摘要
对2012-2013年黄土高原种植的13个牧草品种、780份干草样品的营养成分建立了近红外光谱(near infrared reflectance spectroscopy,NIRS)的检测模型。豆科牧草的粗脂肪(EE)、酸性洗涤纤维(ADF)和粗灰分(Ash)建模结果最好,其定标决定系数(RSQ)>0.94,交叉验证相关系数(1-VR)>0.7最高,定标标准分析误差(SEC)在0.071~0.713,交叉校验定标标准分析误差(SECV)在0.160~2.751。禾本科牧草的EE和可溶性糖(WSC)建模结果最好,RSQ分别达0.916和0.859,1-VR分别为0.609和0.810,SEC和SECV分别是0.250、1.488和0.505、3.172。菊科和车前科牧草的模型,除ADF外,其它指标预测的稳定性和准确性较为理想,RSQ在0.85以上,1-VR在0.70以上,SEC和SECV分别在0.361~3.557和0.495~4.602。NIRS对豆科粗蛋白(CP)和WSC的数值预测较差,RSQ仅>0.55,对禾本科CP、ADF、中性洗涤纤维(NDF)、Ash及菊科和车前科的ADF的预测稍差,RSQ>0.7。
A visible/near-infrared reflectance spectroscopy（visible/NIRS）model was developed to determine the forage cultivar nutritional composition of 780 hay samples under simulated rotational grazing.Hay samples（n=780）from 13 forage crop varieties under simulated grazing in Loess Plateau during the 2012 to 2013growing season were evaluated using calibration methods for prediction of nutrient contents using NIRS.The following results were obtained.The optimal calibrations in Leguminosae were ether extract（EE）,acid detergent fiber（ADF）,and crude ash（Ash）.The multiple correlation coefficients（RSQ）and 1-variance ratio（1-VR）were〉0.94and〉0.7,and standard error of calibration（SEC）and standard error of cross validation（SECV）were 0.071~0.713 and 0.160~2.751,respectively.Optimal calibrations in Gramineae were EE and water-soluble carbohydrate content（WSC）.RSQ were 0.916 and 0.859 and 1-VR were 0.609 and 0.810 for EE and WSC,respectively,and SEC was 0.250 and 1.488 and SECV was 0.505 and 3.172,respectively.For the other species,the results for nutrient predication were reasonably good,with the exception of ADF.RSQ and 1-VR were〉0.85and〉0.70,and SEC and SECV were 0.361~3.557 and 0.495~4.602,respectively.These results indicate that the accuracy of prediction using NIRS was acceptable for 13 forage crop nutrients,although the crude protein（CP）,ADF,neutral detergent fibre（NDF）,Ash of Gramineae and the ADF of others species（RSQ 〉0.7）may require further calibration.The accuracies of the predictions for CP and WSC in Leguminosae（RSQ〉 0.55）were not acceptable and thus more samples and greater precision during measurement will be required in further investigations.
作者
杨天辉
常生华
莫本田
侯扶江
Yang Tian-hui Chang Sheng-hua Mo Ben-tian Hou Fu-jiang(State Key Laboratory of Grassland Agro-ecosystems, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730020, China Institute of Animal Science, Ningxia Academy of Agricultural and Forestry Sciences, Yinchuan 750002, China Guizhou Institute of Prataculture, Guiyang 550006, China)
出处
《草业科学》
CAS
CSCD
北大核心
2017年第3期575-581,共7页
Pratacultural Science
基金
长江学者和创新团队发展计划(IRT13019)
甘肃省2016年草牧业试验试点和草业技术创新联盟科技支撑(GCLM2016001)
