A New Variational Study for Two-Site Holstein Model

A variational approach is developed to study the groundstate (GS) of the two-site Holstein model. By the extended coherent state, where the more phonon correlations are easily incorporated, we can get the very accurate ground state energy for all electron-phonon coupling range in typical values of hopping integral t = 0.5, 1.1, and 2.1 (in units of phonon frequency ωo ), which covers the crossover region from antiadiabatic limit to the adiabatic limit. Within a very wide t range [0, 2.7], the exact results for the GS energy are obtained with the twelfth (fourteenth) order corrections to the zeroth order wave function. Moreover, the present approach is more concise than any other analytical ones in this field, and hopefully can be easily generalized to many other Holstein models.

Analytic Study on Some Properties of the Holstein Model

A new ansatz is presentedfor analytic study of the properties of the Holstein model. New analytic resultsfor the polaronic band structure, ground state energy, phonon distribution, hopping probability of electron, and effectivemasses, of the Holstein molecular crystal model, are given in one dimension. All the analytic results obtained are inaccord with the numerical results completed recently and valid both in the adiabatic and nonadiabatic regimes, andaccurate enough in the region of validity.

Extended Holstein polaron model for charge transfer in dry DNA

The variational method is applied to the study of charge transfer in dry DNA by using an extended Holstein small polaron model in two cases： the site-dependent flnite-chain discrete case and the site-independent continuous one. The treatments in the two cases are proven to be consistent in theory and calculation. Discrete and continuous treatments of Holstein model both can yield a nonlinear equation to describe the charge migration in an actual long-range DNA chain. Our theoretical results of binding energy Eb, probability amplitude of charge carrier Ф and the relation between energy and charge-lattice coupling strength are in accordance with the available experimental results and recent theoretical calculations.

Variation Regulation and Models of Raw Milk Composition of Chinese Holstein Cattle in Tianjin

Based on raw milk DHI data of Chinese Holstein cattle in northern China,milk composition (milk protein percentage and milk fat percentage) of lactating cow is grouped into parity 1 to 4. After preprocessing original data,6114 data records of milk protein percentage and 5871 data records of milk fat percentage were obtained. This study discusses effects of natural months,lactation parity and their interaction on changes of milk protein percentage and milk fat percentage,and the model is established using GLM procedure of SAS software. At last,results are as follows: (i) Duncan multiple comparison of natural months,regardless of parity (only parity 1 to 4) ,indicates that milk composition takes on significant difference between different months (P < 0. 05) . And milk protein percentage reaches highest in September (3. 187%), drops to the lowest in July (3. 016%); the milk fat percentage reaches highest in February (4. 137%),and drops to the lowest in July (3.845%) . (ii) Duncan multiple comparison of different parity,regardless months (January to December) ,shows that milk composition of different parity also takes on significant difference (P < 0. 05) although the difference between parities are not significant; milk protein percentage reaches highest in the 2nd parity (3. 114%)and drops to the lowest in the 4th parity (3. 066%); milk fat percentage reaches highest in the 2nd and 3rd parity (3. 983% and 3. 973%),and drops to the lowest in the 4th parity (3. 923%). (iii) Using Wood model,the relational expression between milk protein percentage (MPP,%)and milk fat percentage (MFP,%)of different parity and natural month,i. e. MPP = 3. 094x - 0. 046 4 × e 0. 011 7x and MFP = 4. 211 6x - 0. 034 4 × e 0. 027 6x (x stands for month) . According to the above results,it is concluded that natural months,lactation parity and their interaction significantly influence milk protein percentage and milk fat percentage (P < 0. 001) ,and milk protein percentage and milk fat percentage take on Wood model change characteristics with natural months respectively. This study is intended to explore change regulation of milk composition,and to provide decision reference for properly regulating feeding management and nutrition supply of cattle,and thereby guaranteeing the quality of raw milk in certain month reach sales standard.

