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1.
《河南畜牧兽医(综合版)》2002,23(9)
上半年肉类市场盘点猪肉：上半年批发价为每千克８．７８元，比去年同期下降８．２％。从１月份每千克９．３８元逐月下跌至６月份每千克８．４９元，月均跌幅为２．７％。上半年去骨统肉零售均价为每千克１３．８元，比去年同期下降１．２％。２月份价格每公斤１４．３２元，比１月份上涨２％，达到上半年最高水平，而后逐月下跌至６月份每千克１３．４元，月均跌幅１．６％。牛肉：上半年批发均价为每千克１３．５４元，比去年同期上涨４％。２月份价格为每千克１４．１１元，比１月份上涨７．７％，达到上半年最高水平，而后逐月回落至６… 相似文献
2.
内蒙古赤峰地区牛皮蝇生活史观察 总被引：2，自引：0，他引：2
内蒙古赤峰地区阿鲁科尔沁旗和巴林右旗牛体寄生的皮蝇属皮蝇主要为牛皮蝇（Ｈｙｐｏｄｅｒｍａ ｂｏｖｉｓ）和纹皮蝇（Ｈ．ｌｉｎｅａｔｕｍ）２种，其寄生数量以纹皮蝇占绝对优势。调查的茶兰牛和蒙古牛寄生的牛皮蝇蛆其寄生强度为３～１３９只，平均为３１只。牛皮蝇㈩龄幼虫在３月中旬落地率为６．９％，３月下旬为７２．６％，４月上旬４月中旬为９２．０％，５月上旬为９５．８％。牛皮蝇Ⅱ龄幼虫在７～１２月份牛体内检出数 相似文献
3.
郑州地区种鸡场鸡白血病的初步调查 总被引：1，自引：0，他引：1
调查结果表明，被调查的郑州地区８个父母代种鸡场，有５个为鸡白血病感染阳性场。在调查的８个品种种鸡中，检出的５个阳性品种均为进口，种群，应用羽髓琼脂扩散试验和卵清琼脂扩散试验进行对比检测，结果证明；ＦＭＡＧＤＴ检出阳性率为７．６％－２０％；而ＥＡＡＧＤＴ则为６．３％－１６．６％，前者检出的效果高于后者。 相似文献
4.
１华丰树冠开张，呈圆头形。树势中强，每结果母校抽生结果枝近３条，每结果枝平均着苞２．６个，结实率５６％，空苞率１％。总苞椭圆形，柄较长，皮薄。每苞平均含坚果２．９个，一字形开裂。坚果椭圆形，腹面较平，常有１－２条线状波纹，均重７．６ｇ，坚果皮红棕色。 萌芽期４月上旬，展叶期４月中旬，盛花期６月中旬，成熟期９月中旬，落叶期１１月上旬。结果早，丰产稳产。嫁接苗或高接换种后第２年即可结果。３年生幼树株产 １．５ｋｇ。定植 ３年平均株产 ２．６ｋｇ，平均每６６６．７ｍ２产量１８０ｋｇ，较常规品种增产１０倍以… 相似文献
5.
色质联用（GC／MS）研究天祝微孔草草籽油中的脂肪酸 总被引：9，自引：1，他引：8
采用色谱－质谱二联仪研究天祝微孔草草籽油的化学成分。共分离鉴定出１１种化合物，占油样总量的９９．９２％，主要是亚油酸，油酸，α－亚麻酸，顺－１１－二十碳烯酸，软脂酸，γ－亚麻酸，硬脂酸。饱和脂肪酸４种，不饱和脂肪酸７种，含量分别占总量的１３．５４％和８６．４６％。γ－亚麻酸含量为６．３７％，种子含油４３．５％。 相似文献
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7.
WTO框架下中国奶业发展前景研究 总被引：4，自引：1，他引：3
在中国几乎所有农畜产品的生产总量都占据了世界第一、人均占有量都赶上了世界平均水平、实现了长期目标的今天，惟有奶类是个例外：１９９７—１９９９年３年平均生产量７７５．４万吨，仅及同期世界牛奶总产量４７３３３．７万吨的１．６％；１９９９年中国人均占有量６．６５千克，仅及世界平均牛奶消费水平８０．４０千克／人的８．２７％。相应的，中国的奶类是唯一呈净进口的畜产品：１９９７—１９９９年３年年均出口１１．０２万吨，占国内产量的１．４２％；进口８５．９２万吨，相当于国内产量的１１．０８％；净进口７４．９万吨… 相似文献
8.
