共查询到19条相似文献，搜索用时 750 毫秒
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<正> 前言近红外反射光谱技术能快速估测牧草的营养品质(Norris等,1976;Shenk等,1979;Bartoa和Bu rdick,1981;Shenk等,1981)。然而,应用近红外反射光谱(NIRRS)估测含多种牧草的样品品质的 相似文献
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本研究利用近红外光谱通过人工神经网络(Artificial neural network, ANN)建立狼尾草属(Pennisetum Rich)牧草水分、粗蛋白、木质素、酸性/中性洗涤纤维及灰分含量的预测模型。结果表明：基于人工神经网络的狼尾草属牧草品质预测模型总体优于全光谱偏最小二乘法(PLS)模型效果。在人工神经网络的方向传播(BP)网络模型中,6项表征牧草品质指标的校正均方根误差(RMSEC)、预测均方根误差(RMSEP)均显著低于PLS模型,同时校正集决定系数(R■)、预测集决定系数(R■)显著提高,除灰分含量预测不理想外,其他预测效果均理想。同时人工神经网络的BP网络对于近红外光谱的非线性数据具有良好的拟合能力,其预测模型对于指导狼尾草属牧草品质预测和分级管理研究具有广阔的应用前景。 相似文献
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《动物营养学报》2021,33(7)
本研究旨在探讨近红外光谱(NIRS)技术在定量分析高寒草原天然牧草营养品质的可行性。试验于2015—2018年,每年6—9月份,从青藏高原高寒草原放牧研究样地收集不同放牧强度(0、3.6、5.3、7.6只/hm2)的混合和4个优势种(莎草科矮生嵩草、蓼科珠芽蓼、蔷薇科金露梅和豆科锦鸡儿)牧草样品共计1 280份,随机分为定标样品集(n=854)和预测样品集(n=426),建立天然牧草干物质(DM)、粗脂肪(EE)、粗蛋白质(CP)、酸性洗涤纤维(ADF)、中性洗涤纤维(NDF)含量及体外干物质消化率(IVDMD)和估算代谢能(EME)营养品质近红外光谱(NIRS)预测模型,实现天然牧草营养品质的快速和准确评估。结果显示:牧草DM、CP、EE、ADF、NDF含量及IVDMD和ME变异较大;DM、CP、ADF、NDF含量及IVDMD和EME的NIRS预测模型的验证决定系数(R2CV)为0.992～0.999,外部验证相对分析误差(RPD)为3.82～5.97,取得了最佳的定标效果,且定标方程均具较好的预测能力,能够成功应用于日常分析。EE含量的NIRS预测模型的R2CV为0.837,外部RPD为2.30,定标效果不理想,定标模型虽不能用于准确的定量分析测定,但仍能应用于牧草EE含量的粗略测定。综上所述,本研究建立的高寒草原天然牧草DM、CP、ADF、NDF含量及IVDMD和EME的NIRS预测模型能够成功应用于日常分析。 相似文献
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现代生物技术在牧草生产中的应用研究 总被引：5，自引：1，他引：5
牧草研究和开发在我国生态建设和草地畜牧业发展等方面具有十分重要的意义.对现代生物技术在牧草品种资源保存、牧草基因克隆与表达的分析研究和牧草育种方面的应用研究进展作一综述,为今后我国开展牧草种质资源研究和育种工作提供参考. 相似文献
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植酸是一种抗营养因子。传统的用三氯化铁沉淀植酸的化学分析法费时费工,不能满足饲料工业发展的需要。为了寻求快速检测饲料中植酸磷(简称P.P.)含量的手段,本试验运用近红外光谱分析技术(简称 NIRS),分别以植酸磷含量较高的米糠饼和植酸磷含量较低的高粱为样品,对这两种饲料的化学分析法测值与近红外光谱法测值进行了比较。试验结果表明:用48个米糠饼样品和50个高粱样品进行定标,相关系数(R,下同)分别为0.901和0.890,残余标准差(RSD,下同)分别为0.06和0.03;另用不参与定标的25个米糠饼样品和21个高粱样品对定标结果进行检验,R 分别为0.803和0.917,RSD 分别为0.07和0.02。NIRS 法的分析精度基本上可以达到化学分析法的要求。作者认为,达项技术作为饲料中 PP 含量快速分析的手段是可行的。 相似文献
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综述了近红外光谱法的基本原理和发展,以及近红外光谱技术在药物检测中的应用现状,并对其在兽药检测中的应用前景进行展望. 相似文献
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Abstract A Near Infra‐Red Reflectance Spectrophotometer was calibrated to analyse Italian ryegrass for protein nitrogen (N). Rye‐grass samples having a wide range in N content were analysed by standard “wet” chemistry techniques and the resulting data used to calibrate the Near Infra‐Red Spectrophotometer for ryegrass N analysis. A correlation (r) of 0,99 and standard error of calibration (SEC) of 0,209 resulted from the initial regression analysis between the Near Infra‐Red Spectroscopy (NIRS) estimated and “wet” chemistry data. In order to further evaluate the accuracy of the NIRS calibration a separate set of ryegrass samples were analysed for N content, by both the “wet” chemistry and NIRS methods, resulting in a correlation (r) of 0,98 and standard error of prediction (SEP) of 0,235. The applicability of the NIRS ryegrass calibration to other species was briefly examined by estimating the N contents of kikuyu (Pennisetum clandestinum) (r = 0,97 and SEP = 0,277). 相似文献
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Ohlsson C Houmøller LP Weisbjerg MR Lund P Hvelplund T 《Journal of animal physiology and animal nutrition》2007,91(11-12):498-507
