The evolving role of Fourier-transform midinfrared spectroscopy in genetic improvement of dairy cattle

Over the last 100 years,significant advances have been made in the characterisation of milk composition for dairy cattle improvement programs.Technological progress has enabled a shift from labour intensive,on-farm collection and processing of samples that assess yield and fat levels in milk,to large-scale processing of samples through centralised laboratories,with the scope extended to include quantification of other traits.Fourier-transform midinfrared(FT-MIR)spectroscopy has had a significant role in the transformation of milk composition phenotyping,with spectral-based predictions of major milk components already being widely used in milk payment and animal evaluation systems globally.Increasingly,there is interest in analysing the individual FT-MIR wavenumbers,and in utilising the FT-MIR data to predict other novel traits of importance to breeding programs.This includes traits related to the nutritional value of milk,the processability of milk into products such as cheese,and traits relevant to animal health and the environment.The ability to successfully incorporate these traits into breeding programs is dependent on the heritability of the FT-MIR predicted traits,and the genetic correlations between the FT-MIR predicted and actual trait values.Linking FT-MIR predicted traits to the underlying mutations responsible for their variation can be difficult because the phenotypic expression of these traits are a function of a diverse range of molecular and biological mechanisms that can obscure their genetic basis.The individual FT-MIR wavenumbers give insights into the chemical composition of milk and provide an additional layer of granularity that may assist with establishing causal links between the genome and observed phenotypes.Additionally,there are other molecular phenotypes such as those related to the metabolome,chromatin accessibility,and RNA editing that could improve our understanding of the underlying biological systems controlling traits of interest.Here we review topics of importance to phenotyping and genetic applications of FT-MIR spectra datasets,and discuss opportunities for consolidating FT-MIR datasets with other genomic and molecular data sources to improve future dairy cattle breeding programs.

Use of Fourier-transform infrared spectroscopy to rapidly diagnose gastric endoscopic biopsies

AIM: To determine if Fourier-transform infrared (FT-IR)spectroscopy of endoscopic biopsies could accurately diagnose gastritis and malignancy.METHODS: A total of 123 gastroscopic samples, including 11 cases of cancerous tissues, 63 cases of chronic atrophic gastritis tissues, 47 cases of chronic superficial gastritis tissues and 2 cases of normal tissues, were obtained from the First Hospital of Xi'an Jiaotong University, China. A modified attenuated total reflectance (ATR) accessory was linked to a WQD-500 FT-IR spectrometer for spectral measurement followed by submission of the samples for pathologic analysis. The spectral characteristics for different types of gastroscopic tissues were summarized and correlated with the corresponding pathologic results.RESULTS: Distinct differences were observed in the FTIR spectra of normal, atrophic gastritis, superficial gastritis and malignant gastric tissues. The sensitivity of FT-IR for detection of gastric cancer, chronic atrophic gastritis and superficial gastritis was 90.9%, 82.5%, 91.5%, and specificity was 97.3%, 91.7%, 89.5% respectively.CONCLUSION: FT-IR spectroscopy can distinguish gastric inflammation from malignancy.

Classification of Toxic Cyanobacterial Blooms by Fourier-Transform Infrared Technology (FTIR)

Cyanobacteria are gram-negative photosynthetic bacteria capable of producing toxins responsible for morbidity and mortality in humans and domestic animals. They are capable of forming concentrated blooms, referred to as harmful algal blooms (HABs). Characterization of HABs is necessary to reduce risks from human and animal exposures to toxins. Current methods used to classify cyanobacteria and cyanotoxins have limitations related to time, analyst skills, and cost. Fourier-Transform Infrared Spectroscopy (FTIR) is a potential tool for rapid, robust cyanobacterial classification that is not limited by these factors. To examine the practicality of this method, library screening with default software algorithms was performed on HAB samples, followed by principle component cluster analyses and dendrogram analysis of samples meeting minimum quality requirements. Two tested spectrometers and software packages were successful at distinguishing cyanobacteria from green algae. Principle component cluster analysis and dendrogram analysis also resulted in clear differentiation between cyanobacteria and green algae. While these methods cannot be used independently to fully characterize HABs, they show the potential and practicality of FTIR as a screening tool.

