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Near-infrared reflectance spectroscopy prediction of neutral

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Near-infrared reflectance spectroscopy prediction of neutral detergent-soluble carbohydrates in timothy and alfalfa

Z. Nie ,* G. F. Tremblay ,†1 G. Bélanger ,† R. Berthiaume ,‡ Y. Castonguay ,† A. Bertrand ,† R. Michaud ,† G. Allard ,§ and J. Han * * Department of Grassland Science, College of Animal Science and Technology, China Agricultural University, Beijing, P. R. China, 100094 † Agriculture and Agri-Food Canada, Quebec, Quebec, Canada G1V 2J3 ‡ Agriculture and Agri-Food Canada, Sherbrooke, Quebec, Canada J1M 1Z3 § Université Laval, Québec, Québec, Canada G1K 7P4

ABSTRACT Carbohydrates in forage crops can be divided into neutral detergent-insoluble fiber and neutral detergent-soluble carbohydrates (NDSC); the latter includes or-ganic acids (OA), total ethanol:water-soluble carbohy-drates (TESC), starch, and neutral detergent-soluble fiber (NDSF). The accurate and efficient estimation of NDSC in forage crops is essential for improving the performance of dairy cattle. In the present study, visible and near-infrared reflectance spectroscopy (NIRS) were applied to evaluate the feasibility of predicting OA, TESC, starch, NDSF, NDSC, and all related constitu-ents used to calculate these 5 carbohydrate fractions in timothy and alfalfa. Forage samples (n = 1,008) of timothy and alfalfa were taken at the first and second harvests at 2 sites in 2007; samples were dried, ground, and then scanned (400 to 2,500 nm) using an NIRSys-tems 6500 monochromator. A calibration (n = 60) and a validation (n = 15) set of samples were selected for each species and then chemically analyzed. Concentra-tions of TESC and NDSC in timothy, as well as starch in alfalfa, were successfully predicted, but many other carbohydrate fractions were not predicted accurately when calibrations were performed using single-species sample sets. Both sets of samples were combined to form new calibration (n = 120) and validation (n = 30) sets of alfalfa and timothy samples. Calibration and validation statistics for the combined sets of alfalfa and timothy samples indicated that TESC, starch, and NDSC were predicted successfully, with coefficients of

determination of prediction R

P

2

() of 0.92, 0.89, and

0.93, and a ratio of prediction to deviation (RPD) of 3.3, 3.1, and 3.6, respectively. The NDSF prediction was classified as moderately successful

R88, RPD28P20==()... The NIRS prediction of OA

was unsuccessful R38, RPD13P20==()... All related

constituents were predicted successfully R9, RPD3P2000>>().. by NIRS except ethanol-insolu-

ble residual OM, with R75 and RPD19P20==... Our

results confirm the feasibility of using NIRS to predict NDSC, its fractions, and other related constituents, except for OA and ethanol-insoluble residual OM, in timothy and alfalfa forage samples. Key words: alfalfa , near-infrared reflectance spectros-copy , neutral detergent-soluble carbohydrate , timothy

INTRODUCTION Forage carbohydrates account for approximately 60 to 75% of the total carbohydrate intake for lactating dairy cows. Carbohydrates in ruminant diets can be divided into 2 principal constituents: NDF and NFC. Because these 2 constituents are divided based on their solubility in neutral detergent solution, the term neu-tral detergent-soluble carbohydrates (NDSC) is more appropriate to describe NFC (Hall et al., 1999; Figure 1). Neutral detergent fiber includes cellulose, hemicellu-lose, and lignin, whereas the predominant carbohydrates in NDSC are sugars, starch, and pectic substances. The NDSC also include organic acids (OA), fructans, and any other carbohydrates that are soluble in the neutral detergent solution with heat-stable α-amylase. As a class, NDSC are considered to be approximately 98% digestible (Van Soest, 1967), but their diversity precludes their use as a uniform nutritional fraction. A better understanding of how dairy cattle digest carbo-hydrates could lead to improved animal performance and contribute to more efficient nitrogen use (Leiva et al., 2000). The system for partitioning NDSC proposed by Hall et al. (1999) is based on different extractions in neutral detergent solution and an ethanol solution. This method allows researchers to quantitatively evaluate feed con-centrations of OA, starch, sugars (monosaccharides and

J. Dairy Sci. 92 :1702–1711doi: 10.3168/jds.2008-1599 © American Dairy Science Association, 2009 .

1702 Received July 31, 2008. Accepted December 12, 2008. 1 Corresponding author: gaetan.tremblay@agr.gc.ca

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5C培训模拟试题及答案重症医学专科资质培训班模拟考试试题及答案

