Assessment of muscle oxygenation in the horse by near infrared spectroscopy

This study examined the ability of near infrared spectroscopy (NIRS) to noninvasively determine changes to muscle oxygenation in the resting horse. Five horses had (NIRS) performed over extremity muscle while under general anaesthesia, first with 8 min limb ischaemia, then systemic hypoxaemia for 5 min. A second group of 6 awake horses had NIRS performed over extremity muscle while being administered hypoxic gas (F(I)O2 0.10) for 5 min, and after return to steady state, limb ischaemia was induced for an additional 5 min. In the anaesthetised horses' ischaemia induced marked and significant muscle deoxygenation of haemoglobin/myoglobin (P<0.01), with corresponding arterial saturation decreasing from 98.9 to 81.9%. Hypoxaemia induced small yet significant muscle deoxygenation (P<0.01) that was 3.2% of the ischaemia deoxygenation signal, with a corresponding decrease in arterial saturation from 98.6 to 90.4%. In the awake horses muscle deoxygenation was not detectable during hypoxia despite reduction of arterial saturation from 97.8 to 86.8%, whereas ischaemia induced rapid and significant deoxygenation of muscle (P<0.05), with corresponding reduction of venous saturation from 78.4 to 75.4%. In neither group of horses was there evidence of cytochrome aa3 reduction, despite complete ischaemia for up to 8 min. NIRS changes in the resting horse muscle clearly differed between ischaemia and hypoxaemia, and can readily show muscle deoxygenation in clinically relevant hypoxaemia in the horse under anaesthesia. Further, as the deoxygenation signal induced by ischaemia was clearly detectable above a background movement artefact, NIRS application to study of muscle oxygenation in the working horse should be explored.     

近红外光谱法测定DDGS中粗蛋白含量的试验研究

试验建立DDGS粗蛋白含量测定的近红外光谱分析定标模型。采用化学分析法测定72个DDGS样品中的粗蛋白含量,利用FOSS InfraXact型近红外光谱分析仪采集样品光谱,光谱经2,4,4,1导数和标准正常化+散射处理(SNV+Detrend),用改进最小二乘法(MPLS)回归,获得了较好的定标模型,校正决定系数(RSQ)、交叉验证决定系数(1-VR)、校正标准误差(SEC)、交叉验证标准误差(SECV)分别为0.982 5、0.932 8、0.266 2、0.389 5。利用30个验证集的DDGS样品进行外部检验,预测值与真实值之间差异不显著(P>0.05)。结果表明,定标模型的预测性能较好,可以替代化学分析法快速测定DDGS中的粗蛋白含量。     

傅立叶变换近红外光谱技术快速测定玉米DDGS营养成分

为实现玉米DDGS营养指标的快速检测,本实验采用傅立叶变换近红外光谱技术,建立玉米DDGS水分、粗蛋白质、粗脂肪、粗灰分和氨基酸定量分析模型。收集全国范围内230个玉米DDGS样品,随机分为215个校正样品和15个验证样品,通过对不同组分独立进行光谱的预处理、交互检验计算和优化定标,得到的水分、粗蛋白质和粗脂肪定标方程决定系数R~2均在0.9以上,交互验证均方根误差(RMSECV)在0.30以内,相对分析误差RPD>3;粗灰分R~2为0.81,RMSECV为0.12,RPD为2.3,盲样验证结果均满足GB/T 18868要求,模型均有较好的准确性和稳定性;氨基酸组分建模和验证效果也较好。结果表明,采用傅立叶变换近红外光谱技术能够实现对玉米DDGS的快速检测。     

Nutritional evaluation of commercial dry dog foods by near infrared reflectance spectroscopy

