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Chemical composition,energy and amino acid digestibility in double-low rapeseed meal fed to growing pigs

Journal of Animal Science and Biotechnology 2015年第4期6卷 445-454页

作者： Peili Li Fengli Wang Fei Wu Jinrong Wang Ling Liu Changhua Lai State Key Laboratory of Animal Nutrition College of Animal Science and TechnologyChina Agricultural University College of Bio-engineering Henan University of Technology

Background： The nutritional value of rapeseed meal may be variable due to the variation of its chemical composition. And a precise understandin9 of the nutritional value of an ingredient is beneficial for the accurate diet formulation and reduction of feed costs. This study was conducted to determine the chemical composition, dicjestible energy （DE） and metabolizable enercjy （ME） content, and apparent ileal digestibility （AID） and standardized ileal dicjestibility （SID） of amino acids （AA） for growincj pigs. Thirteen solvent-extracted double-low rapeseed meal （DLIRSM） samples were obtained from the main double-low rapeseed producing areas in China. Methods： The DE and ME contents of the 13 DLRSM samples were measured in cjrowin9 pigs （six pigs per DLRSM sample, average initial body weicjht （BW） =48.3 kg）. The AID and SID of AA of 10 DLRSM samples were determined in 12 crossbred barrows （average initial BW = 35.3 kcj） by using two 6 x 6 Latin square designs. Each Latin square comprised one N-flee diet and 5 DLRSM test diets. Results： The chemical composition of DLRSM varied among samples, and the coefficient of variation was greater than ]0 % for ether extract （EE）, neutral detergent fiber （NDF）, acid detergent fiber （ADF）, calcium （Ca）, and total 91ucosinolates. The AA content of DLRSM varied among samples especially for lysine （Lys） and methionine （Met）. On a dry matter （DM） basis, the apparent total tract digestibility （ATFD） of gross energy （GE）, the DE and ME and the ME：DE ratio of DLRSM averaged 62.39 %, 2862 kcal/k9 and 2723 kcal/kcj, and 94.95 %, respectively. The mean value of S1D of Lys was 70.52 % which varied from 66.54-76.54 %. The SID of crude protein （CP）, Met, and threonine （Thr） averaged 72.81%, 82.41%, and 69.76 %, respectively. Conclusions： There was great variability in chemical composition especially in the concentration of EE, NDF and ADF, but no significant differences in energy content of the DLIRSM samples were observed. In addition, the AID

关键词： Digestible energy Double-low rapeseed meal Growing pigs Ileal digestibility of amino acids,Metabolizable energy

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Predicting corn digestible and metabolizable energy content from its chemical composition in growing pigs

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Journal of Animal Science and Biotechnology 2014年第3期5卷 357-364页

作者： Quanfeng Li Jianjun Zang Dewen Liu Xiangshu Piao Chanqhua Lai Defa Li State Key Laboratory of Animal Nutrition Ministry of Agriculture Feed Industry CentreChina Agricultural University

Background： The nutrient composition of corn is variable. To prevent unforeseen reductions in growth performance, grading and analytical methods are used to minimize nutrient variability between calculated and analyzed values. This experiment was carried out to define the sources of variation in the energy content of corn and to develop a practical method to accurately estimate the digestible energy （DE） and metabolisable energy （ME） content of individual corn samples for growing pigs. Twenty samples were taken from each of five provinces in China （Jilin, Hebei, Shandong, Liaoning, and Henan） to obtain a range of quality. Results： The DE and ME contents of the 100 corn samples were measured in 3.5.3 ±1.92 kg growing pigs （six pigs per corn sample）. Sixty corn samples were used to build the prediction model; the remaining forty samples were used to test the suitability of these models. The chemical composition of each corn sample was determined, and the results were used to establish prediction equations for DE or ME content from chemical characteristics. The mean DE and ME content of the 100 samples were 4,053 and 3,923 kcal/kg （dry matter basis）, respectively. The physical characteristics were determined, as well, and the results indicated that the bulk weight and 1,000-kernel weight were not associated with energy content. The DE and ME values could be accurately predicted from chemical characteristics. The best fit equations were as follows： DE, kcal/kg of DM = 1062.68 ＋（49.72 ×EE）＋（0.54 × GE）＋（9.1 ] x starch）, with R^2 = 0.62, residual standard deviation （RSD） = 48 kcal/kg, and P 〈 0.01; ME, kcal/kg of dry matter basis （DM） = 671.54 ＋（0.89 ×DE） - （5.57 × NDF） - （191.39 ×ash）, with R^2 = 0.87, RSD = 18 kcal/kg, and P〈 0.01. Conclusion： This experiment confirms the large variation in the energy content of corn, describes the factors that influence this variation, and presents equations based on chemical measurements that may be used to predict the DE and ME

