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1.
为了比较新疆农七师荷斯坦牛不同模型泌乳曲线拟合效果,以该师奶牛场2004年3月~2009年10月间656头中国荷斯坦牛9 426个完整泌乳记录为基础,应用Wood不完全伽玛函数模型、Nelder逆多项式模型、Wilmink模型3个数学模型,对第1胎、第2胎、第3胎和第4胎及所有胎次的泌乳曲线进行了拟合。结果显示,利用Nelder逆多项式模型拟合泌乳曲线,其拟合度(R2)为0.1271～0.9431;利用Wilmink模型拟合泌乳曲线,其拟合度(R2)为0.8944～0.9471;利用Wood模型拟合泌乳曲线,其拟合度(R2)为0.8948～0.9475。结果表明,农七师荷斯坦牛泌乳曲线最佳拟合模型为Wood模型。 相似文献
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《中国畜牧杂志》2020,(8)
为研究新疆哈萨克马的泌乳规律,本实验以新疆富蕴县和布尔津县放牧状态下的哈萨克马(3～5胎次)为研究对象,最终收集得到57匹马3 420条泌乳期记录,分析比较Wood模型、IQP模型、六次多项式回归模型、ML模型4个模型对哈萨克马泌乳曲线的拟合效果。利用SAS 9.4软件对4个模型的参数进行拟合并计算拟合度,然后通过最佳拟合参数列模型方程,将每个时间点代入方程中得到产奶量,最终绘制泌乳曲线,同时计算校正系数。结果显示:4个模型对哈萨克马3个胎次泌乳曲线的拟合效果均较好,Wood模型的拟合度(R2)在0.817 9～0.972 9,IQP模型的拟合度在0.967 6～0.985 5,六次多项式回归模型的拟合度在0.989 1～0.993 0,ML模型的拟合度在0.9651～0.9736,其中六次多项式回归模型的拟合效果优于其他3个模型,为新疆哈萨克马第3、4、5胎次的最佳泌乳曲线模型,拟合度分别为0.993 0、0.989 1、0.991 1,同时利用六次多项式回归模型绘制出新疆哈萨克马的泌乳曲线,并制定出新疆哈萨克马3～5胎次产奶量的校正系数。根据泌乳曲线可得出,哈萨克马产奶高峰出现在泌乳的第60～70天,且产奶量大小依次为第3胎次第4胎次第5胎次。本研究可为高产哈萨克马的培育提供基础依据。 相似文献
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研究旨在比较Wood模型和AS模型对荷斯坦奶牛不同胎次泌乳曲线的拟合效果,探究泌乳期内产奶量的变化规律。选择中原地区两个规模化牧场374头中国荷斯坦牛2006-2018年的产奶量记录,使用NLS语句拟合其泌乳曲线并利用AIC比较拟合效果。结果表明,1、3胎AS模型的AIC值较低,2胎Wood模型的AIC值较低;不同胎次的泌乳曲线二级参数不同:1胎泌乳高峰日晚、高峰产奶量较低,但泌乳持续力强,2至4胎次泌乳高峰日早、高峰产奶量较高、泌乳持续力较弱;不同牧场间泌乳曲线二级参数也有差别。结果提示,AS模型为1、3胎最佳拟合模型,Wood模型为2胎最佳拟合模型;头胎牛和经产牛的泌乳曲线差别较大,在实际生产管理中应分群饲养,根据各自不同的泌乳特点供给泌乳期营养。 相似文献
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5.
不同胎次中国荷斯坦牛泌乳曲线及其拟合的初步研究 总被引：2，自引：0，他引：2
通过对扬州大学实验农牧场2000～2007年度147头中国荷斯坦牛1～5胎次(333个)完整泌乳期记录,分析了各胎次月平均产奶量和累积产奶量的变化规律,用Wood模型对月平均产奶量泌乳曲线,用线性方程、二次方程、三次方程及S型模型对累积产奶量泌乳曲线进行了拟合。结果表明:中国荷斯坦牛第1胎各泌乳月平均产奶量上升慢,泌乳高峰低,下降也慢,而第2～5胎各泌乳月平均产奶量上升快,泌乳高峰高,下降也快;各胎次累积产奶量泌乳曲线基本类似,第1、5胎产量低,2、3、4胎产量高;Wood模型对1～5胎次各泌乳月平均产奶量泌乳曲线拟合度分别为0.152、0.054、0.036、0.001、0.089;线性方程、二次方程、三次方程对不同胎次累计产奶量泌乳曲线拟合度均在0.7以上,S型模型对各胎次累计产奶量泌乳曲线拟合度均大于0.8。 相似文献
6.