Detection of Broad Bean Diseases by Fourier Transform Infrared Spectroscopy Combined with Curve Fitting

Fourier transform infrared （FTIR） spectroscopy was used to study diseased leaves in broad bean. Results showed that the infrared spectra of different broad bean diseased leaves were similar, which were mainly made up of the vibrational absorption bands of protein,lipid and polysaccharide.There were minor differences in-cluding the spectral peak position, peak shape and the absorption intensity in the range of 1 800-1 300 cm-1. There were obvious differences among their second derivative spectra in the range of 1 800-1 300 cm-1. After the procedure of the Fourier self-deconvolution and curve fitting of health bean leaves and broad bean diseased leaves in the range of 1 700-1 500 cm-1, three sub-peaks were obtained at 1 550 cm-1 （protein amide Ⅱ band）, 1 605 cm-1 （lignin） and 1 650 cm-1 （protein amide I band）.The ratios of relative areas of the bands of amide Ⅱ, lignin, and amide I were 38.86%, 28.68% and 32.47% in the spectra of healthy leaves, respec-tively. It was distinguished from the diseased leaves （chocolate spot leaf： 15.42%, 42.98% and 41.61%, ring spot leaf：32.39%, 35.63% and 31.98%, rust leaf： 13.97%, 46.40% and 39.65%, yel owing leaf curl disease leaf： 24.01%,36.55% and 39.44%）. For sub-peak area ratios （A1 563/A1 605, A1 650/A1 605 and A1 563/A1 654）, those of four kinds of diseased leaves were smal er than that of healthy leaves, and there were also differences among four kinds of diseased leaves. The results proved that FTIR combining with curve fitting might be a potential y useful tool for detecting different kinds of broad bean diseases.

Molecular structure characterization of middle-high rank coal via^(13)C NMR,XPS,and FTIR spectroscopy

Elemental analysis,nuclear magnetic resonance carbon spectroscopy(^(13)C-NMR),X-ray photoelectron spectroscopy(XPS)and Fourier transform infrared spectroscopy(FTIR)experiments were carried out to determine the existence of aromatic structure,heteroatom structure and fat structure in coal.MS(materials studio)software was used to optimize and construct a 3D molecular structure model of coal.A method for establishing a coal molecular structure model was formed,which was“determination of key structures in coal,construction of planar molecular structure model,and optimization of three-dimensional molecular structure model”.The structural differences were compared and analyzed.The results show that with the increase of coal rank,the dehydrogenation of cycloalkanes in coal is continuously enhanced,and the content of heteroatoms in the aromatic ring decreases.The heteroatoms and branch chains in the coal are reduced,and the structure is more orderly and tight.The stability of the structure is determined by theπ-πinteraction between the aromatic rings in the nonbonding energy EN.Key Stretching Energy The size of EB determines how tight the structure is.The research results provide a method and reference for the study of the molecular structure of medium and high coal ranks.

Quantitative Analysis of Lignocellulosic Components of Non-Treated and Steam Exploded Barley, Canola, Oat and Wheat Straw Using Fourier Transform Infrared Spectroscopy

Rapid and cost effective quantification of lignocellulosic components （cellulose, hemicelluloses and lignin） of agricultural biomass （barley, canola, oat and wheat） is essential to determine the effect of various pre-treatments （such as steam explosion） on biomass used as feedstock for the biofuel industry. Fourier Transformed Infrared （FTIR） spectroscopy was considered as an option to achieve this objective. Regression equations having R2 values of 0.89, 0.99 and 0.98 were developed to predict the cellulose, hemicelluloses and lignin compounds of biomass, respectively. The average absolute difference in predicted and measured cellulose, hemicellulose and lignin in agricultural biomass was 7.5%, 2.5%, and 3.8%, respectively.