Near infrared reflectance spectroscopy (NIRS) was used to predict the nutritional value of dog foods sold in Chile. Fifty-nine dry foods for adult and growing dogs were collected, ground and scanned across the visible/NIR range and subsequently analysed for dry matter (DM), crude protein (CP), crude fibre (CF), total fat, linoleic acid, gross energy (GE), estimated metabolizable energy (ME) and several amino acids and minerals. Calibration equations were developed by modified partial least squares regression, and tested by cross-validation. Standard error of cross validation (SE(CV)) and coefficient of determination of cross validation (SE(CV)) were used to select best equations. Equations with good predicting accuracy were obtained for DM, CF, CP, GE and fat. Corresponding values for and SE(CV) were 0.96 and 1.7 g/kg, 0.91 and 3.1 g/kg, 0.99 and 5.0 g/kg, 0.93 and 0.26 MJ/kg, 0.89 and 12.4 g/kg. Several amino acids were also well predicted, such as arginine, leucine, isoleucine, phenylalanine-tyrosine (combined), threonine and valine, with values for and SE(CV) (g/kg) of 0.89 and 0.9, 0.94 and 1.3, 0.91 and 0.5, 0.95 and 0.9, 0.91 and 0.5, 0.93 and 0.5. Intermediate values, appropriate for ranking purposes, were obtained for ME, histidine, lysine and methionine-cysteine. Tryptophan, minerals or linoleic acid were not acceptably predicted, irrespective of the mathematical treatment applied. It is concluded that NIR can be successfully used to predict important nutritional characteristics of commercial dog foods.     

近红外光谱技术在饲料品质检测中的应用

介绍了近红外光谱分析技术在饲料原料、配合饲料及奶牛全混合日粮检测中的应用及前景.     

近红外光谱分析技术在饲料工业中的应用进展

近红外光谱分析技术(Near infrared reflectancespectroscopy,简称NIRS)是20世纪70年代兴起的一种新的成分分析技术。该技术首先由美国农业部(USDA)的Norris开发,最早用于谷物中水分、蛋白质的测定。20世纪80年代中后期,随着计算机技术的发展和化学计量学研究的深入,加之近红外     

近红外光谱分析技术在饲料检测中的应用

近红外光谱（Near Infrared Reflectance Spectroscopy,简称NIRS）分析技术是20世纪70年代发展起来的一项高效、快速的现代分析技术,它综合运用了计算机技术、光谱技术和化学计量学等多个学科的最新研究成果,以其独特的优点在多个领域特别是农业领域得到广泛的应用。随着计算机技术和化学计量学的应用,     

近红外光谱法检测饲料玉米品质的优化PLS模型

试验基于化学计量学方法,提出了饲料玉米品质检测的优化近红外光谱定量模型。首先以偏最小二乘法分别建立饲料玉米水分、蛋白质测定的全光谱定标模型,然后综合运用光谱变换、异常样本剔除和特征波长选择等技术方法优化其性能。结果表明:优化模型的建模波点数减至全光谱的5%以下,R_c²和R_p²升到0.99以上,RMSEC和RMSEP降至0.05以下,RPD提高到12以上,预测结果与参考值的差异不显著(P>0.05)。由此可见,优化模型的预测能力和运行效率得到了显著改善,可将其用于实际检测工作。     

反刍动物饲料中总磷的近红外反射光谱分析研究

利用近红外反射光谱分析技术,采用偏最小二乘回归(PLS)方法,分别对光谱进行附加散射校正、变量标准化、一阶导数和二阶导数处理,建立了反刍动物饲料中总磷的预测模型。附加散射校正和二阶导数处理定标效果最优。定标集化学分析值与预测值之间的决定系数(R2)和标准差(RM-SEC)分别为0.9426和0.0347,相对分析误差为4.32;验证集化学分析值与预测值之间的决定系数(r2)和标准差(RMSEP)分别为0.9321和0.0359,相对分析误差为3.93。结果表明,利用近红外光谱反射分析技术可以定量检测反刍动物饲料中总磷的含量。     

Analysis of bovine udder, plate and viscera using near infrared reflectance spectroscopy

The objective of this study was to evaluate near infrared reflectance spectroscopy (NIRS) as an accurate and inexpensive alternative to conventional chemical analyses of nonconsumer bovine tissue. Udder, plate and visceral samples were collected from mature, Charolais-Angus and Hereford-Angus crossbred beef cows at slaughter, ground and analyzed for concentrations of lipid, protein and dry matter using standard AOAC chemical procedures. Samples were analyzed using NIRS. The collection of samples was randomly split into separate calibration and validation sets. Nine calibration equations representing each constituent and tissue combination were developed, using first- or second-order derivative mathematical transformations, and those calibration equations were validated. Correlation coefficients of calibration (R) and validation (r) ranged from .95 to .98 and from .87 to .97, respectively, for all analyses except plate dry matter (r = .77). Standard errors of calibration and prediction ranged from 1.89 to 5.81%. Results from this study are interpreted to indicate that bovine udder, plate and visceral tissue composition can be accurately, quickly and efficiently predicted using NIRS technology.     