研究以50只同期产羔且具有完整的240d泌乳记录的泌乳母羊为研究对象,采集其每天泌乳量,绘制泌乳曲线,利用wood模型对泌乳曲线进行拟合,对其泌乳规律进行了研究。结果表明:西农萨能奶山羊240d平均泌乳量为(544.39±111.56)kg;泌乳高峰出现在泌乳第39天,其泌乳高峰值平均为2.76kg/d;西农萨能奶山羊240d泌乳曲线符合Wood模型,其泌乳曲线可用方程Y=1.6997x0.1885e-0.0048x(R2=0.9297);胎次对参数c值、泌乳峰值、泌乳持续力和总泌乳量有显著影响(P0.05),其中第4胎次总泌乳量最大,为627.2kg,而第2胎次最小,为464.1kg,第4胎次母羊的泌乳峰值平均为3.25kg/d,依次为5胎次及以上的2.86kg/d,3胎次的2.75kg/d及2胎次的2.32kg/d;以第3胎次持续力最好为6.65,且泌乳持续力在第3胎以后有下降的趋势;在机械挤奶条件下,产羔数对泌乳曲线不存在显著影响(P0.05)。综合分析,wood模型拟合的泌乳曲线能客观反映西农萨能奶山羊的泌乳规律。 相似文献
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新疆褐牛产奶量校正系数的制定 总被引：2，自引：0，他引：2
为了制定新疆褐牛产奶量校正系数,收集了新疆褐牛17 962条月测定记录。采用5个数学模型(Wood不完全伽玛函数模型、Nelder逆多项式模型、多项式回归模型(六次)、Ali-Schaeffer模型和Wil mink模型)通过SAS(8.1)软件的非线性过程(NLIN)对泌乳曲线进行拟合。结果表明:5个模型的拟合度R2在0.834 0～0.921 4,确定逆多项式模型为新疆褐牛泌乳曲线最佳拟合模型,绘制了不同胎次的泌乳曲线,制定了一套不同胎次的泌乳天数产奶量校正系数。结果提示,新疆褐牛泌乳高峰日出现在20～50 d,第一胎泌乳高峰值最低,第三胎泌乳高峰日来得最早;随胎次的增加,母牛产奶量不断提高,在第五胎达到最高,以后逐渐下降,平均305 d产奶量为4 445.3kg。 相似文献
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《黑龙江畜牧兽医》2016,(15)
为了从泌乳曲线角度量化不同胎次和产犊季节的差异,试验利用奶牛群体改良(DHI)记录和Wood模型,拟合北京地区代表性牛场的荷斯坦奶牛泌乳曲线,并对泌乳曲线参数进行分析。结果表明:Wood模型拟合群体泌乳曲线拟合度(R2)变化范围为0.948 9~0.976 9,极显著受到胎次影响(P0.01);达到产奶高峰的速度极显著受到胎次影响(P0.01);高峰后产奶量的下降速度极显著受到产犊季节的影响(P0.01);高峰泌乳月和泌乳持续力都极显著受到胎次的影响(P0.01),显著受到产犊季节的影响(P0.05);泌乳潜力和高峰产奶量都极显著受到胎次、产犊季节及其互作的影响(P0.01)。说明泌乳曲线具有群体特异性,增加数据量制作不同产犊季节和胎次的标准泌乳曲线,以量化季节对个体和群体产奶性能的影响、预测产奶量实属必要。 相似文献
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《中国畜牧杂志》2017,(11)
为探索宁夏地区荷斯坦奶牛不同胎次的泌乳特征,本研究用Wood和Cubic函数构建产奶量及乳成分变化规律的模型,以2008—2016年宁夏地区荷斯坦奶牛的DHI数据为基础,构建产奶量(DMY)及乳成分(乳脂率MFP、乳蛋白率MPP、体细胞数SCC、乳糖率MLP和乳干物质率MMP)随泌乳周数(DIW)的变化规律,分析不同胎次间DMY、MFP、MPP、MLP和MSP的泌乳曲线的差异性。结果表明:Wood能较好地拟合宁夏地区荷斯坦奶牛1~4胎次的泌乳曲线(R2依次为0.84、0.75、0.47和0.64),Cubic能较好地拟合MPP的曲线(R2依次为0.91、0.68、0.71和0.75)。 相似文献
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11.
LIU Li-yuan ZANG Chang-jiang ZHOU Jing-hang CHEN Bao-ping GAO Pan HUANG Xi-xia ZHONG Hai-jiao 《中国畜牧兽医》2015,42(10):2707-2713
In this study,the statistical analysis data of 185 340 Holstein dairy cows daily yield records were collected from 2011 to 2014 years in Changji area of Xinjiang,five kinds of models (Wood,IQP,Wilmink,ML,AS models) were used for the first,second,third,fourth and all parities fitting lactation curve.The results showed that the Wood,IQP,Wilmink,ML,AS models fitting precision were within the range from 0.9562 to 0.9828,0.9467 to 0.9809,0.8671 to 0.9752,0.8752 to 0.9175,0.8775 to 0.9127;Milmink model was the best fitting model for the first parity lactation curve,Wood model was the best fitting model for the second,third,and fourth parities lactation curve. 相似文献
12.