关键词： Corn Digestible energy Metabolizable energy Pigs Prediction equation 1

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Effect of variety and drying method on the nutritive value of corn for growing pigs

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Journal of Animal Science and Biotechnology 2014年第4期5卷 454-460页

作者： Quanfeng Li Meng Shi Chuanxin Shi Dewen Liu Xiangshu Piao Defa Li Changhua Lai State Key Laboratory of Animal Nutrition Ministry of Agriculture Feed Industry CentreChina Agricultural University

Background：This experiment was conducted to determine the nutritive value of corn from the north of China for growing *** experiment examined corn variety（LS1,LS2,LS3 and LS4）grown in one location,drying method（sun dried and artificially dried）and different drying *** harvested at 20-25%moisture was dried to about 12%moisture by sun drying and artificially drying at 80,100,or 120℃ in a fluidized bed ***-six barrows（average BW of 33.4 ± 2.7 kg）were housed in individual metabolism crates to facilitate separate collection of feces and urine.A five-day collection period followed a seven-day diet acclimation ***：The results indicated that variety significantly influenced（P〈0.01）the 1,000 kernel weight of corn but not the bulk *** also influenced the available energy content（digestible energy of dry matter,P〈0.01;metabolisable energy of dry matter,P〈0.01）and digestibility of organic matter（P〈0.01）,as well as dry matter（P〈0.01）and gross energy（GE）content（P〈0.02）.The drying method of corn significantly influenced the 1,000 kernel weight（P〈0.01）,bulk weight（P〈0.01）and digestibility of ether extract（EE）（P〈0.01）.No effect of drying temperature on the digestibility of organic matter,dry matter（DM）,crude protein（CP）,neutral detergent fiber（NDF）,acid detergent fiber（ADF）and gross energy was observed,but gelatinization（P〈0.05）and test weight（P〈0.01）decreased with an increase in ***：Variety has a significant impact on the nutritive value of corn for growing pigs,and greater attention needs to be paid to these influences in the assignment of the nutritive value of corn given to growing pigs.

关键词： Corn Digestible energy Drying method Pigs Variety

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The effects of dietary fiber level on nutrient digestibility in growing pigs

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Journal of Animal Science and Biotechnology 2013年第4期4卷 309-315页

作者： Wenjuan Zhang Defa Li Ling Liu Jianjun Zang Qiwu Duan Wenjun Yang Liying Zhang State Key Laboratory of Animal Nutrition China Agricultural University

The objective of this study was to investigate the effects of total dietary fiber level on nutrient digestibility and the relationship between apparent total tract digestibility of total dietary fiber, and soluble dietary fiber, insoluble dietary fiber and available energy. Sugar beet pulp was as the only fiber source. The experiment was designed as a 6 x 6 Latin square with an adaptation period of 7 d followed by a 5-d total collection of feces and urine. Feed intake tended to decrease （P =0.] O） as total dietary fiber level increased. The apparent total tract digestibility of dry matter, crude protein and gross energy decreased （P 〈0.0]） when total dietary fiber increased but the digestibility of soluble dietary fiber and insoluble dietary fiber increased （P 〈0.01）. The digestible energy and metabolizable energy content of diets decreased （P 〈0.01） as the total dietary fiber increased.