Identification of Plant-Pathogenic Fungi Using Fourier Transform Infrared Spectroscopy Combined with Chemometric Analyses

Identification of plant-pathogenic fungi is time-consuming due to cultivation and microscopic examination and can be influenced by the interpretation of the micro-morphological characters observed.The present investigation aimed to create a simple but sophisticated method for the identification of plant-pathogenic fungi by Fourier transform infrared(FTIR)spectroscopy.In this study,FTIR-attenuated total reflectance(ATR)spectroscopy was used in combination with chemometric analysis for identification of important pathogenic fungi of horticultural plants.Mixtures of mycelia and spores from 27fungal strains belonging to nine different families were collected from liquid PD or solid PDA media cultures and subjected to FTIR-ATR spectroscopy measurements.The FTIR-ATR spectra ranging from 4 000to 400cm-1 were obtained.To classify the FTIRATR spectra,cluster analysis was compared with canonical vitiate analysis(CVA)in the spectral regions of3 050~2 800and 1 800~900cm-1.Results showed that the identification accuracies achieved 97.53%and99.18%for the cluster analysis and CVA analysis,respectively,demonstrating the high potential of this technique for fungal strain identification.

Rapid Method for the Determination of Total Monosaccharide in <i>Enterobacter cloacae</i>Strains Using Fourier Transform Infrared Spectroscopy

Fourier Transform Infrared Spectroscopy (FTIR) was used to quantify total monosaccharide content in the bacterium Enterobacter cloacae and several of its biofilm mutants. Bacterial biofilm samples were grown on trypticase soy agar, and 30 μL aliquots of aqueous sample bacterial plus biofilm were deposited into the center of barium fluoride crystals and dried at 50°C for 1-hour before being scanned by FTIR. The total amounts of monosaccharides were estimated using the absorbance of the mono-saccharide peak, 1192 - 958 cm–1, and normalized using the amide II peak, 1585 - 1483 cm–1. This method provided a linear correlation between the absorbance of the monosaccharide peak and concentration of monosaccharide in standard monosaccharides, fructose, glucose, mannose, and rhamnose, over a concentration range of 0.5 - 2.0 mg/mL.

Fourier Transform Infrared Spectroscopic Study of Sodium Phosphate Solids and Solutions

Solids and solutions of sodium phosphates with various chain lengths have been studied by using the techniques of diffuse reflectance infrared Fourier transform (DRIFT) spectroscopy and attenuated total reflection-Fourier transform infrared (ATR-ETIR) spectroscopy, respectively. A systematic study of the infrared spectra of the solid sodium phosphates has been conducted on the basis of the information available it? the literatures to establish the assignments of the infrared vibrations of the different groups in the phosphate molecules. The infrared spectra of the solutions of sodium phosphates have been analyzed according to the infrared study on the relevant solids, in conjunction with the study of the phosphate species distribution in solution on the basis of the acid-base reaction equilibria. The results obtained have revealed the correlations between the infrared absorption spectra and the structure of the different P-O groups in different kinds of phosphates and are useful in the analysis of phosphate solids and solutions widely used in the various operations of mineral processing.

Thermal,infrared spectroscopy and molecular modeling characterization of bone:An insight in the apatite-collagen type I interaction