The objective of the present study was to examine if near infrared reflectance spectroscopy (NIRS) could be used to predict degradation parameters and effective degradation from scans of original forage samples. Degradability of dry matter (DM), crude protein (CP) and neutral detergent fibre (NDF) of 61 samples of perennial ryegrass (Lolium perenne L.) and orchardgrass (Dactylis glomerata L.) was tested by using the in situ technique. The grass samples were harvested at three different stages, early vegetative growth, early reproductive growth and late reproductive growth. Degradability was described in terms of immediately rumen soluble fraction (a fraction, for DM and CP only as NDF does not contain a soluble fraction), the degradable but not soluble faction (b fraction) and the rate of degradation of the b fraction (c value). Overall effective degradability of DM, CP and NDF was also calculated. Near infrared reflectance spectroscopy was examined for its ability to predict degradation parameters and to make a direct prediction of effective degradation from scans of the original samples of perennial ryegrass and orchardgrass. Prediction of effective degradation of the different feed fractions showed different accuracy. The coefficients of determination (R(2)) from regressions of predicted vs. measured effective degradation, using a cross-validation method, were 0.92 for DM, 0.78 for CP and 0.61 for NDF. The attempt to predict the degradation parameters (a, b and c) by NIRS was less successful as the coefficients of determination for the degradation parameters were low. Concentrations of CP and NDF in the original samples were predicted by using NIRS and the validated R(2) value was 0.98 for CP and 0.92 for NDF. It is concluded that using NIRS predictions from scans of original samples is a promising method to obtain values for the effective degradation of DM, CP and NDF in ruminant feeds, but that larger calibration sets are necessary for obtaining improved accuracy. 相似文献
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基于红光和近红外反射光谱特征参数反演草地地上生物量 总被引：1，自引：0，他引：1
2013年6~10月测定东非狼尾草+白三叶混播草地冠层反射光谱和地上生物量;分析红光波段和近红外波段反射光谱特征参数与牧草鲜重及干物质之间的相关关系;构建并检验基于红光单波段和植被指数(NDVI、RVI、DVI)反演草地地上生物量回归模型。结果表明:红光波段反射率与草地地上生物量之间存在显著相关性;地上生物量的增加能够显著降低"红谷"反射率,显著升高近红外850.0nm处反射率;选用红光单波段反射率、红光波段构建的植被指数RVI或红光与近红外波段构建的植被指数NDVI,均能够精确反演草地鲜草产量和干物质产量;适宜估产的植被指数因季节和草地生物量的差异而不同,在6月11日,植被指数RVI反演模型估测的草地生物量与实测值的模拟效果最好,10月12日,植被指数NDVI反演模型估测的草地生物量与实测值的模拟效果最好。 相似文献
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M. Hervera M. D. Baucells G. González E. Pérez C. Castrillo 《Journal of animal physiology and animal nutrition》2009,93(3):366-372
The aim of this study was to check the accuracy of laboratory methods to predict the apparent protein digestibility (CPd, %) and digestible protein content (DP, g/kgDM) of dog foods, avoiding the use of experimental animals in digestion trials. Twenty‐eight commercial dry extruded dog foods were tested by three different methodologies: an adaptation of the in vitro incubation method described by Hervera et al. (J Anim Physiol Anim Nutr 2007, 91 : 205) for estimation of digestible energy of commercial dog foods, a modification of the pH drop methodology proposed by Hsu et al. (J Food Sci 1977, 42 : 1269) for protein evaluation of human foods and the Near Infra Red Spectroscopy (NIRS) technology. All the methods assessed revealed very good, similar accuracy in the prediction of DP content either using the in vitro method (r = 0.99; RSD = 6.76; CV = 2.31%), the pH drop method (r = 0.99; RSD = 6.94; CV = 3.02%) or the NIRS (R2 = 0.96; SECV = 10.50) method, although the in vitro digestion method showed the highest accuracy approach of in vivo crude protein apparent digestibility: CPd in vitro (r = 0.81; RSD = 2.01; CV = 2.41%); CPd pH‐drop (r = 0.78; RSD = 2.48; CV = 2.98%) and NIRS (r2cv = 0.53; SECV = 2.37). 相似文献
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近红外光谱分析技术在黑麦草粉粗蛋白测定中的应用 总被引：7，自引：0，他引：7
选取河北省吴桥试区不同品种、不同熟期、不同地块的黑麦草样品65份 ,用凯氏定N法进行了常规粗蛋白含量的测定。从中选出30个粗蛋白含量不同的样品作为近红外漫反射技术(NIR技术)测定的定标样品集。结果指出 :用NIR法得到的预测值与用凯氏定N法得到的测定值间的复相关系数达到R2=0.99 ,定标标样的标准误均方RMSEC=0.34 % ;用21个样品作检测样品集 ,凯氏定N法得到的测定值与NIR预测值间的复相关系数为R2=0.98 ,检测集样品预测标准误均方RMSEP=0.42 %。这一结果表明NIR作为一种黑麦草粉粗蛋白快速分析的技术是可行的 相似文献