Milk Yield of Holstein Cows Induced into Lactation Twice Consecutively and Lactation Curve Models Fitted to Artificial Lactations

Nineteen multiparous barren Holstein cows were subjected to an induction of lactation protocol for 21 d administering estradiol cypionate （2 mg kg-1 of body weight （BW） d-1, on day 1 to 14）, progesterone （0.10 mg kg-1 of BW, on day 1 to 7）, lfumethasone （0.03 mg kg-1 of BW, on day 18 to 20） and recombinant bovine somatotropin （rbST;500 mg per cow, on day 1, 6, 16 and 21）. At the end of lactation and with a minimum of a 2-mon dry period, the same cows were again hormonally induced into lactation. Cows in both lactations were not artiifcially inseminated, they were milked 3 times daily and received rbST throughout lactation. Mean accumulated milk yield at 305 d in milk （DIM） did not differ between the ifrst and second induced lactations （（9 710 ＆#177;1 728） vs. （9 309＆#177;2 150） kg;mean＆#177;SD）. Total milk yield （（12 707＆#177;3 406） vs. （12 306＆#177;4 218） kg;mean＆#177;SD） and lactation length （（405＆#177;100） vs. （410＆#177;91） d;mean＆#177;SD） were not different between the ifrst and second induced lactations. In a second study, 15 empirical models including exponential, power law, yield-density, sigmoidal and miscellaneous models were compared for their suitability by modeling 12-mon （n=334）, 18-mon （n=164） and 29-mon （n=22） lactation cycles of Holsteins cows induced into lactation and treated with rbST throughout the lactation. Hoerl （Y=ab1/xxc）, Wood （Y=axb exp（cx）） and Dhanoa （Y=ax（bc）exp（cx）） models were equally suitable to describe 12-mon lactations. An exponential model with ifve parameters （Y=exp（a＋bx＋cd2＋e/x）） showed the best ift for milk yield for 18-mon lactations. The rational model （Y=a＋bx/1＋cx＋dx2） was found to produce the closest ift for 29-mon lactations. It was concluded that, with the protocol used in the present study, multiparous cows respond favorably to a second cycle of induced lactation, with milk yield similar to that experienced during the ifrst cycle. Thus, dairy producers might be able to lengthen the productive life of infertile high producing cows with a renewal of artiifcial lactation, which would imply an overall reduction in voluntary culling of cows. Also, various equations used to describe the lactation curves demonstrated the potential for iftting monthly milk records of Holstein cows with prolonged lactations and induced hormonally into lactation.

Use of Random Regression Test-Day Model to Estimate Genetic Parameters of Milk Yield in Holstein Cows

(Co) variance components and genetic parameters were estimated for milk yield of Iranian Holstein cows. A total number of 68,945 milk test-day records of first, second and third lactations of 8515 animals from 100 sires and 7743 dams originated from 34 herds collected during 2007 to 2009 by Iranian animal breeding center were used. The ASReml computer program was used to analyze the milk test-day records using the random regression procedure. Herd test date (HTD), milking times per day (milking frequency), number of lactations, year of birth, year of calving, age of animal at calving and days in milk (DIM) considered as fixed effects and additive genetic effects and animal permanent environmental effects were considered as the random effects. Additive genetic variance, animal permanent environment variance, residual variance, phenotypic variance, heritability and repeatability were estimated during different months of lactation between 5.7 - 19.6, 15.3 - 27.1, 31.4 - 17.2, 45.8 - 64.83, 0.1 - 0.32 and 0.4 - 0.6, respectively. Genetic correlation and phenotypic correlation were also estimated between months of lactation in range of -0.35 - 0.98 and 0.03 - 0.67, respectively. Genetic correlation and phenotypic correlation both showed the same changing pattern and they decreased as the interval between months of lactation increased.

Holstein模型的非波矢确定态稳定传播解

论文通过引入含时相干态形式波函数 ,对Holstein模型的非波矢确定态的稳定行波解做了详细的研究 .首先在紧束缚近似下 ,通过数值计算 ,给出了具有普遍意义的稳定传播解 ,即一种有着复杂结构的准周期波 ;同时在低激发态条件下 ,得到系统的解析解 ,并可看到数值解与解析解相吻合 ;最后计算了系统能量的无损耗传播过程 ,即系统的能量密度随群速变化的情况 .这些结果对进一步用Holstein模型研究其他领域传能问题有一定的指导意义 .

利用量子代数SU(1,1)_(q,s)的 Holstein-Primakoff实现讨论双参数变形Jaynes-Cummings模型

本文利用量子代数 SU(1,1)_(q,s)的 Holstein-Primakoff 实现讨论了双参数变形Jaynes-Cummings 模型,并给出了布居数反转的时间演化表达式.