An insight into the interaction of collagen type I with apatite in bone tissue was performed by using differential scanning calorimetry, Fourier transform infrared spectroscopy, and molecular modeling. Scanning electron microscopy shows that bone organic content incinerate gradually through the different temperatures studied. We suggest that the amide regions of the type I collagen molecule (mainly C=O groups of the peptide bonds) will be important in the control of the interactions with the apatite from bone. The amide I infrared bands of the collagen type I change when interacting to apatite, what might confirm our assumption. Bone tissue results in a loss of thermal stability compared to the collagen studied apart, as a consequence of the degradation and further combustion of the collagen in contact with the apatite microcrystals in bone. The thermal behavior of bone is very distinctive. Its main typical combustion temperature is at 360°C with a shoulder at 550°C compared to the thermal behavior of collagen, with the mean combustion peak at ca. 500°C. Our studies with molecular mechanics (MM+ force field) showed different interaction energies of the collagen-like molecule and different models of the apatite crystal planes. We used models of the apatite (100) and (001) planes;additional two planes (001) were explored with phosphate-rich and calcium-rich faces;an energetic preference was found in the latter case. We preliminary conclude that the peptide bond of collagen type I is modified when the molecule interacts with the apatite, producing a decrease in the main peak from ca. 500°C in collagen, up to 350°C in bone. The combustion might be related to collagen type I, as the ΔH energies present only small variations between mineralized and non-mineralized samples. The data obtained here give a molecular perspective into the structural properties of bone and the change in collagen properties caused by the interaction with the apatite. Our study can be useful to understand the biological synthesis of minerals as well as the organic-inorganic interaction and the synthesis of apatite implant materials.

GP Algorithm-Based Fourier Transform Infrared Spectrum Trend Term Removal Model

Trend term removal is a key step in Fourier transform infrared spectroscopy(FTIR)data pre-processing.The most commonly used least squares(LS)method,although satisfying the real-time requirement,has many problems such as highly correlated initial values of the expression parameters,the need to pre-estimate the trend term shape,and poor fitting accuracy at low signal-to-noise ratios.In order to achieve real-time and robust trend term removal,a new trend term removal method using genetic programming(GP)in symbolic regression is constructed in this paper,and the FTIR simulation interference results and experimental measurement data for common volatile organic compounds(VOCs)gases are analyzed.The results show that the genetic programming algorithm can both reduce the initial value requirement and greatly improve the trend term accuracy by 20%-30% in three evaluation indicators,which is suitable for gas FTIR detection in complex scenarios.

Infrared-Spectral Characteristics of <i>Camellia oleifera</i>Shell/Meal during Composting

The compost products of Camellia oleifera shell/meal mixed at different mass ratios were characterized by Fourier-transform infrared spectroscopy (FTIR) at different composting stages to monitor the structural changes of their components. The results showed that the amount of Camellia oleifera meal significantly affected the composting rate of the shell, but did not change the degradation order and decomposition of the related compounds. During the composting process, microorganisms used the highly decomposable carbon source materials, such as proteins and sugars, first to grow and multiply, and then decomposed hemicellulose, cellulose and lignin by oxidative cleavage after these nutrients were consumed to a certain extent. The decomposition products were then condensed into more stable humic acids. The degradation rates of the compounds were directly proportional to the amount of Camellia oleifera?meal. The compounds in Camellia oleifera shell were composted faster with higher amounts of Camellia oleifera meals, resulting in less lignocellulose in the final products.

模块化FTIR测定FCV用氢气痕量杂质

设计构建了用于质子交换膜燃料电池汽车(FCV)氢气痕量杂质的模块化FTIR分析表征平台,开发了适用于氢气痕量杂质的分析方法,无需处理一次进样,能够同时快速测定HCOOH、CO、CO_(2)、NH_(3)、H_(2)O、CH_(4)、C_(2)H_(4)、C_(2)H_(6)、HCHO等多种痕量级别杂质。考察了各含氢杂质分析的影响因素,精选了杂质物种定性区域,优化了定量方法,提出了实用性强的定量检出限,在降低了背景气和空白气纯度的要求也能确保限值浓度准确测定。九种杂质的计算方法检出限达到ASTM D7653-18参考值,其定量限也均低于ISO 14687:2019相应的限值,定量线性范围约2个数量级,相关系数均大于0.999,准确度和精密度均不高于10%,通过ISO 21087:2019规定的方法适用性验证规则,满足ISO 14687:19相应的质控标准。根据不同场景需求,样品模块、气体净化控制模块、配气模块、红外分析模块和尾气处理模块可以有机结合并具有良好的实用性和扩展性,尾气处理后氢气浓度可降至100μmol·mol^(-1)以下排放,满足安全绿色环保的要求。与实验室其他参考方法测定值有较好的一致性,并已在FCV氢气工业生产样品质量检测中得到应用,它将从实验室离线方法逐步发展成为适用于工业不同场景的在线方法,这对燃料级氢气品质体系的建立、纯化技术的推广应用及燃料电池催化剂新材料开发均具有意义。

