升，但与CF_reg校正效果仍有较大差距，优先选择CF_reg。【结论】CF_reg和CF_2point的校正效果和群体适应性都很好，可用于生产实践。单点校正系数（CF_1point）的校正效果不理想，不宜用于生产实践。在校正D_100kg时，可以根据猪只的数据量，采用合适的方法，以提高估计准确性，降低估计误差。

关键词: 里岔黑猪, 达100 kg体重日龄, 校正系数CF, 回归日龄

Abstract:

【Objective】 The aims of this study were to compare the powers of three correction coefficients for days to 100 kg (D_100kg), so as to provide the reference for pig breeding farms to select the appropriate correction coefficient for D_100kg according to the data they have. 【Method】 A total of 1 344 pigs were used in this study, including Licha black pig, F₁ (BL₁) and F₂ (BL₂) from its intercross with Berkshire boars. Body weight and age in days for each pig were recorded everyday during its growth and fattening period. The data were qualified according to following criteria: the start body weight ≥25kg, the final body weight among 80 - 125 kg, the slope of the regression equation of body weight to age in days within±2 standard deviations of its average and so on. Three methods described as following were used to estimate the correction coefficient of the days to 100 kg (CF) into Licha Black pig, BL₁, BL₂ and their mixed population. First one was the regressive correction coefficient (CF_reg): b₁_i was the slope of the simple regression equation of body weight to age in days for the ith individual, and b₂_i was the slop of the straight line through the testing end point of the ith individual and the origin (age and weight were both 0), then the average of b₁_i/b₂_i in the population was CF_reg. Second one is the two-point correction coefficient (CF_2point): b₁_i was the slope of the straight line through the testing start and end points of the ith individual, and the methods to calculate b₂_i and CF_2point were as same as those of CF_reg. The last one was the single-point correction coefficient (CF_1point): b₁ was the slope of the simple regression equation of body weight to age in days at the testing end point for all pigs, and the methods to calculate b₂_i and CF_1point were as same as those of CF_reg. Put CF_reg, CF_2point and CF_1point into the correction equation, respectively, and got D_100kg._CF_.reg, D_100kg.2point and D_100kg.1point. The simple regression of age in days to body weight was used to calculate the regressive age in days to 100 kg (D_100kg.reg), and the correlation coefficients and deviations between D_100kg.reg and other D_100kg were calculated. The merits and demerits of the three methods were evaluated according to their correlation coefficients and deviations to D_100kg.reg. D_100kg of a population was estimated by using the correction coefficients from another population, and its correlation coefficient with D_100kg.reg of the population was calculated to evaluate whether the correction coefficient estimated from one population could be used in other populations. The relationship between body weight at the end of performance test (BW_end) and correction error was also investigated to explore whether BW_end had an effect on D_100kg. Taking consideration of the strong linear relationship between BW_end and the correction error of CF_1point, BW_end was used to correct D_100kg.1point to improve the correction accuracy of CF_1point. 【Result】 A total of 1 181 sows were used for following analyses after quality control. In the same population, the values of CF_reg and CF_2point were almost the same, and both of which were highly significantly greater than CF_1point. D_100kg._CF_.reg and D_100kg.2point of each pig were very close to its D_100kg.reg, and all of the correlation coefficients among D_100kg._CF_.reg, D_100kg.2point and D_100kg.reg were greater than 0.98, indicating that the correction powers of CF_reg and CF_2point were very good. The difference between D_100kg.1point and D_100kg.reg was large, and their correlation coefficient was 0.89, so the correction power was not very good. CF_reg and CF_2point had good population transplantations, and could be used to correct D_100kg of other populations, while CF_2point had poor population transplantations, and it was unsuitable to correct D_100kg of other populations. With the difference of BW_end to the target body weight increasing, the correction error of D_100kg._CF_.reg was also increasing in the three populations, and the correction error of D_100kg.2point was no significant changing. D_100kg.1point was significant negative correlation with BW_end, the correlation coefficients were -0.9812, -0.9627, -0.9786 and -0.9352 in the four populations, respectively. The correction power of CF_1point has been significantly improved after adjusting with BW_end, but CF_reg was still better than CF_1point, and it was preferred. 【Conclusion】 The correction powers and transplantations of correction coefficients CF_reg and CF_2point were very good, so CF_reg and CF_2point were suitable to be used to correct D_100kg in practice. The correction power of CF_1point was not very good, therefore, CF_1point was unsuitable to be used in practice. According to the datum amount of a pig, its D_100kg was estimated with the appropriate correction coefficient in order to improve the estimation accuracy and reduce the estimation error.

Key words: Licha Black pig, days to 100 kg, correction coefficient CF, regressive days to 100 kg

崔登帅, 熊三亚, 郑浩, 李龙云, 余乃标, 黄智勇, 肖石军, 郭源梅. 里岔黑猪和巴里杂交猪母猪100kg体重日龄校正方法的比较[J]. 中国农业科学, 2023, 56(6): 1177-1188.

CUI DengShuai, XIONG SanYa, ZHENG Hao, LI LongYun, YU NaiBiao, HUANG ZhiYong, XIAO ShiJun, GUO YuanMei. Comparing Methods for Correcting Days to 100 kg of Sows in Licha Black Pig and Its Intercross with Berkshire[J]. Scientia Agricultura Sinica, 2023, 56(6): 1177-1188.