Genetic parameters for somatic cell score and production traits in the fi rst three lactations of Chinese Holstein cows

The objectives of this study were to estimate genetic parameters of lactation average somatic cell scores （LSCS） and examine genetic associations between LSCS and production traits in the first three lactations of Chinese Holstein cows using single-parity multi-trait animal model and multi-trait repeatability animal model. There were totally 273605 lactation records of Chinese Holstein cows with first calving from 2001 to 2012. Heritability estimates for LSCS ranged from 0.144 to 0.187. Genetic correlations between LSCS and 305 days milk, protein percentage and fat percentage were -0.079, -0.082 and -0.135, respectively. Phenotypic correlation between LSCS and 305 days milk yield was negative （-0.103 to -0.190）. Genetic correlation between 305 days milk and fat percentage or protein percentage was highly negative. Genetic correlation between milk fat percentage and milk protein percentage was highly favorable. Heritabilities of production traits decreased with increase of parity, whereas heritability of LSCS increased with increase of parity.

奶牛乳房炎风险评估体系在中国南北方奶牛场的验证及应用

【目的】探究奶牛乳房炎风险评估体系在中国南北方奶牛场近年来实际应用的准确性和稳定性,观察该体系是否可以稳定应用于中国荷斯坦牛群奶牛乳房炎的预测。【方法】基于课题组已构建的奶牛乳房炎Logistic回归模型(cow mastitis logistic regression model,CMLM),在北京、河南、浙江6个荷斯坦牛场进行大规模横向、纵向数据验证,以北方地区5个荷斯坦牛场(覆盖北京、河南)以及南方地区1个荷斯坦牛场(浙江)共56985头次泌乳牛的奶牛群体改良(dairy herd improvement,DHI)信息作为验证数据,验证奶牛乳房炎风险评估体系的预测能力;利用北方地区2016―2021年27万余条DHI测定记录,检验CMLM在整体不同时间段下的大规模纵向数据验证效果。【结果】CMLM在北京地区荷斯坦牛群的验证数据集中,平均准确率为71.85%,表现较优且稳定;在新加入的河南大群奶牛场的验证数据集中也有较好的实际应用表现,平均准确率为78.67%。CMLM在中国南方小群奶牛场长达180个月的验证数据集中应用表现稳定,平均准确率为77.63%。CMLM在不同时间阶段均具有较高的预测效力,模型的预测价值集中在0.70~0.90之间,可以认为该模型良好。【结论】CMLM体系在中国南北方荷斯坦牛群中应用表现优异,在大规模横向、纵向数据的验证中也有较高的预测效力,具有较高推广应用价值。

中国荷斯坦奶牛乳尿素氮非营养影响因素及其与泌乳性能的相关性分析

本试验旨在揭示中国荷斯坦奶牛乳尿素氮(MUN)浓度非营养影响因素的变化规律及其与泌乳性能的关系,探究非营养因素影响MUN浓度的内在机制。以北京、河北等地的17家奶牛场共24 508头泌乳奶牛的生产性能测定(DHI)报告为研究材料,利用固定模型分析牛场效应、胎次效应、产犊季节、泌乳天数、泌乳季节、产奶量、乳脂率、乳蛋白率、乳糖率和体细胞评分对MUN浓度的影响,并按高(16~27 mg/dL)、正常(10~16 mg/dL)和低(0~16 mg/dL)对MUN浓度进行分组,通过显著性和相关性等多种方法分析非营养影响因素的规律及MUN对泌乳性能的影响。结果表明:1)牛场效应、泌乳季节和泌乳天数是影响MUN浓度的重要非营养影响因素;2)MUN浓度在群体水平上与乳脂率呈极显著正相关(r=0.813,P<0.01),与体细胞评分呈极显著负相关(r=-0.441,P<0.01),且MUN浓度在夏季最低、冬季最高;3)相同乳脂率数据集分析表明,泌乳季节、体细胞评分与MUN浓度并无相关性(r<0.100);4) MUN浓度的变化极显著影响乳蛋白率、乳脂率、校正乳含量及脂蛋比(P<0.01)。综上所述,非营养因素的波动导致了MUN浓度的规律性变化,且泌乳季节、体细胞评分非营养因素通过影响乳脂率进而导致MUN浓度变化,关于乳脂率与MUN浓度的变化机理有待进一步研究。

