共查询到19条相似文献，搜索用时 171 毫秒
1.
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
2.
本研究收集宁夏地区1997—2018年63个奶牛场16.9万头荷斯坦牛的生产性能测定数据，从个体和群体水平拟合泌乳曲线，旨在探析我国高产奶牛群的泌乳性能特征及其影响因素。使用WOOD不完全伽马模型对奶牛的个体泌乳曲线进行拟合，并获得模型参数a、b、c以及二级参数泌乳持续力、高峰奶量、高峰日和305 d产奶量，进而采用线性模型分析胎次、产犊季节、初产月龄、出生年份和牧场规模等因素对泌乳曲线参数的影响。结果表明，高峰奶量为42.18±8.66 kg（平均值±标准差，下同），高峰日为86.15±42.88 d,305 d产奶量为10 023.98±2 139.89 kg。胎次、产犊季节、初产月龄、出生年份和牧场规模对宁夏奶牛泌乳曲线参数均有极显著影响。头胎牛产奶量极显著低于经产牛，夏季产犊奶牛的产奶量显著低于其他季节，初产月龄为22～24月龄时产奶量最高，牧场规模低于500头与高于500头奶牛产奶量存在极显著差异，高峰奶量与305 d产奶量随出生年份的增加而增加。这些研究结果为规模化牧场精细化管理和群体遗传改良提供了有用信息。 相似文献
3.
《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
4.
本文应用Wood提出的伽玛曲线公式中关于泌乳期初期的三个参数:高峰周的平均日产奶量(a),产奶量的递增率(b),高峰奶量出现周数(t_(max)),用b/c替代了下降率(c)。并引入系数0.85和校正值E=2.674,来估测305天产奶量。修正的Wood公式是: Ln Yt=Ln0.85+Ln a+b Ln t-ct Yt′=Yt+E 将估测奶量与实际产奶量对比,用相关系数表示,在实际产奶量比较稳定的情况下,估测值与实际值间的r=0.92;在各地生产情况变动较大的情况下,r=0.69。都为强相关。修正的伽玛曲线对实际产奶量有很好的预报特性,对我国西门塔尔牛可利用阶段泌乳资料,扩大母牛的评定头数,提高选择的准确性。 相似文献
5.
《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
6.
用Wood模型拟合南方中国荷斯坦牛产奶量、乳脂率、乳蛋白率和体细胞评分及其效果分析 总被引：1，自引：0，他引：1
旨在了解南方中国荷斯坦牛测定日产奶量、乳脂率、乳蛋白率和体细胞评分(Somatic cell score,SCS)变化趋势,并进行准确预测.利用Wood模型对南方5个大中型奶牛场(2008-2010年1～3胎)中国荷斯坦牛的33 194条测定日产奶量、乳脂率、乳蛋白率和SCS数据进行曲线拟合.结果表明,测定日产奶量为标准泌乳曲线,乳脂率、乳蛋白率和SCS变化与标准泌乳曲线正好相反.Wood模型对乳蛋白率和产奶量变化曲线拟合度最高,各胎次拟合度均为0.99,误差均方也较低;其次为乳脂率,各胎次拟合度均为0.98,而对SCS的拟合度最低,均在0.7以下,同时误差均方也最大.各胎次产奶高峰日出现的时间与乳蛋白率和SCS最低值出现的时间相近,而最低乳脂率出现的时间较晚.一胎牛高峰产奶量相对较低(30.4 kg·d-1),但泌乳后期泌乳持续力及维持低SCS能力较强;二胎和三胎牛高峰产奶量较大,分别为35.9和36.2 kg·d-1,二胎奶牛在泌乳后期同时维持高乳脂率和乳蛋白率的能力较强.Wood模型适合于南方中国荷斯坦牛测定日产奶量、乳脂率、乳蛋白率变化曲线的拟合分析,而不适合于SCS的拟合分析. 相似文献
7.
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
8.
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
9.
本文利用Wood模型对北京市黑白花奶牛的879个泌乳期逐个进行了拟合,拟合过程中采用最小二乘法估计参数a、b、c.并进行了均方差RMS和拟合度R~2的计算。对于不符合正常泌乳曲线的泌乳期进行剔除。得到a,b,c均大于零的732个泌乳期,再进一步剔除R~2<0.30的泌乳期。得到633个正常的泌乳期。且按场队、胎次对参数a、b、c、R~2进行了方差分析。按胎次对参数a.b、c的遗传力及遗传相关等遗传参数进行了计算,旨在找到影响Wood模型拟合奶牛泌乳曲线的诸因素及其遗传学基础,为进一步做好奶牛产奶性能的早期预测,搞好奶牛育种工作提供一定的依据。 相似文献
10.
11.