高产荷斯坦奶牛泌乳曲线的特征及相关分析 总被引：4，自引：0，他引：4
选取285胎次第三、四胎305d产奶量超过8000kg的安徽荷斯坦牛的泌乳资料，利用Wood模型（Yt=ate^b-ct）进行高产荷斯坦奶牛泌乳曲线特征及相关的分析。结果表明：按照达到泌乳高峰周时间的不同对选取奶牛进行分级，11组Wood模型拟合泌乳曲线的平均拟合精度（R^2）为0.939（幅度为0.899-0.962）。随着达到泌乳高峰周时间的推迟，规模因子a具有逐渐降低的趋势；而产奶量上升率b、产奶量下降因子c、泌乳持久力表现与a相反的变化趋势。在相关分析中，MY（实际产奶量）与EMY（估计产奶量）、PY（高峰月产奶量）为强正相关，r(相关系数）分别为0.999和0.776，与持久力为中等正相关（r=0.379），与a、b、c的r分别是0.905、－0.875、0.731，与PY的相关程度较弱（r=-0.140）。 相似文献
13.
K. Togashi C.Y. Lin Y. Atagi K. Hagiya J. Sato T. Nakanishi 《Livestock Science》2008,114(2-3):194-201
The first three lactation curves of the Japanese Holstein cows were analyzed using a random regression (RR) test-day model with a cubic Legendre polynomial fitted to each of the three parities. The first three eigenvectors of the additive genetic RR covariance matrix explained 77.8, 10.9, and 4.2% of the total variance of the three parities and are associated mainly with the level of milk yield, the linear increase, and the concave curve, respectively. On a lactational basis, as the parity increases, the contribution of the first eigenvector to a lactational variation decreases whereas the contribution of the second eigenvector increases sharply. This means that the impact of the first eigenvector on the level of milk production decreases across parity whereas the effect of the second eigenvector on the shape of the lactation curve increases across parity. The first lactation curve was the most persistent, followed by the second and the third lactation. Persistency and days to reach peak yield decrease as the parity increases (45, 40, and 36 days for the first three parities). Daily heritabilities within lactation were lower for the first parity than for the second or the third parity. The first three lactation curves possess distinctive genetic characteristics that merit consideration when combining the proofs of the first three lactations to select for lifetime production. Within- and between-parity genetic correlations between the constant and the linear RR coefficients were all positive, suggesting that raising the level of milk production in one parity would increase the linear slope in all parities, thus improving persistency. Within- and between-parity genetic correlations between the constant and the quadratic RR coefficients were all negative, implying that increasing the level of production in one parity would deepen and/or widen the concave curve in all parities, thus decreasing persistency. The linear and quadratic RR coefficients were negatively correlated within or between parities and thus have antagonistic effects on persistency. 相似文献
14.
为了解中国荷斯坦牛乳脂率变化规律,本文利用Wood模型对我国南方5个大中型奶牛场2008~2010年1~3胎中国荷斯坦牛33 194条测定日乳脂率进行曲线拟合。结果表明:中国荷斯坦牛乳脂率变化曲线为典型的倒抛物线形,第一胎拟合度最高(0.9820),第三胎最低(0.9789)。二胎牛乳脂率最先达到最低点(第16周),而三胎乳脂率最后达到(第19周)。就最低乳脂率而言,二胎牛最大(3.54%),而三胎牛最小(3.45%)。综合各方面情况得出,Wood模型适用于中国荷斯坦牛乳脂率变化的曲线拟合。 相似文献
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中国荷斯坦牛泌乳曲线拟合研究 总被引：5，自引：1，他引：4
为了解南方大型奶牛场中国荷斯坦牛泌乳曲线及其影响因素,利用5种泌乳曲线模型(Wood模型、Nelder 逆多项式模型、WIL模型、混合对数模型和Ali-Schaeffer模型)和4种时间间隔方式(天、周、旬和泌乳月),对海丰奶牛场2009-2010年度980头第1～5胎具有完整泌乳期的中国荷斯坦牛296 895次日产奶量记录进行泌乳曲线拟合,并进一步分析不同模型、时间间隔和胎次3个因素对泌乳曲线拟合度及其参数的影响.结果表明,5种模型泌乳曲线拟合度变化范围为0.839 7～0.954 1,不同模型和胎次极显著影响泌乳曲线拟合度(P＜0.01),时间间隔对泌乳曲线拟合度无显著影响(P＞0.05).Ali-Schaeffer模型拟合度最高,Nelder逆多项式模型拟合度最低;不论哪种泌乳曲线模型,第一胎拟合度均显著高于第三胎.不同模型、时间间隔和胎次均极显著影响参数a值(P＜0.01),模型极显著影响参数b值(P＜0.01),时间间隔显著影响参数b值(P＜0.05).模型和胎次均极显著影响高峰产奶量和产奶高峰日(P＜0.01).综合各方面情况,确定Ali-Schaeffer模型为适合于海丰奶牛场奶牛的最佳泌乳曲线模型. 相似文献
16.