泌乳期中国荷斯坦牛转化孕酮浓度的影响因素分析及其表型预测

【目的】本研究基于试验测定的中国荷斯坦牛血液和乳汁中的孕酮浓度表型,探究了影响中国荷斯坦牛体内孕酮分泌的环境因素、孕酮浓度的变化趋势、孕酮浓度与乳成分的关联程度以及血乳中孕酮浓度的预测方法。【方法】试验于2021年8月在北京、山东两个牧场采集不同胎次、泌乳阶段和妊娠状态的中国荷斯坦泌乳牛的奶样、尾根血样,测定孕酮浓度,最终获得402条乳汁孕酮浓度和298条血液孕酮浓度表型用于数据分析。对孕酮浓度进行数据转化使其近似服从正态分布后,采用固定效应模型探究胎次、泌乳阶段、妊娠状态、牧场等固定效应对奶牛孕酮表型的影响,运用R语言cor函数计算孕酮与各乳成分间的关联,并利用偏最小二乘法和个体及乳成分信息对孕酮浓度进行预测,以建立孕酮浓度表型高通量获取手段。【结果】妊娠状态对转化乳汁孕酮浓度存在极显著影响(P<0.01),胎次、场效应对转化乳汁孕酮浓度均有显著影响(P<0.05),而转化血液孕酮浓度只受到妊娠状态影响(P<0.01);全乳固体、乳脂率、乳蛋白率、脂蛋比与转化乳血孕酮浓度均存在显著或极显著的正相关关系(r=0.14~0.37,P<0.05;P<0.01);基于本试验数据,乳成分与个体信息对转化乳血孕酮浓度的预测准确性不高(R2=0.030~0.17),但如果增加血液或乳汁的转化孕酮浓度对乳汁或血液的转化孕酮浓度进行预测,预测效果则有大幅提升(R2=0.40)。【结论】影响泌乳期中国荷斯坦牛转化孕酮浓度的因素除妊娠状态外,可能还包括饲养条件与胎次。此外转化孕酮浓度与乳脂率、乳蛋白率等乳成分呈极显著相关。基于乳成分信息与转化孕酮的关系,获得了对中国荷斯坦牛乳血转化孕酮浓度预测的可用策略,为今后牧场的繁殖辅助管理、奶牛育种新性状研发以及孕酮浓度的高通量获取等提供了新思路。

中国荷斯坦牛泌乳曲线拟合研究

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。

运用动物模型BLUP法估计荷斯坦牛育种值及制定总性能指数

【目的】探讨动物模型BLUP法在估计新疆地区荷斯坦牛育种值中的应用,为荷斯坦牛的选种选配计划提供理论依据。【方法】利用新疆呼图壁种牛场牧一场、牧二场及牧三场1996-2010年共15 a荷斯坦牛生产性能记录资料,运用动物模型BLUP法,对荷斯坦牛进行单性状育种值估计。【结果】估计得到公牛产奶量育种值、乳脂率育种值、乳蛋白率育种值排名第一的分别为94166、8466、11100120号;母牛产奶量育种值、乳脂率育种值、乳蛋白率育种值排名第一的分别为120030103、120040007、320030159号;并根据产奶量、乳脂率、乳蛋白率育种值制定了荷斯坦牛总性能指数公式（TPI）。【结论】为使种牛评定更准确,需综合考虑产奶量和乳成分等性状,制定荷斯坦奶牛总性能指数公式。

用随机回归模型估计宁夏地区荷斯坦牛头胎测定日产奶量遗传参数

【目的】通过拟合泌乳曲线对影响宁夏地区荷斯坦牛测定日产奶量的诸多因素进行分析,并采用随机回归测定日模型估计遗传参数,为后续估计乳成分和体细胞数遗传参数及个体育种值估计奠定基础,同时也为制定适合该群体的优化育种方案提供参数。【方法】收集了2009—2013年间,宁夏地区24个牛场38 592头荷斯坦牛原始DHI数据,共包含550 078条测定日产奶量记录。质控标准为:产犊月龄为22—36 mo、泌乳天数为5—305 d及日产奶量为5.9—53.3 kg。质控后,共得到14 320头母牛的127 478条测定日记录(占原始记录的23.14%)。将有表型的母牛至少向上追溯三代(父母、祖父母、外祖父母),得到遗传评估所用的系谱文件,共包含24 272头奶牛。使用Excel 2013计算各测定日的平均产奶量,利用SAS 9.1软件的非线性回归过程(NLIN)结合Wood模型拟合群体水平的泌乳曲线。采用随机回归测定日动物模型,通过DMU 5.2软件对头胎产奶量进行遗传参数估计。随机回归测定日模型中包括了一般固定效应、固定回归项及随机回归项三类效应。研究中使用场-测定日作为固定效应、产犊年季效应作为固定回归项,并将加性遗传效应和永久环境效应作为随机回归项。测定日子模型采用4阶勒项德多项式(Legendre polynomials)。根据宁夏地区气候特点,将产犊季节划分为春(3月11日至5月20日)、夏(5月21日至8月25日)、秋(8月26日至10月15日)和冬(10月16日至3月10日)四季。【结果】宁夏地区荷斯坦牛头胎测定日产奶量群体均值为29.66 kg,在泌乳90 d时达到泌乳高峰,高峰产奶量为31.84 kg。通过不同产犊年份、产犊季节和牧场效应组合下的泌乳曲线拟合效果分析,以上因素通过影响泌乳曲线拟合效果进而影响头胎产奶量。在使用测定日模型估计头胎遗传参数时均应通过子模型拟合考虑其泌乳曲线的差异,在产奶量遗传评估模型中予以考虑。产奶量性状5—305d的遗传力在0.08—0.29之间,305d产奶量的总遗传力为0.16。【结论】通过使用wood模型拟合宁夏地区荷斯坦牛头胎泌乳曲线,优化了适合于该群体的测定日模型。利用修改后的测定日模型,估计了宁夏地区荷斯坦牛测定日产奶量的遗传参数。305 d遗传力(0.16)略低于其他群体的同类文研究结果。在测定日模型评估生产性能记录时,应注意对残差方差的处理并关注构建分子亲缘关系矩阵所需系谱的完整性,以保证遗传评估的可靠性。本研究为日后使用多性状随机回归测定日模型估计泌乳性状遗传参数研究奠定了基础。