公牛家系泌乳曲线的研究 总被引：1，自引：1，他引：0
本文根据北京黑白花奶牛２２个公牛家系的女儿泌期资料，利用Ｗｏｏｄ模型估计了各公牛家系的泌乳曲线参数，并且按照家系内女儿的不同胎次，所在牧场和产犊年份分组作了更加深入的研究。所考虑的曲线参数为规模因子ａ。产奶量上升率ｂ和下降率ｃ；次级参数包括３０５天实际产奶量，３０５天估计产奶量，高峰月份，高峰月产奶量和泌乳持久力。结果表明，与低产公牛家系相比，高产公牛家系的泌乳曲线通常具有较高的初始产奶量，参数ａ 相似文献
12.
The objective of this study was to develop a framework describing the milk production curve in sows as affected by parity, method of milk yield (MY) determination, litter size (LS), and litter gain (LG). A database containing data on LS, LG, dietary protein and fat content, MY, and composition measured on more than 1 d during lactation and method for determining MY from peer reviewed publications and individual sow data from 3 studies was constructed. A Bayesian hierarchical model was developed to analyze milk production data. The classical Wood curve was used to model time trends in MY during lactation, and it was re-parameterized expressing the natural logarithm of MY values at d 5, 20, and 30 as functional parameters. The model incorporated random effects of experiment, sow nested within experiment, and fixed effects of LS, LG, parity, and method through the functional parameters of the Wood curve. A second set of models were constructed to analyze milk composition data, including day in milk, LS, dietary protein, and fat contents. Four scenarios with different LG and LS were constructed using the framework to estimate the energy output in milk at different days during lactation. The estimated energy output was compared with energy output values calculated using the 1998 NRC method. Milk yield was underestimated by approximately 20% with the weigh-suckle-weigh technique compared with the deuterium oxide dilution technique (P < 0.001). The mean LG and LS for the dataset were 2.05 kg/d (1.0; 3.3) and 9.5 piglets (5; 14), respectively. The MY was affected by LS on d 5 and 20 (P < 0.001) and by LG on d 20 (P < 0.001) and d 30 (P = 0.004). The mean time to peak lactation was 18.7 d (SD = 1.06) postpartum and mean MY at peak lactation was 9.23 kg (SD = 0.14). The average protein, lactose, and fat content of milk was 5.22 (SD = 0.06), 5.41 (SD = 0.08), and 7.32% (SD = 0.17%), respectively. The NE requirement for lactation increased from d 5 to 20 because of increased MY. Requirements also increased with increasing LG and LS. The framework could be used to predict energy and protein requirements for lactation under different production expectations and can be incorporated into a whole animal model for determination of energy and nutrient requirements for lactating sows, which can optimize sow performance and longevity. 相似文献
13.
Most studies on lactation curves only consider milk yield and describe a standard lactation curve of dairy cows, showing a peak or maximum daily yield occurring between 4 and 8 weeks after calving, followed by a daily decrease in milk yield until the cow is dried off. Wood's model is a widely used lactation curve function. Wood's model was fitted to test-day records of 95,405 lactations of parities lower than 5. Milk traits were milk yield (MY), fat percentage (F%), protein percentage (P%), fat yield (FY) and protein yield (PY), and the lactation curve was individually considered as a cluster of five linked curves. Milk trait and parity influence the goodness of fit of Wood's model. In 19.3% of the lactations, the shape of the MY, FY and PY curves follows the standard lactation curve while F% and P% have the reversed standard shape. The initial phase of lactation with the FY and PY curves contributes to the high variability of shapes. 相似文献
14.
The effect of strain of Holstein-Friesian, feeding system and parity on lactation curves characteristics of spring-calving dairy cows 总被引：1，自引：0，他引：1
The purpose of the present study was to investigate the influence of strain of Holstein-Friesian (HF) cow and feeding system (FS) on the lactation curve characteristics of spring-calving cows. The Wilmink model was used to analyse the lactation curves. The three strains of HF cows compared were high production North American (HP), high durability North American (HD) and high Breeding Worth New Zealand (NZ). The three FS compared were a high milk output from pasture feed system (MP), a high concentrate feed system (HC) and a high stocking rate feed system (HS). A repeated measures model with a factorial arrangement of treatments was used to determine the influence of strain of HF, FS, parity and their interactions on the shape of the lactation curve. The curve was described based on yield at calving, the degree of ascendancy between calving and peak yield, and the persistency after peak yield. Analysis of the residuals indicated a good fit of the Wilmink curve to the data set. Strain of HF, FS, parity and the interaction of strain of HF with FS had significant effects on lactation curve characteristics. In all three FS, the HP strain achieved the highest milk production post-claving and peak yield, with the lowest persistency of lactation. In the HC system, milk production post-claving and at peak yield were higher for all three strains. Offering higher levels of concentrate supplementation to the HP strain on a pasture-based system improved their persistency of lactation. The highest persistency of lactation was achieved with NZ strain. The highest milk production post-claving and at peak and lowest persistency was achieved with third parity cows. The existence of strain by feed system interactions for lactation curve parameters clearly exhibits that the optimum system of production varies with strain of HF. 相似文献
15.