ATR-FTIR法在皮革产品中的应用

Comparison of the ATR-FITR spectra of nature and artificial leather shows that their feature peak positions do not overlap,By analysing their spectra and their corresponding second derivative infrared spectra we can discriminate them easily.Analysis and discrimination of leather products by ATR-FTIR is an accurate,sensitive,quick method.

基于FTIR的SBS改性沥青老化特性分析

采用宏观和微观分析相结合的方法,细致区分了SBS改性沥青中沥青相和SBS相各自的老化特性.通过常规指标试验评价了SBS改性沥青热氧老化前后的物理性能差异,并将其与基质沥青对比,得出SBS改性沥青的老化规律为黏度增加、变形能力下降.采用傅里叶红外光谱技术(FTIR)定量分析了SBS改性沥青老化前后结构与性能的关系,发现SBS改性沥青在老化时主要发生吸氧反应,并伴随着SBS中丁二烯C—C键的断裂.老化过程中,SBS改性沥青FTIR特征峰的定量变化与其宏观性能间具有明确的定量关系.

7份不同产地野生甜茶FTIR指纹图谱及其甜茶苷含量比较分析

本研究运用傅里叶变换红外光谱法,采集7份不同产地甜茶叶片的FTIR图谱,结合相关性系数和二阶导数方法对其红外光谱特征进行指认,并比较各供试甜茶的红外指纹图谱及甜茶苷含量间差异。研究结果表明,依据不同产地甜茶红外指纹图谱特征,可以将其归结为3大类Ⅰ类包括:金秀、荔浦、平南、象州及永福等地的甜茶,相关系数在0.992～0.999间;Ⅱ类包括第Ⅰ类型以外的广西其它采集地区的甜茶,相关性系数主要集中在0.984～0.990之间;Ⅲ类包括广东分布区,该区甜茶与广西分布区甜茶的相关系数均在0.986以下。供试甜茶与甜茶苷标准品的光谱特征比较结果表明,不同产地甜茶甜茶苷含量有较大差异。其中,广西金秀和广西平南产的甜茶叶片中甜茶苷含量最高,广西岑溪产的甜茶叶片中甜茶苷含量最低。所以,运用FTIR技术可以对不同产地甜茶进行分析并快速鉴别出不同产地甜茶中甜茶苷含量差异。本研究结果对广西地区甜茶的引种驯化和合理开发利用有一定指导意义。

栽培与野生黄花蒿中化学组分的FTIR表征及青蒿素含量比较分析

本研究运用FTIR技术,对栽培和野生黄花蒿不同部位化学成分的红外光谱特征进行指认,并比较分析两者不同部位青蒿素含量差异。结果显示:酰胺、芳香类物质均以栽培黄花蒿茎和叶片中多;可溶性多糖和糖苷类物质,栽培与野生黄花蒿茎中含量相近,但是,叶片中含量以栽培黄花蒿高;纤维素类物质,栽培茎少于野生茎,而两种黄花蒿叶片的纤维素含量相近。与青蒿素标准品比较,栽培和野生黄花蒿不同部位青蒿素含量有一定差异,其中栽培叶最高,其次是野生叶,栽培茎的含量最低。所以,运用FTIR技术可以快速判断栽培和野生型黄花蒿主要化学成分的差异,本研究对黄花蒿的引种驯化和良种选育工作有一定指导意义。