不同模型估计中国荷斯坦牛生产寿命遗传参数

旨在估计中国荷斯坦牛生产寿命遗传参数,同时比较不同模型的预测可靠性和稳定性。本研究使用单性状动物模型、单性状公畜模型和多性状动物模型对北京地区29个牧场90049头中国荷斯坦母牛的生产寿命数据进行遗传参数估计,所有模型均考虑了场、出生年季、头胎产犊月龄组的固定效应,个体加性遗传效应(动物模型)或父亲遗传效应(公畜模型)的随机效应和残差效应。结果表明,单性状动物模型和单性状公畜模型估计的生产寿命遗传力分别为0.052和0.047,多性状动物模型估计的遗传力较为稳定,介于0.057与0.069之间,多性状动物模型的遗传相关在0.779~0.998之间。对于存在大量在群个体(删失记录)的数据,使用基于前三胎数据的多性状动物模型较为合适,模型预测稳定性更高。本研究对中国荷斯坦牛生产寿命进行了遗传评估,为提高牧场效益、实现平衡育种提供了理论基础。

中国北方荷斯坦奶牛乳成分及相关指标的季节性与胎次变化规律研究

为满足对奶牛饲养管理的季节性及胎次调控,探索乳成分及相关指标的变化规律,基于中国北方荷斯坦泌乳奶牛群的DHI测定数据及派生数据,按胎次及自然月份对DHI原始数据进行分组,剔除异常数据后获得包括乳产量(DMP)、乳干物质率(MSP)、乳脂率(MFP)、乳蛋白率(MPP)、乳糖率(MLP)、体细胞数(SCC)、体况评分(BCS)、奶损失量(LMP)及脂肪蛋白比(FPR)等9项指标的完整观察数据6 520套,以自然月份、胎次及两者的互作作为影响上述指标变化的因素,SAS软件GLM过程进行的方差分析表明:自然月份及胎次分别极显著或显著影响9项观察指标(P<0.000 1,或P<0.001,或P<0.05)。但是,两者的互作对MFP、MPP、MSP、SCC及FPR的变化影响不显著(P>0.05),对DMP影响极显著(P<0.000 1),对MLP、BCS及LMP影响显著(P<0.05)。进行牛群自然月份下乳成分的Duncan多重比较显示,DMP、MSP、MPP及MFP均在6月份表现最低,依次为23.58kg·d-1,12.35%,3.02%及3.81%。SCC在8月份达到最高(385.3×1 000.mL-1),而LMP在11月份最高(1.12kg·d-1)。FPR在2月份最高(1.32),预示着该月份奶牛在快速动用体脂。进行牛群不同胎次性状指标的多重比较表明,MSP、MPP及MLP到第4胎显著下降(P<0.05),而SCC在第4胎显著上升,LMP也随胎次显著增加(P<0.05),意味着随着胎次增加,乳的品质逐渐下降,乳品的卫生指标随之恶化,LMP在增加。其次,对9项指标的典型相关分析表明,BCS与SCC、LMP呈高度正相关(0.830 6,0.836 0),而SCC与LMP也表现高度相关(0.786 1)。最后,利用Wood模型,建立了不同胎次混合牛群的乳干物质率(MSP)及乳糖率(MLP)与自然月份之间的关系方程(MSP=12.862x-0.031 7*e0.004 59x,MLP=4.982 4x-0.019 6*e0.001 06x,式中x代表月份)。通过数据挖掘获得的乳成分及相关性状在自然月份及不同胎次之间的变化规律及模型,为准确调控牛群的饲养管理和营养供给提供了决策依据。