5C培训模拟试题及答案重症医学专科资质培训班模拟考试试题及答案

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国家标准粮油检验大豆蛋白质脂肪含量测定近红外法编制说明

国家标准粮油检验大豆蛋白质脂肪含量测定近红外法编制说明

国家标准《粮油检验大豆蛋白质、脂肪含量测定近红外法》编制说明《粮油检验大豆蛋白质、脂肪含量测定近红外法》国家标准起草组二〇〇八年十月十六日1.工作简况（包括任务来源、协作单位、主要工作过程、国家标准主要起草人及其所做工作等）项目背景和来源近红外分析方法(NIR)是近年来在粮食质量测定中作为迅速、简便、非破坏性检测发展起来的新技术，它是利用粮食中某一成分在近红外谱段中（700nm—2500nm）对特定波长近红外光能量与其含量有等比吸收的原理。

近年来，我国粮食和农业部门引进了世界各国多种型号近红外分析仪，使我国近红外应用技术迅速发展，在农产品质量控制上发挥了一定作用。

近红外分析方法自二十世纪七十年代被美国确定为非破坏检测粮食水分、蛋白质、脂肪的标准方法以来，在美国、法国、丹麦、瑞典、日本、澳大利亚等农业发达国家已经将NIR检测装置作为大豆蛋白质、脂肪证明的认定基准装置。

实践验证，近红外分析仪不仅可以为生产企业的品质控制提供直接快速的信息，使生产企业能够及时调整生产工艺，而且近红外光谱分析仪在粮食质量检测中充分体现了它快速、准确、节省人力物力等优点。

多年来，粮食检验部门和加工企业陆续购置了不少近红外分析仪器，但是由于缺乏标准的支撑，近红外分析技术在粮食检验机构一直未能得到真正应用。

为了规范近红外光谱仪的使用，确保测定结果的可靠性，使各级检测部门、研究机构及厂家在使用近红外光谱分析仪时有标准方法可依据。

通过近红外粮食质量检测系列标准的建立，将为粮食质量保证体系提供良好的技术支撑。

根据国家标准化管理委员会《关于下达2007年第四批国家标准制修订计划的通知》（国标委计[2007]85号）的要求，项目编号为-T-449的《粮油检验大豆蛋白质、脂肪含量测定近红外法》国家标准起草任务由河南工业大学负责起草。

在国家粮食局标准质量中心的组织、协调下，河南工业大学连同有关单位组成了本标准起草小组。

本标准制定主要工作过程本标准重点研究了AACC、ISO等关于近红外测定大豆或饲料方法的标准（草案），同时研究了国内有关近红外测定方法的标准。

液相色谱-串联质谱法测定水环境中的十氯酮

液相色谱-串联质谱法测定水环境中的十氯酮

液相色谱-串联质谱法测定水环境中的十氯酮周丽;董亮;史双昕;张利飞;张秀蓝;杨文龙;李玲玲;黄业茹【摘要】An analytical procedure for the determination of kepone in water was described. Water samples were extracted by liquid-liquid extraction,and then cleaned-up. Chromatograph-ic separation was performed on an Eclipse plus C18 column(100 mm×2. 1 mm,3. 5 μm)with gradient elution using acetonitrile and water at a flow rate of 0. 3 mL / min. The target com-pounds were determined in multiple reaction monitoring(MRM)mode via negative electrospray ionization( ESI - )and quantified by isotopic-dilution technique. Results showed that kepone existed as diol form and hemiacetal in acetone / acetonitrile and methanol respectively,the structures of which were confirmed by liquid chromatography-tandem mass spectrometry( LC-MS / MS). Due to the polar nature of kepone,it was difficult to be eluted during clean-up proce-dure and it may be decomposed during sulfuric acid washing. Therefore,it could not be ana-lyzed together with the other organochlorine pesticides. The calibration curve showed good line-arity in the range of 5-100 μg / L with correlation coefficient(r 2 )of 0. 999. The limit of detec-tion was 0. 70 ng / L and the limit of quantification was 2. 8 ng / L in water. The average recover-ies when spiked at 5,40 and 100 ng / L in water were 95. 1% -98. 9% ,and the relative standard deviations(RSDs)were 3. 85% -4. 72% . The method can be used to the determination of kepone in water due to its high sensitivity,good recovery and reproducibility.%建立了分析测定水环境中十氯酮的液相色谱-串联质谱法。

光纤反射光谱法(FORS)

光纤反射光谱法(FORS)

光纤反射光谱法（FORS）达妮埃拉·平娜（Daniela Pinna）1.分类光纤反射光谱法（fibre optic reflectance spectroscopy，FORS）是一种非侵入式检测技术。