关键词： Growing pigs Insoluble dietary fiber Nutrient digestibility Soluble dietary fiber Total dietary fiber

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Risk Assessment of Diary Cattle Brucellosis Based on Systematic Multilevel Grey Relation Entropy Method

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Agricultural Science & Technology 2012年第10期13卷 2169-2174,2225页

作者：孙向东江慎铭刘拥军中国动物卫生与流行病学中心山东青岛266032 南昌航空大学江西南昌330063

[Objective] The study was to explore the major factors affecting diary cattle brucellosis risk assessment,as well as their strong-to-weak sequence,so as to provide theoretical basis for assessing diary cattle brucellosis risk level in different regions.[Method] From 4 dimensions of feeding and importing,breeding,housing and polyculture situation,an evaluation index system was set up,and diary cattle brucellosis risk survey was conducted in 3 typical ***,systematic multilevel grey relation entropy method was applied to perform data analysis.[Result] The strong-to-weak sequence of Level 1 impact factor of diary cattle brucellosis was as follows：feeding and importinghousingpolyculture situationbreeding;the sequence of Level 2 impact factor was U32〉U12〉U11〉U31〉U21〉U42〉U43〉U23〉U22〉U41;the risk level sequence of 3 typical regions was Province A（County A1,A2,A3）Province B（County B1,B2,B3）Province C（County C1,C2,C3）.[Conclusion] According to the weight of Level 1 index strata,administrative departments at all levels and dairy cattle farmers should lay emphasis on the aspects of feeding,importing and housing;viewed from the perspective of Level 2 index strata,dairy cattle farmers should value the siting of cattle field,the brucellosis surveillance before importing and milking modes *** to the diary cattle brucellosis risk level of 3 typical regions,if administrative departments at all levels strengthen peoples＇ awareness of their personal health and increase investment in this area,with new healthy cultured atmosphere built,the risk level of diary cattle brucellosis will surly decline.

关键词： Systematic multilevel grey relation entropy method Diary cattle brucellosis Risk assessment

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Use of near-infrared reflectance spectroscopy for the rapid determination of the digestible energy and metabolizable energy content of corn fed to growing pigs

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Journal of Animal Science and Biotechnology 2017年第1期8卷 161-169页

作者： Juntao Li Quanfeng Li Defa Li Yiqiang Chen Xiaoxiao Wang Wenjun Yang Liying Zhang State Key Lab of Animal Nutrition College of Animal Science&Technology China Agricultural University Beijing 100193China

Background： The ability of near-infrared reflectance spectroscopy（NIRS） to determine the digestible energy（DE）and metabolizable energy（ME） content of corn fed to growing pigs was tested. One hundred and seventeen corn samples, comprising different planting regions and varieties were collected from all over China in a three-year period. The samples were randomly split into a calibration set（n = 88） and a validation set（n = 29）. The actual and calculated DE and ME content of the corn samples was determined by digestion-metabolism experiments and the prediction equations of Noblet and Perez（J Anim Sci. 71：3389–98,1993）. The samples were then subjected to NIRS scanning and calibrations were performed by the modified partial least square（MPLS） regression method based on77 different spectral pre-treatments. The NIRS equations based on the actually determined and calculated DE and ME were built separately and then validated using validation ***： The NIRS equations obtained from actually determined DE, the coefficient of determination for calibration（RSQcal）, cross-validation（R^2CV）, and validation（RSQv） were 0.89, 0.87 and 0.86, and these values for determined ME were 0.87, 0.86 and 0.86. For the NIRS equations built from calculated DE, the RSQcal, R^2CV, and RSQvvalues were 0.88, 0.85 and 0.84, and these values for calculated ME were 0.86, 0.84 and 0.82. Except for the equation based on calculated ME（RPD_v= 2.38, 〈 2.50）, the other three equations built from actually determined energy and calculated DE produced good prediction performance（RPD_vranging from 2.53 to 2.69, 〉 2.50） when applied to validation ***： These results indicate that NIRS can be used as a quantitative method for the rapid determination of the available energy in corn fed to growing pigs, and the NIRS equations based on the actually determined energy produced better predictive performance than those built from calculated energy values.