Relationship between antibodies against Mycobacterium avium subsp. paratuberculosis in milk and shape of lactation curves 总被引：1，自引：0，他引：1
To analyze how infection with Mycobacterium avium subsp. paratuberculosis (MAP) affects the shape of lactation curves, a three-level hierarchical test-day model was set up with fat-corrected test-day milk yield (FCTM) as response. Milk samples from 6955 cows in 108 Danish dairy herds were tested with ELISA to detect antibodies against MAP. Optical densities (ODs) recorded on a continuous scale were standardized according to parity and stage of lactation. In addition to standardized ODs (stOD), seven fixed covariates, quadratic terms and first-order interactions were included in the model. Cow and cow nested in herd were included as random effects. Cows of first, second and higher parities were analyzed separately. The lactation curves after peak yield were significantly less persistent in young infected cows, where an increase of one stOD unit was associated with a depression of the milk yield per day through day 305 of 3.7 kg FCTM in first parity and 2.7 kg FCTM in second parity. In second-parity cows, the lactation curve also was both depressed through the entire lactation and more steep after 60 days in milk (DIM). In third and older parities, a significant effect of the quadratic term of stOD indicated exponentially increased losses with increased ODs. 相似文献
17.
本研究通过对北京地区1998-2016年28个场区的奶牛生产性能测定（DHI）数据进行分析,旨在比较不同产犊季节对1~3胎奶牛泌乳曲线相关参数的影响。使用Wood模型对1~3胎不同产犊季节群体和个体泌乳曲线进行拟合,并获得相应胎次下不同产犊季节奶牛泌乳曲线参数a、b、c （分别代表泌乳潜力、产奶量上升至顶峰速率、产奶量达到顶峰后下降速率）、泌乳曲线二级参数Per、PY （分别代表泌乳持续力、泌乳峰值）及305 d产奶量（305MY）。群体和个体水平的曲线拟合采用SAS 9.2中NLIN模块进行,采用混合线性模型分析不同产犊季节对各胎次奶牛泌乳曲线参数的影响。结果显示：产犊季节对Wood泌乳曲线的泌乳潜力、达到峰值的上升速率、达到峰值后的下降速率、泌乳峰值及305MY均有显著影响（P<0.05）,对于泌乳持续力没有显著影响（P>0.05）。夏季产犊牛泌乳曲线整体低于其他产犊季节,且胎次越高趋势越明显,1胎牛受到的影响较小;从胎次上分析,头胎牛泌乳持续力极显著高于经产牛（P<0.01）;头胎牛夏季产犊305MY比其他产犊季节的低274.33~490.17 kg,经产牛夏季产犊305MY比其他产犊季节的低440.76~930.68 kg。以上结果提示,北京地区牛场应注重做好经产牛和头胎牛的防暑降温工作,注意调整配种时间,避免夏季产犊牛过多,造成损失。 相似文献
18.
《Livestock Production Science》2004,88(3):251-261
Genetic variation and covariation of liability to clinical mastitis in the course of first lactation in Norwegian Cattle (NRF) were investigated. The data consisted of 36,178 first-lactation cows with 354,506 clinical mastitis (absence=0 vs. presence=1) monthly records. A longitudinal binary data analysis was carried out using Bayesian threshold models and Markov chain Monte Carlo (MCMC) procedures. Liability was related to stage of lactation using random regression functions: the Ali–Schaeffer function (AS), the Wilmink function (W) and Legendre Polynomials of order 2, 3 or 4 (L2, L3, L4). Models were compared using a pseudo Bayes factor and an analysis of residuals. The MCMC scheme for the AS function did not converge after 20,000 iterations, and was therefore excluded from further analysis. The pseudo Bayes factor strongly favored the L4 model. Most posterior means of the residuals fell in the range from −0.2 to 0 when cows were healthy (a residual is negative when mastitis is absent and positive otherwise). The L4 model tended to have smaller residuals than the other three models when cows had mastitis. The posterior means of the herd variance and of the cow-specific variance were 0.0645 and 0.1084, respectively, for the fourth order Legendre polynomial. Heritability of liability to clinical mastitis was from 7% to 13% before calving, and ranged between 3% and 11% from calving to 260 days after calving. Most genetic correlations of liability to clinical mastitis between different days of first-lactation ranged from 0.4 to 0.7. 相似文献