近红外光谱技术与饲料质量评价

近红外光谱的技术(NIRS)作为一种新的分析技术在饲料行业的应用和研究已经十分广泛,它不仅能够较准确地测定饲料产品营养价值等方面的各相关参数指标,而且能科学的分析配合饲料的原料组成和含量。文中综述了国外利用近红外技术分析测定饲料原料以及配合饲料产品中蛋白、纤维、脂肪等常规营养指标,以及消化能、代谢能等营养价值指标的研究进展。同时,文章还概述了近红外光谱技术鉴别配合饲料所用原料以及测定成分含量方面的研究。     

近红外光谱技术(NIRS)测定玉米粉碎粒度的研究

试验研究了近红外光谱技术(NIRS)快速测定玉米粉碎粒度的应用。建立的近红外定量预测模型定标决定系数(RC2)为0.9463,相对标准差(RSD)为6.5619%,相对分析误差(RPD)为4.3771,定标结果较好;并对模型的预测能力进行了验证,其中验证决定系数(RV2)为0.9186,相对标准差为6.8646%,相对分析误差为4.0856,预测能力较好,表明近红外技术具有较高的准确度。实验研究结果对饲料生产过程中粉碎粒度的控制具有重要的实际意义。     

近红外反射光谱法(NIRS)分析奶牛精料补充料营养成分的研究

采用滤光片型8620近红外光谱技术(NIRS),结合主成分回归法,以105个不同的奶牛精料补充料样品建立了常规化学成分以及可消化总养分(TDN)含量的近红外定量分析校正模型。常规化学成分中,粗蛋白、粗脂肪、粗灰分、中性洗涤纤维、酸性洗涤纤维、酸性洗涤木质素和可消化总养分含量的校正模型决定系数R2分别为0.9132、0.9016、0.9220、0.9171、0.8928、0.7083和0.8346;研究发现除酸性洗涤木质素之外,其他成分含量的相对分析误差RPD(SD/SEP)均大于2.5,因此除酸性洗涤木质素之外,所建近红外预测模型对奶牛精料补充料常规营养成分以及TDN含量的快速测定具有重要的实际意义。     

Identification of uroliths by infrared spectroscopy

Wet chemical tests have deficiencies when applied to mixtures containing silica, which are common in the uroliths of some domestic animals. Consequently, the applicability of an infrared spectroscopic method was tested on 104 uroliths obtained from cattle, sheep, goats, horses, pigs, dogs, a chicken and a rabbit during diagnostic investigations. The following components were satisfactorily identified: silica, calcium oxalate, calcium carbonate, calcium phosphate, magnesium ammonium phosphate, magnesium phosphate and urates. The infrared characteristics of these compounds and their mixtures are described.     

近红外光谱分析与传统方法检测豆粕中营养成分的比较

近红外光谱分析技术(NIR)能简单、快速、准确地测定有机物中的化学成分。本实验用该法测定豆粕中各种常规营养成分,并将其与化学方法进行比较。数据显示:NIR与化学方法测定的结果相比,粗蛋白质、粗脂肪、灰分、水分、中性洗涤纤维和酸性洗涤纤维测定值的差异均不显著(P>0.05),相对误差分别为0.68%、9.61%、2.23%、1.17%、6.36%和6.34%;两种方法测定结果的相关系数(r)分别为0.9561、0.9408、0.9512、0.9924、0.9632和0.9584(P<0.01)。表明NIR可以应用于豆粕中营养成分的测定。     

近红外线光谱分析与传统方法检测面粉中粗蛋白和粗灰分的比较

近红外光谱分析技术是近年来发展起来一种新的分析技术,能简单、快速、准确地测定有机物中的化学成分。将其与传统分析方法测定面粉中粗蛋白和粗灰分进行比较,统计结果表明,二者相关系数r分别为0.986和0.991,相对误差均小于5%,说明可以用近红外光谱分析技术进行面粉粗蛋白和粗灰分的测定。     

Effective rumen degradation of dry matter, crude protein and neutral detergent fibre in forage determined by near infrared reflectance spectroscopy

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.     

近红外光谱分析与传统方法检测玉米中营养成分的比较

<正>在饲料工业中,各种原料以及成品的营养成分分析需要使用不同的仪器和方法,不同的试剂,且样品需要经过不同的物理、化学方法预处理,不但手续繁琐,而且耗时费力、花费高、安全性能差。因此,怎样快速、准确、经济、安全地测定饲料中各种营养成分已成为生产实践中亟待解决的问题。近红外光谱分析技术