动物模型在荷斯坦牛遗传评定上的应用

本研究应用动物模型ＢＬＵＰ法在微机上评定了北京地区１９６５～１９９２年间出生的荷斯坦牛４１０８０头，建立了一套荷斯坦牛的动物模型评定系统。迭代求解采用间接解法，在阅读数据文件时进行。对于管理组、公牛与牛场互作、永久环境效应，采用Ｇａｕｓｓ—Ｓｅｉｄｅｌ迭代法，对于动物个体和遗传组效应，采用不完全的Ｊａｃｏｂｉ迭代法。提供预期传递力、父母传递力均数、预期生产力、表型均值等有用的遗传和生产信息。在配备了微机的农场或畜群不大的地区，移植本研究成果相当方便。

中国北方荷斯坦奶牛乳产量及乳成分变化的普适模型构建

为探索中国荷斯坦奶牛不同胎次的泌乳特性,构建乳产量及乳成分的变化规律模型。以中国北方天津市第一奶牛良种场(2008-2010年度1~3胎)荷斯坦奶牛的DHI成套原始数据(其中:1胎奶牛DHI数据11 901套,2胎奶牛DHI数据13 474套,3胎奶牛DHI数据13 215套)为基础,利用Wood模型构建乳产量(DMY)及乳成分率(乳脂率MFP、乳蛋白率MPP、乳糖率MLP及乳干物质率MSP)随泌乳天数(DIM)的变化规律,并分析不同胎次间DMY、MFP、MPP、MLP及MSP的差异性。结果表明,Wood模型极好地拟合了中国荷斯坦奶牛1~3胎次的泌乳曲线,构建的模型具有广泛适应性。通过模型模拟参数a、b及c揭示的泌乳特性参数,如高峰日tm、高峰日产量ym及泌乳持续力等,较好地反映我国泌乳奶牛在2、3胎次高峰后泌乳持续力下降过快,影响了泌乳周期的总产乳量。而乳成分的模型揭示了2胎奶牛的平均乳脂率(3.93%)最高,1胎(3.83%)次之,3胎(3.69%)最低;2胎奶牛的平均乳蛋白率(3.24%)最高,3胎(3.18%)次之,1胎(3.10%)最低;随着胎次的增加,平均乳糖率逐渐下降(1胎4.87%,2胎4.84%,3胎4.75%);2胎奶牛的平均乳干物质率(12.54%)最高,3胎(12.52%)次之,1胎(12.50%)最低,因此,虽然3胎牛的乳产量低于2胎的,但乳中干物质含量并没有因为产量下降而提高,不同胎次间乳产量(DMY)及乳成分率(MFP、MPP、MLP及MSP)均差异显著(P<0.05)。此外,Wood模型对DMY拟合最好,MPP及MSP次之,而对MFP及MLP拟合不佳。综合乳产量及乳成分在不同胎次的变化规律,模型奶牛场2胎牛的泌乳生产,无论是产乳量,还是生乳品质均是最佳的,头胎牛次之,而3胎次牛的泌乳生产不仅在数量上下降,而且其内在品质,如MFP、MPP及MLP在305d泌乳周期内的均值均显著下降。因此,加强3胎及3胎后奶牛的饲养管理与养分供给,维护其健康并继续发挥其泌乳潜力是我国奶牛场应当重视的问题。

高产荷斯坦奶牛泌乳曲线的特征及相关分析

选取 2 85胎次第三、四胎 30 5 d产奶量超过 80 0 0 kg的安徽荷斯坦牛的泌乳资料 ,利用Wood模型 ( Yt=atb-cte )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组 ,1 1组 Wood模型拟合泌乳曲线的平均拟合精度 ( R2 )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的相关程度较弱 ;持久力与 MY、EMY均为中等正相关 ,r分别为 0 .379及 0 .382 ,与 b、a、c的 r分别是 0 .90 5、- 0 .875、0 .731 ,与 PY的相关程度较弱 ( r =- 0 .1 40 )。