关键词： Corn Digestible energy Growing pigs Metabolizable energy Near-infrared reflectance spectroscopy

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The effect of the ratio of standardized ileal digestible lysine to metabolizable energy on growth performance,blood metabolites and hormones of lactating sows

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Journal of Animal Science and Biotechnology 2012年第3期3卷 143-154页

作者： Lingfeng Xue Xiangshu Piao Defa Li Pengfei Li Rongfei Zhang Sung Woo Kim Bing Dong Ministry of Ag ricultu re Feed Industry Centre State Key Laboratory of Animal NutritionChina Ag ricultural UniversityBeijing 100193China Departmentof Animal Science North Carolina State University RaleighNC 27695USA

A total of 335 lactating sows （Landrace x Large White） were used in two experiments to determine the optimum ratio of standardized ileal digestible lysine （SID-Lys） to metabolizable energy （ME） for mixed parity sows during lactation. In Exp. 1, 185 sows （weighing an average of 256.2 ± 6.5 kg and having an average parity of 3.4 ± 0.3） were allocated to one of six experimental diets in a completely randomized block design within parity groups （1, 2, and 3＋）. The experimental diets were formulated to contain 3.06, 3.16, 3.20, 3.25, 3.30 or 3.40 Mcal/kg of ME and each diet was fed to the sows throughout a 28 day lactation. All diets provided a similar SID-lysine level （0.86%）. As a result, the diets provided a SID-Lys：ME ratio of 2.81, 2.72, 2.69, 2.65, 2.61 or 2.53 g/Mcal ME. Sow feed intake was significantly （P 〈 0.01） affected by the energy content of the diet as well as by sow parity. Using regression analysis, feed intake was shown to be maximized at 3.25, 3.21, 3.21 and 3.21 Mcal/kg of ME for parity 1, 2, 3＋ sows and the entire cohort of sows respectively （quadratic; P 〈 0.01）. In addition, the result of feed intake can be expressed as 2.65, 2.69, 2.69 and 2.68 g/Mcal based on analysis of SID-Lys：ME ratio. Litter weight gain was affected by dietary treatment for parity 3＋ sows and the entire cohort （P 〈 0.01）. Based on regression analysis, litter weight gain was maximized at 3.25 and 3.24 Mcal/kg of ME for parity 3＋（quadratic; P 〈 0.01） and the entire cohort （quadratic; P 〈 0.01）. Similarly, the result of litter weight gain could be expressed as 2.65 and 2.66 g/Mcal of SID- Lys：ME ratio. Therefore, 3.25 Mcal/kg of ME was selected for Exp. 2 in which 150 sows （weighing 254.6 ± 7.3 kg and having an average parity of 3.4 ± 0.4） were allocated to one of five treatments in a completely randomized block design within parity （1, 2, and 3＋）. The experimental diets were formulated to contain 2.1, 2.4, 2.7, 3.0 or 3.3 g/Mcal of SID-Lys：ME ratio with all diets providing 3.2

关键词： Blood metabolites Hormones Lactating sows Metabolizable energy Performance Standardized ilea digestible lysine

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Effect of Fertilizing Amount and Planting Density on Yield and Qual-ity of Strong-gluten Wheat Taishan 27

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Asian Agricultural Research 2017年第1期9卷 62-64,69页

作者： Yong MI Guangde LU Chao WANG Xianyin SUN Ruixia WANG Qiuhuan MU Tai'an Academy of Agricultural Sciences

To get the cultivation pattern featured by improved varieties and fine methods for strong-gluten and high-yielding wheat variety Taishan 27,this paper used Taishan 27 as material to study the effect of fertilizing amount and planting density on yield and quality of *** results showed that Taishan 27 had high yield under fertilizing amount of 225 kg/ha pure nitrogen and planting density of 240 × 104-300× 10~4/ha; the yield was lowest under fertilizing amount of 300 kg/ha pure nitrogen and planting density of 360 × 10~4/ha. The suitable planting density for Taishan 27 was 240 × 104-300 × 10~4/ha,and the fertilizing amount of nitrogen should be based on different soil fertility conditions to avoid water and fertilizer stress and improve yield.

关键词： Wheat Taishan 27 Fertilizing amount Planting density

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