本文对东北地区月份与种鸭蛋受精率及孵化率的关系进行了研究。结果表明：２、３、４、５月份是种鸭蛋受精率，孵化率最高的月份，平均受精率８７．８２％，孵化率８１．０３％；７、８月份是最差的月份，平均受精率８１．１１％，孵化率６５．９７％。 相似文献
9.
牛冷冻精液品质受许多因素的影响，了解和掌握这些影响因素对饲养好种公牛，生产优质精液，提高种牛站效益十分必要，现将我站多年的采精记录资料整理分析的结果总结如下，供同行参考。 １、环境温度影响 承德市位于东径１１７°５０’，北纬４０°５８’，海拔３７５米，最高气温达３７℃，最低气温为－１８℃。据资料分析，每年７月份气候炎热，精子活力开始下降，耐冻性差，废弃精液增多，冻精产量减少，８、９、１０三个月减少最严重，３个月的平均产量较年均产量低２９．６％，最多一年下降 ３６％。１０月下旬开始恢复。 １１月份恢复… 相似文献
10.
洪河自然保护区东方白鹳人工招引及种群恢复的研究 总被引：1，自引：0，他引：1
笔者于１９９２年２月－６月，１９９５年２月－６月在洪河自然保护区进行了东方白鹤数量调查，人工招引及种群恢复研究。目前保护区内仅余一天然巢。两年共建人工巢１６个，已被利用６巢，利用率为３７．５％。同时将建立濒危鸟类种群繁殖、恢复基地，恢复、扩大野生种群。 相似文献
11.
S. Amirpour Haredasht C. J. Taylor P. Maes W. W. Verstraeten J. Clement M. Barrios K. Lagrou M. Van Ranst P. Coppin D. Berckmans J.‐M. Aerts 《Zoonoses and public health》2013,60(7):461-477
Wildlife‐originated zoonotic diseases in general are a major contributor to emerging infectious diseases. Hantaviruses more specifically cause thousands of human disease cases annually worldwide, while understanding and predicting human hantavirus epidemics pose numerous unsolved challenges. Nephropathia epidemica (NE) is a human infection caused by Puumala virus, which is naturally carried and shed by bank voles (Myodes glareolus). The objective of this study was to develop a method that allows model‐based predicting 3 months ahead of the occurrence of NE epidemics. Two data sets were utilized to develop and test the models. These data sets were concerned with NE cases in Finland and Belgium. In this study, we selected the most relevant inputs from all the available data for use in a dynamic linear regression (DLR) model. The number of NE cases in Finland were modelled using data from 1996 to 2008. The NE cases were predicted based on the time series data of average monthly air temperature (°C) and bank voles’ trapping index using a DLR model. The bank voles’ trapping index data were interpolated using a related dynamic harmonic regression model (DHR). Here, the DLR and DHR models used time‐varying parameters. Both the DHR and DLR models were based on a unified state‐space estimation framework. For the Belgium case, no time series of the bank voles’ population dynamics were available. Several studies, however, have suggested that the population of bank voles is related to the variation in seed production of beech and oak trees in Northern Europe. Therefore, the NE occurrence pattern in Belgium was predicted based on a DLR model by using remotely sensed phenology parameters of broad‐leaved forests, together with the oak and beech seed categories and average monthly air temperature (°C) using data from 2001 to 2009. Our results suggest that even without any knowledge about hantavirus dynamics in the host population, the time variation in NE outbreaks in Finland could be predicted 3 months ahead with a 34% mean relative prediction error (MRPE). This took into account solely the population dynamics of the carrier species (bank voles). The time series analysis also revealed that climate change, as represented by the vegetation index, changes in forest phenology derived from satellite images and directly measured air temperature, may affect the mechanics of NE transmission. NE outbreaks in Belgium were predicted 3 months ahead with a 40% MRPE, based only on the climatological and vegetation data, in this case, without any knowledge of the bank vole’s population dynamics. In this research, we demonstrated that NE outbreaks can be predicted using climate and vegetation data or the bank vole’s population dynamics, by using dynamic data‐based models with time‐varying parameters. Such a predictive modelling approach might be used as a step towards the development of new tools for the prevention of future NE outbreaks. 相似文献
12.