Relationships between daily, morning, evening and peak yield and persistency in Turkish Saanen goats
A matrix of persistency values is given instead of one value of persistency or persistency values based on succeeding test days. Overall, the persistency matrix of morning milk had higher values than the persistency matrix of evening milk. As the distance between the test days increased, the correlations dramatically decreased. The effects of morning milk yield b = 0.23 (P < 0.01) on standard deviation of morning and evening milk yield and on peak the milk yield was higher compared to the evening daily milk yield b = 0.03 (P = 0.05) and the total daily milk yield 0.10 (P < 0.01). Increased persistency means that the lactation curve may be flatter. Since the peak value of morning milk (1597 mL) was lower than evening milk (1799 mL), and morning milk was more persistent than evening milk, morning milk can be said to contribute more to the flatness of the lactation curve. Overall, the morning milk volume (938 mL) was larger than the evening milk volume (835 mL). A 3D plot of peak milk versus morning and evening milk yield indicated that increasing the evening milk yield increases the peak yield while the morning milk yield holds the peak value lower and the curve stable. 相似文献
16.
奶牛泌乳曲线数学模型的遗传分析 总被引：7，自引：3，他引：7
本文采用Wood、改进多项式、回归模型各参数估值及拟合、预报奶量进行了方差分析,遗传力、遗传相关估计及BLUP法育种值估计。方差分析结果表明,产犊季节和胎次对各性状具有较为显著的影响。各遗传相关的估值均较高,这是由环境因素及取样情况所致。实际及估计305天产奶量的遗传力估值较高,Wood模型参数c、改进多项式模型参数d及回归模型参数d、e的遗传力估值也相对较高。各估计、预报奶量及各选定模型参数的BLUP育种值排队序号与实际305天产奶量BLUP育种值排队序号均呈极显著的秩相关(p<0.001).这表明可以用估计和预报奶量及模型参数来评定种公牛的优劣。这对奶牛生产和育种实践具有一定的实践意义。 相似文献
17.
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
18.
Takeshi YAMAZAKI Hisato TAKEDA Akiko NISHIURA Kenji TOGASHI 《Animal Science Journal》2009,80(6):636-643
We examined the relationships between the shape of the first parity lactation curve and udder disease incidence at different stages of lactation in 538 Holstein cows. Data used were first‐parity daily milk yields and treatment records. Each cow was classified according to whether or not it had had udder disease at least once over the whole lactation period or in one of three stages within the lactation period. We then examined the differences in the shapes of the lactation curves between the disease incidence and non‐incidence group in each stage. Cows that had high rates of increase in milk yield and high milk yields in early lactation were predisposed to udder disease afterwards. Cows with high milk production over a long period but with low lactation persistency were predisposed to udder disease after the peak of lactation. There was no difference in total milk yield between incidence and non‐incidence groups in all stages, suggesting that, for a comparable level of lactation, cows without udder diseases have flatter lactation curves. 相似文献
19.
D. Kolbehdari Z. Wang J.R. Grant B. Murdoch A. Prasad Z. Xiu E. Marques P. Stothard & S.S. Moore 《Zeitschrift für Tierzüchtung und Züchtungsbiologie》2009,126(3):216-227
The detection and mapping of genetic markers linked to quantitative trait loci (QTL) can be utilized to enhance genetic improvement of livestock populations. With the completion of the bovine genome sequence assembly, single nucleotide polymorphisms (SNP) assays spanning the whole bovine genome and research work on large scale identification, validation and analysis of genotypic variation in cattle has become possible. The objective of the present study was to perform a whole genome scan to identify and map QTL affecting milk production traits and somatic cell scores using linkage disequilibrium (LD) regression and 1536 SNP markers. Three and 18 SNP were found to be associated with only milk yield (MY) at a genome and chromosome wise significance (p < 0.05) level respectively. Among the 21 significant SNP, 16 were in a region reported to have QTL for MY in other dairy cattle populations and while the rest five were new QTL finding. Four SNP out of 21 are significant for the milk production traits (MY, fat yield, protein yield (PY), and milk contents) in the present study. Six and nine SNP were associated with PY at a genome and chromosome wise significant (p < 0.05) level respectively. Three and 17 SNP were found to be associated with FY at a genome and chromosome wise significant (p < 0.05) level. Five and seven SNP were mapped with somatic cell score at a genome and chromosome wise significant (p < 0.05) level respectively. The results of this study have revealed QTL for MY, PY, protein percentage, FY, fat percentage, somatic cell score and persistency of milk in the Canadian dairy cattle population. The chromosome regions identified in this study should be further investigated to potentially identify the causative mutations underlying the QTL. 相似文献