杉木光变色的FTIR光谱分析

暴露于室外环境的木材或木制品,由于受气候因子的作用其表面性状和品质发生劣化,主要表现为木材变色,大大降低其利用价值。以人工林杉木为研究对象,利用模拟太阳辐射的氙光衰减仪对木材表面进行光劣化处理,采用傅里叶变换红外(FTIR)光谱技术分析了木材光变色过程中化学成分的变化,建立了木材变色与化学成分变化之间的关系。试验结果表明:光照过程中,1512,1462,1269和1227cm-1处与木质素有关的吸收峰强度明显降低,1720～1735cm-1处非共轭羰基伸缩振动吸收明显增强,木材表面发生光氧化反应,木质素明显降解,同时不断有新的羰基化合物生成;光照80h内,木质素的降解以及羰基化合物的生成速度较快,此后变化不显著;木材表面部分多糖物质(纤维素和半纤维素)被氧化降解。研究表明,木材光照过程中的颜色变化(ΔE*)与木质素的降解以及羰基官能团的生成密切相关。

FTIR-ATR法对人体胆结石中胆固醇和胆红素的定量分析研究

目的:建立傅立叶变换衰减全反射红外光谱法(FTIR-ATR)同时测定胆结石中的胆固醇和胆红素的含量。方法:无需溶解和提取,分别选择胆结石中互不干扰的胆固醇特征吸收峰1049 cm-1和胆红素特征吸收峰1245 cm-1作为各自的定量吸收峰,利用基线吸收度法,直接地同时测定胆结石中的胆固醇和胆红素的含量。结果:胆固醇和胆红素的浓度与其峰高的线性范围分别为32.1-45.2μg·mg-1和13.2-44.2μg·mg-1,相关系数分别为0.9995和0.9987,说明符合Beer-Lambert’s定律。胆固醇和胆红素的回收率分别为100.4%和99.2%,RSD分别为2.1%和2.0%(n=3)。并与HPLC方法所测结果做了比较,发现2个方法所测含量结果基本相符。结论:本方法操作简便,无污染,结果准确可靠,可用于胆结石中胆固醇和胆红素含量的同时测定。

FTIR结合化学计量学对三七产地鉴别及皂苷含量预测研究

不同产地对中药次生代谢产物有显著影响,产地鉴别有助于中药的科学合理利用;其次,有效成分含量检测是评价中药质量的主要手段。通过傅里叶变换红外光谱结合化学计量学建立快速鉴别三七产地及测定三七中四种主要皂苷的方法,为三七的科学、合理、规范使用以及对三七质量进行快速评价提供依据。采集5个区域12个产地117个三七样本的红外光谱。产地鉴别预处理数据采用离散小波变换除去噪音造成的部分高频信号,偏最小二乘判别对产地判别贡献率大于1的数据进行筛选,kennard-stone算法将117个个体分为70%训练集与30%预测集。训练集数据用于建立支持向量机判别模型,交叉验证法用于筛选支持向量机最优参数,预测集数据对支持向量机判别模型结果进行验证。皂苷含量预测预处理数据采用标准正态变量变换、离散小波变换处理;处理的红外数据设为X变量,三七样品中通过高效液相色谱法测得的四种皂苷总量设为Y变量,采用正交信号校正去除红外光谱中与四种皂苷总量无关的干扰数据。个体数据分为80%训练集与20%预测集,训练集建立偏最小二乘回归模型,预测集数据对偏最小二乘回归模型的预测结果进行验证。结果显示:(1)交叉验证法得到支持向量机判别模型的最优参数为c=2.828 43,g=0.0625,训练集的产地判别最优正确率为91.463 4%;(2)支持向量机判别模型参数设置为最优参数,代入预测集数据,预测集的产地判别正确率为94.285 7%,判别正确率较高;(3)训练集建立偏最小二乘回归模型的相关系数R2=0.941 8,校正均方差RMSEE=4.530 7;(4)代入预测集数据,预测集的相关系数R2=0.962 3,外部检验均方差RMSEP=3.855 9,皂苷预测值与高效液相检测值接近,预测效果良好。傅里叶变换红外光谱结合支持向量机能对三七进行产地鉴别,正交信号校正结合偏最小二乘回归能对三七中四种主要皂苷总量进行准确预测,为三七质量控制提供一种快速简便、无损、高灵敏度的检测方法。