Nasir Moghaddar Daniel J Brown Andrew A Swan Phillip M Gurman Li Li Julius H van der Werf 《Zeitschrift für Tierzüchtung und Züchtungsbiologie》2022,139(1):71-83
The objective of this study was to investigate the accuracy of genomic prediction of body weight and eating quality traits in a numerically small sheep population (Dorper sheep). Prediction was based on a large multi-breed/admixed reference population and using (a) 50k or 500k single nucleotide polymorphism (SNP) genotypes, (b) imputed whole-genome sequencing data (~31 million), (c) selected SNPs from whole genome sequence data and (d) 50k SNP genotypes plus selected SNPs from whole-genome sequence data. Furthermore, the impact of using a breed-adjusted genomic relationship matrix on accuracy of genomic breeding value was assessed. The selection of genetic variants was based on an association study performed on imputed whole-genome sequence data in an independent population, which was chosen either randomly from the base population or according to higher genetic proximity to the target population. Genomic prediction was based on genomic best linear unbiased prediction (GBLUP), and the accuracy of genomic prediction was assessed according to the correlation between genomic breeding value and corrected phenotypes divided by the square root of trait heritability. The accuracy of genomic prediction was between 0.20 and 0.30 across different traits based on common 50k SNP genotypes, which improved on average by 0.06 (absolute value) on average based on using prioritized genetic markers from whole-genome sequence data. Using prioritized genetic markers from a genetically more related GWAS population resulted in slightly higher prediction accuracy (0.02 absolute value) compared to genetic markers derived from a random GWAS population. Using high-density SNP genotypes or imputed whole-genome sequence data in GBLUP showed almost no improvement in genomic prediction accuracy however, accounting for different marker allele frequencies in reference population according to a breed-adjusted GRM resulted to on average 0.024 (absolute value) increase in accuracy of genomic prediction. 相似文献
13.
1. Two different methods, categorised as input-output and single output models, were evaluated for slaughter weight prediction of broiler chickens. The input-output models included linear and non-linear recursive modelling with a time-varying model structure, whereas the output models consisted only of empirical growth equations and several growth curve fitting techniques. 2. The results suggested that a simple linear growth curve fitting method gives the greatest accuracy in a prediction horizon of 4 d or less. Error is minimised to an average of 0.14% when 4 d of past information is used to fit a line to predict the end weight one day ahead. 相似文献
14.
Jorge Hidalgo Daniela Lourenco Shogo Tsuruta Yutaka Masuda Vivian Breen Rachel Hawken Matias Bermann Ignacy Misztal 《Journal of animal science》2021,99(9)
Accuracy of genomic predictions is an important component of the selection response. The objectives of this research were: 1) to investigate trends for prediction accuracies over time in a broiler population of accumulated phenotypes, genotypes, and pedigrees and 2) to test if data from distant generations are useful to maintain prediction accuracies in selection candidates. The data contained 820K phenotypes for a growth trait (GT), 200K for two feed efficiency traits (FE1 and FE2), and 42K for a carcass yield trait (CY). The pedigree included 1,252,619 birds hatched over 7 years, of which 154,318 from the last 4 years were genotyped. Training populations were constructed adding 1 year of data sequentially, persistency of accuracy over time was evaluated using predictions from birds hatched in the three generations following or in the years after the training populations. In the first generation, before genotypes became available for the training populations (first 3 years of data), accuracies remained almost stable with successive additions of phenotypes and pedigree to the accumulated dataset. The inclusion of 1 year of genotypes in addition to 4 years of phenotypes and pedigree in the training population led to increases in accuracy of 54% for GT, 76% for FE1, 110% for CY, and 38% for FE2; on average, 74% of the increase was due to genomics. Prediction accuracies declined faster without than with genomic information in the training populations. When genotypes were unavailable, the average decline in prediction accuracy across traits was 41% from the first to the second generation of validation, and 51% from the second to the third generation of validation. When genotypes were available, the average decline across traits was 14% from the first to the second generation of validation, and 3% from the second to the third generation of validation. Prediction accuracies in the last three generations were the same when the training population included 5 or 2 years of data, and a decrease of ~7% was observed when the training population included only 1 year of data. Training sets including genomic information provided an increase in accuracy and persistence of genomic predictions compared with training sets without genomic data. The two most recent years of pedigree, phenotypic, and genomic data were sufficient to maintain prediction accuracies in selection candidates. Similar conclusions were obtained using validation populations per year. 相似文献
15.