用于FORS分析的分光光度计可测量光谱的紫外段、可见光段和近红外段。

2.说明分光光度计测量的是一种材料对一个谱段的光的反射比，测量结果以光谱曲线的形式给出，可反映材料反射的能量与波长（单位：nm）的关系。

FORS用的是便携式分光光度计，配有光纤，可采集对象表面的反射光谱。

大部分绘画材料都具有特定的光谱特征，采集UV-VIS-NIR谱段内的光谱，就可以得出它们在VIS-NIR谱段的综合指标（图1）。

图1 青金石和蓝铜矿的反射光谱［感谢苏珊娜·布拉奇（Susanna Bracci）］3.应用FORS已应用于绘画和彩绘表面的颜料与染料鉴定。

作为一种非侵入性技术，FORS可以对物体表面的不同区域进行广泛的光谱表征，加上低成本小型光谱仪的普及，它已成为一种常用的强大原位检测技术。

4.局限性反射光谱法对材料的鉴定能力在很大程度上取决于获取到的光谱品质（光谱分辨率），以及是否拥有可靠的标准谱谱库。

当存在复杂混合物时，FORS无法得出准确的结果。

此外，有些反射光谱相似的颜料（如镉红和朱砂）也无法用FORS来区分。

5.补充技术紫外照相术、X射线荧光光谱法、扫描电子显微镜结合能量色散X射线光谱法、傅里叶变换红外光谱法、拉曼光谱法、X射线衍射、气相色谱-质谱法、裂解气相色谱-质谱法。

6.技术规范与注意事项—配有光纤的分光光度计—光源—光谱范围—光谱分辨率—测量头几何条件（如照明0°、信号采集45°）—测量区域—每光谱扫描次数—校准物（如Spectralon®99%反射标准板）。

7.技术简史1938年，巴恩斯（Barnes）率先用这种方法凭借颜料的光谱特征来表征颜料。

8.文献[1] Serefidou M., S.Bracci, D.Tapete, A.Andreotti,L.Biondi, M.P.Colombini, C.Giannini, D.Parenti,‘Microchemicaland Microscopic Characterization of the Pictorial Quality of Egg-tempera Polyptych, Late 14th Century, Florence,Italy’, Microchemical Journal 127, pp.187-198.(2016)[2] Cheilakou E., M.Troullinos, M.Koui, ‘Identification of Pigments on Byzantine Wall Paintings from Crete(14th Century AD) using Non-invasive Fibre Optics Diffuse Reflectance Spectroscopy (FORS)’, Journal ofArchaeological Science 41, pp.541-555.(2014)[3] Gulmini M., A.Idone, E.Diana, D.Gastaldi, D.Vaudanc, M.Aceto, ‘Identification of Dyestuffs in HistoricalTextiles: Strong and Weak Points of a Non- invasive Approach’, Dyes and Pigments 98, pp.136-145.(2013)[4] ‘On-line Database of Fibre Optics Reflectance Spectra (FORS) of Pictorial Materials in the 270-1700 nmrange’.(2011) r.it/ (Retrieved 25-09-2017)[5] Delaney J.K., G.Z.Jason, M.Thoury, R.Littleton,M.R.Palmer, K.M.Morales, E.R.de la Rie, A.Hoenigswald,‘Visibleand Infrared Imaging Spectroscopy of Picasso’sHarlequin Musician: Mapping and Identification of Artist MaterialsIn Situ’, Applied Spectroscopy 64, pp.584-594.(2010)[6] Bacci M., L.Boselli, M.Picollo, B.Radicati,‘Ultraviolet, Visible, Near Infrared Fibre Optics ReflectanceSpectroscopy’, in Scientific Examination for the Investigation of Paintings (ed.D.Pinna, M.Galeotti,R.Mazzeo),pp.197-200.(2009)[7] Bacci M., A.Casini, C.Cucci, M.Picollo, B.Radicati, M.Vervat, ‘Non-invasive Spectroscopic Measurements on theII Ritratto della Figliastra by Giovanni Fattori: Identification of Pigments and Colorimetric Analysis’, Journal ofCultural Heritage 4 (4), pp.329-336, (2003)[8] Leona M., J.Winter, ‘Fibre Optics Reflectance Spectroscopy: A Unique Tool for the Investigation ofJapanese Paintings’, Studies in Conservation 46 (3), pp.153-162.(2001)[9] Bacci M., ‘UV-Vis-NIR FORS Spectroscopies in Modern Analytical Methods in Art and Archaeology’, inChemical Analysis Series Vol.155 (ed.E.Ciliberto, G.Spoto), New York: Wiley & Sons, pp.321-361.(2000)[10] Picollo M., M.Bacci, A.Casini, F.Lotti, S.Porcinai,B.Radicati, L.Stefani, ‘Fibre Optics ReflectanceSpectroscopy:A Non-destructive Technique for the Analysis of Works of Art’, in Optical Sensors and Microsystems:New Concepts, Materials, Technologies (ed.S.Martellucci, A.N.Chester, A.G.Mignani), New York: Kluwer Academic/PlenumPublishers.(2000)[11] Barnes N.F., ‘A Spectrophotometric Study of Artists’Pigments’, Technical Studies in the Field of FineArts 7, pp.120-138.(1938)。