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群体 Population	样本数 n	校正系数 CF	平均数 Mean	标准差 Std.	变异系数 CV (%)	最小值 Min.	最大值 Max.
里岔黑猪 Licha black pig (LC)	175	CF_reg	1.3533	0.1901	14.0474	0.8700	2.0823
		CF_2point	1.3538	0.1812	13.3833	0.8643	1.9703
		CF_1point	0.4963	0.0460	9.2743	0.3956	0.6166
巴里1代 F₁ of Berkshire × Licha black pig (BL1)	593	CF_reg	1.3876	0.1616	11.6464	0.9825	2.0241
		CF_2point	1.3918	0.1620	11.6381	0.9265	2.0839
		CF_1point	0.7265	0.0688	9.4729	0.5605	0.9741
巴里2代 F₂ of Berkshire × Licha black pig (BL2)	413	CF_reg	1.3968	0.1391	9.9553	0.9921	1.9326
		CF_2point	1.4026	0.1326	9.4570	0.9659	1.9422
		CF_1point	0.6784	0.0682	10.0492	0.5353	0.8868
混合群体 Mixed population (MIX)	1181	CF_reg	1.3858	0.1593	11.4973	0.8700	2.0823
		CF_2point	1.3899	0.1562	11.2378	0.8643	2.0839
		CF_1point	0.6756	0.1019	15.0808	0.3956	0.9741

群体 Population	样本数 n	达100kg日龄 D_100kg	平均数 Mean	标准差 Std.	变异系数 CV (%)	最小值 Min.	最大值 Max.
里岔黑猪 Licha black pig (LC)	175	D_100kg.reg	236.97	18.557	7.8309	192.90	285.89
		D_100kg._CF_.reg	236.45	18.247	7.7171	193.61	281.80
		D_100kg.2point	236.01	18.620	7.8898	190.88	280.52
		D_100kg.1point	256.60	38.848	15.1398	152.09	343.30
		D_{100kg.1point.cor}	235.50	17.807	7.5613	191.74	274.30
巴里1代 F₁ of Berkshire × Licha black pig (BL1)	593	D_100kg.reg	209.45	15.633	7.4641	171.11	268.98
		D_100kg._CF_.reg	209.55	15.221	7.2633	174.47	265.18
		D_100kg.2point	208.86	15.289	7.3199	172.38	267.26
		D_100kg.1point	204.27	26.955	13.1958	126.98	279.80
		D_{100kg.1point.cor}	207.70	15.339	7.3853	163.49	259.73
巴里2代 F₂ of Berkshire × Licha black pig (BL2)	413	D_100kg.reg	215.72	17.100	7.9269	171.84	274.46
		D_100kg._CF_.reg	215.69	16.847	7.8111	174.91	274.66
		D_100kg.2point	214.61	16.552	7.7125	174.29	270.97
		D_100kg.1point	207.91	31.558	15.1787	132.78	285.05
		D_{100kg.1point.cor}	213.30	16.761	7.8580	170.84	267.49
混合群体 Mixed population (MIX)	1181	D_100kg.reg	215.72	19.033	8.8230	171.10	285.90
		D_100kg._CF_.reg	215.68	18.635	8.6400	174.50	281.80
		D_100kg.2point	214.99	19.105	8.8865	171.40	286.70
		D_100kg.1point	213.30	35.552	16.6679	127.00	343.30
		D_{100kg.1point.cor}	215.68	20.567	9.5361	172.04	301.92

	D_100kg.reg	D_100kg._CF_.reg	D_100kg.2point	D_100kg.1point	D_{100kg.1point.cor}
D_100kg.reg	1181	0.9925	0.9847	0.8873	0.9349
D_100kg._CF_.reg	<2.2×10^-16	1181	0.9796	0.8886	0.9355
D_100kg.2point	<2.2×10^-16	<2.2×10^-16	1181	0.8995	0.9502
D_100kg.1point	<2.2×10^-16	<2.2×10^-16	<2.2×10^-16	1181	0.8991
D_{100kg.1point.cor}	<2.2×10^-16	<2.2×10^-16	<2.2×10^-16	<2.2×10^-16	1181

来源群体 Original population	校正系数 Correction coefficient	LC	BL₁	BL₂	MIX
里岔黑猪 Licha black pig (LC)	CF_reg	0.9803	0.9718	0.9793	0.9795
	CF_2point	0.9749	0.9718	0.9794	0.9795
	CF_1point	0.7924	0.8169	0.8195	0.8482
巴里1世代 F₁ of Berkshire × Licha black pig (BL₁)	CF_reg	0.9637	0.9911	0.9797	0.9795
	CF_2point	0.9636	0.9786	0.9797	0.9794
	CF_1point	0.9002	0.8800	0.8924	0.9124
巴里2世代 F₂ of Berkshire × Licha black pig (BL₂)	CF_reg	0.9634	0.9715	0.9940	0.9794
	CF_2point	0.9633	0.9714	0.9849	0.9794
	CF_1point	0.8869	0.8763	0.8768	0.9007
混合群体 Mixed population (MIX)	CF_reg	0.9637	0.9716	0.9797	0.9925
	CF_2point	0.9637	0.9716	0.9797	0.9847
	CF_1point	0.8861	0.8754	0.8780	0.8873