Genomic estimation of additive and dominance effects and impact of accounting for dominance on accuracy of genomic evaluation in sheep populations 
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下载免费PDF全文 N. Moghaddar J. H. J. van der Werf 《Zeitschrift für Tierzüchtung und Züchtungsbiologie》2017,134(6):453-462
The objectives of this study were to estimate the additive and dominance variance component of several weight and ultrasound scanned body composition traits in purebred and combined cross‐bred sheep populations based on single nucleotide polymorphism (SNP) marker genotypes and then to investigate the effect of fitting additive and dominance effects on accuracy of genomic evaluation. Additive and dominance variance components were estimated in a mixed model equation based on “average information restricted maximum likelihood” using additive and dominance (co)variances between animals calculated from 48,599 SNP marker genotypes. Genomic prediction was based on genomic best linear unbiased prediction (GBLUP), and the accuracy of prediction was assessed based on a random 10‐fold cross‐validation. Across different weight and scanned body composition traits, dominance variance ranged from 0.0% to 7.3% of the phenotypic variance in the purebred population and from 7.1% to 19.2% in the combined cross‐bred population. In the combined cross‐bred population, the range of dominance variance decreased to 3.1% and 9.9% after accounting for heterosis effects. Accounting for dominance effects significantly improved the likelihood of the fitting model in the combined cross‐bred population. This study showed a substantial dominance genetic variance for weight and ultrasound scanned body composition traits particularly in cross‐bred population; however, improvement in the accuracy of genomic breeding values was small and statistically not significant. Dominance variance estimates in combined cross‐bred population could be overestimated if heterosis is not fitted in the model. 相似文献
16.
Ralph C. Weichselbaum DVM Daniel A. Feeney DVM MS Carl R. Jessen DVM PhD Carl A. Osborne DVM PhD J. Holte PHD 《Veterinary radiology & ultrasound》2001,42(4):311-319
Research involved 2 databases. One database (occurrence frequency) comprised the age, breed, gender and urocystolith mineral type (pure chemical types only) from 2041 canine patients submitted to the Minnesota Urolith Center. The other database (imaging) comprised the maximum size, surface (rough, smooth, and smooth with blunt tips), shape (faceted, irregular, jackstone, ovoid, and round) and internal architecture (lucent center, random-nonuniform, and uniform) from 434 canine patients imaged in a urinary bladder phantom. The imaging database was a partial subset of the occurrence frequency database. Imaging techniques simulated were survey radiography and double contrast cystography. The databases were compared using multivariate analysis techniques. Equations were developed to use clinically-relevant characteristics (age, breed, gender, maximum size, surface, shape, and internal architecture) to predict urocystolith mineral types. The goal was to assess the accuracy of the various techniques in predicting the urocystolith mineral types. The combination of signalment (age, breed, gender) and simulated survey radiographic findings does not improve mineral type prediction accuracy (average across all mineral types is 69.9%) beyond that achievable with signalment alone (average across all mineral types is 69.8%). However, the combination of signalment and double contrast cystography does improve mineral type prediction accuracy (average across all mineral types is 75.3%). For comparison, mineral type prediction accuracy without signalment from survey radiographs only was 65.7% across all mineral types. The clinical utility of the algorithm is the option to distinguish urocystolith mineral types requiring surgical vs. medical treatment. 相似文献
17.
M. Heidaritabar M.P.L. Calus H‐J. Megens A. Vereijken M.A.M. Groenen J.W.M. Bastiaansen 《Zeitschrift für Tierzüchtung und Züchtungsbiologie》2016,133(3):167-179
There is an increasing interest in using whole‐genome sequence data in genomic selection breeding programmes. Prediction of breeding values is expected to be more accurate when whole‐genome sequence is used, because the causal mutations are assumed to be in the data. We performed genomic prediction for the number of eggs in white layers using imputed whole‐genome resequence data including ~4.6 million SNPs. The prediction accuracies based on sequence data were compared with the accuracies from the 60 K SNP panel. Predictions were based on genomic best linear unbiased prediction (GBLUP) as well as a Bayesian variable selection model (BayesC). Moreover, the prediction accuracy from using different types of variants (synonymous, non‐synonymous and non‐coding SNPs) was evaluated. Genomic prediction using the 60 K SNP panel resulted in a prediction accuracy of 0.74 when GBLUP was applied. With sequence data, there was a small increase (~1%) in prediction accuracy over the 60 K genotypes. With both 60 K SNP panel and sequence data, GBLUP slightly outperformed BayesC in predicting the breeding values. Selection of SNPs more likely to affect the phenotype (i.e. non‐synonymous SNPs) did not improve the accuracy of genomic prediction. The fact that sequence data were based on imputation from a small number of sequenced animals may have limited the potential to improve the prediction accuracy. A small reference population (n = 1004) and possible exclusion of many causal SNPs during quality control can be other possible reasons for limited benefit of sequence data. We expect, however, that the limited improvement is because the 60 K SNP panel was already sufficiently dense to accurately determine the relationships between animals in our data. 相似文献
18.
S. Avendaño J.A. Woolliams & B. Villanueva 《Zeitschrift für Tierzüchtung und Züchtungsbiologie》2005,122(5):302-308
This study describes a general framework for predicting the accuracy of Mendelian sampling terms when truncation selection is applied on best linear unbiased prediction (BLUP) estimated breeding values. A selection index approach is followed. The pseudo‐BLUP index is extended to include terms related to the Mendelian sampling term. Predicted accuracies are compared with those obtained through stochastic computer simulation. Good predictions for the accuracy of the Mendelian sampling term were obtained both at selection time and at convergence of long‐term contributions of selected candidates for a range of heritabilities and population structures. The prediction approach developed provides a key tool for obtaining predictions of genetic response from quadratic optimization that maximizes the rate of genetic progress while restricting the rate of inbreeding. 相似文献
19.
Rohrbach BW Buchanan BR Drake JM Andrews FM Bain FT Byars DT Bernard WV Furr MO Paradis MR Lawler J Giguère S Dunkel B 《Journal of the American Veterinary Medical Association》2006,228(11):1748-1756
OBJECTIVE: To create a mathematical model to assist in early prediction of the probability of discharge in hospitalized foals < or= 7 days old. STUDY DESIGN: Prospective study. ANIMALS: 1,073 foals. PROCEDURES: Medical records from 910 hospitalized foals < or = 7 days old for which outcome was recorded as died or discharged alive were reviewed. Thirty-four variables including historical information, physical examination findings, and laboratory results were examined for association with survival. Variables associated with being discharged alive were entered into a multivariable logistic regression model. Accuracy of the model was validated prospectively on data from 163 foals. RESULTS: Factors in the final model included age group, ability to stand, presence of a suckle reflex, WBC count, serum creatinine concentration, and anion gap. Sensitivity and specificity of the model to predict live discharge were 92% and 74%, respectively, in the retrospective population and 90% and 46%, respectively, in the prospective population. Accuracy of an equine clinician's initial prediction of the foal being discharged alive was 83%, and accuracy of the model's prediction was 81%. Combining the clinician's prediction of probability of live discharge with that of the model significantly increased (median increase, 12%) the accuracy of the prediction for foals that were discharged and nonsignificantly decreased (median decrease, 9%) the accuracy of the predication for nonsurvivors. CONCLUSIONS AND CLINICAL RELEVANCE: Combining the clinician's initial predication of the probability of a foal being discharged alive with that of the model appeared to provide a more precise early estimate of the probability of live discharge for hospitalized foals. 相似文献
20.
P. Ma M.S. Lund X. Ding Q. Zhang G. Su 《Zeitschrift für Tierzüchtung und Züchtungsbiologie》2014,131(6):462-472
This study investigated the effect of including Nordic Holsteins in the reference population on the imputation accuracy and prediction accuracy for Chinese Holsteins. The data used in this study include 85 Chinese Holstein bulls genotyped with both 54K chip and 777K (HD) chip, 2862 Chinese cows genotyped with 54K chip, 510 Nordic Holstein bulls genotyped with HD chip, and 4398 Nordic Holstein bulls genotyped with 54K chip and with deregressed proofs for five milk production traits. Based on these data, the accuracy of imputation from 54K to HD marker data and the accuracy of genomic predictions in Chinese Holstein were assessed. The allele correct rate increased around 2.7 and 1.7% in imputation from the 54K to the HD marker data for Chinese Holstein bulls and cows, respectively, when the Nordic HD‐genotyped bulls were included in the reference data for imputation. However, the prediction accuracy was improved slightly when using the marker data imputed based on the combined HD reference data, compared with using the marker data imputed based on the Chinese HD reference data only. On the other hand, when using the combined reference population including 4398 Nordic Holstein bulls, the accuracy of genomic predictions increased 6.5 percentage points together with a reduction of prediction bias. The HD markers did not outperform the 54K markers in genomic prediction based on the present data. The results indicate that for Chinese Holsteins, it is necessary to genotype more individuals with 54K chip to increase reference population rather than increasing marker density. 相似文献