应用近红外反射光谱法整粒测定小样品油菜籽含油量的研究

以完整油菜籽为样品,通过光谱预处理和回归统计方法来优化油菜籽含油量的近红外反射光谱法所建立回归方程,同时采用三种不同用量的样品杯进行近红外扫描分析.结果表明,光谱预处理对较正结果影响较大,不同光谱数学处理以3级导数处理较好,综合考虑定标组和检验组的效果,采用"2,3,3,1"、 "2,6,6,1"和"3,3,3,1"的三种处理组合较好     

用近红外反射光谱法分析稻米3种必需氨基酸含量的研究

采用近红外反射光谱分析技术来测定水稻精米粉样的3种必需氨基酸含量,揭示不同数学处理方法、光谱散射校正和回归统计方法对建立回归方程的影响.研究表明,光谱数据的数学预处理对发展定标回归方程有很大影响,对于不同的氨基酸,通过比较均可找到一些定标效果较理想的数学处理组合,如"2,3,3,1"等.光谱散射处理对氨基酸的定标改     

寒富苹果可溶性固形物可见/近红外光谱无损检测模型的优化

为提高可见/近红外光谱无损检测寒富苹果可溶性固形物的检测精度,应用近红外漫反射光谱仪对寒富苹果进行扫描,对主成分回归(principal component regression,PCR)、偏最小二乘法(partial least squares,PLS)和改进偏最小二乘法(modified partial least squares,MPLS)三种建模方法进行比较,通过改变波长的范围、导数处理、去散射处理、标准化处理、加权多元离散校正及间隔平滑处理等光谱预处理,研究不同建模和光谱预处理方法对寒富苹果可溶性固形物可见/近红外光谱无损检测模型准确性的影响。结果表明,在780~1 100 nm范围内,采用MPLS,间隔点为2,平滑点为2,结合去散射处理和一阶求导处理所建立的寒富苹果可溶性固形物定标模型最好,其定标模型的校正交互验证标准误差(standard error of cross validation,SECV)为0.306,交互验证决定系数(determination coefficient of cross validation,R2cv)为0.961;预测标准偏差(square error of prediction,SEP)、预测决定系数(determination coefficient of prediction,R2P)、预测相对分析误差(residual predictive deviation,RPD)分别为0.357、0.944、4.967,表明模型具有良好的预测效果,适用范围广。建模方法、波长范围、导数处理、间隔平滑处理、去散射处理使模型误差分别降低了14.688%~53.407%、20.787%~33.146%、1.918%~13.123%、1.813%~7.553%、0~2.647%,建模方法和光谱预处理对模型优化的次序依次为:建模方法波长范围导数处理间隔平滑处理去散射处理。     

花生籽仁蔗糖含量近红外模型构建及在高糖品种培育中的应用

含糖量是决定和影响花生食用品质和加工特性的重要指标,蔗糖含量占成熟花生籽仁总糖量的90%以上,建立蔗糖含量的高效检测技术,有助于加快高蔗糖甜味食用型花生品种培育进程。本研究利用蔗糖含量差异显著的185份花生材料,利用近红外仪(波长范围1100~2500 nm),配合小样品杯,扫描和采集自然干燥籽仁的近红外光谱,采用液相色谱(HPLC)结合标准曲线法测定试验材料的蔗糖含量,利用偏最小二乘法(partial least squares,PLS)构建了花生籽仁蔗糖含量的近红外定标模型,模型的决定系数R2=0.962,均方差为0.383。利用20份材料对模型进行外部验证,预测值和化学值的决定系数达0.947,表明该模型可较好地预测蔗糖含量,可以高效地测定杂交早期世代的单株花生蔗糖含量。利用该模型在“吉花02-1-4×中花26”杂交后代中发掘出6份含糖量7%以上、油酸78%以上、含油量48%以下,且农艺性状优良的食用花生新品系。     

天然牧草营养成分的近红外光谱定量分析

为探讨近红外光谱技术(NIRS)定量分析天然牧草营养成分的可行性,采集高寒草甸类高山嵩草草地天然牧草样品210份,用修正偏最小二乘法(MPLS),建立天然牧草中粗蛋白(CP)、中性洗涤纤维(NDF)、粗脂肪(EE)的近红外定量分析模型。结果表明：CP、NDF模型的交叉验证决定系数(1-VR)分别为0.9886、0.9554,交叉验证标准误差(SECV)分别为0.4393、1.7169,交叉验证相对分析误差(RPDCV)分别为9.3355、4.7194;EE模型的SECV、1-VR分别为0.6264、0.668,模型有待于进一步优化。试验初步建立了河南县高山嵩草草地天然牧草CP、NDF、EE定量分析模型,为青海省各地区天然牧草营养价值数据库的建立提供了基础数据。     

基于近红外法的鲜食大豆品质快速分析技术

为建立一种鲜食大豆品质的非破坏性快速检测方法,探究近红外分析技术在鲜食大豆品质检测中应用的可行性,以四川省成都市郫都区种植的66份鲜食大豆样品为材料,采用FOSS近红外谷物分析仪扫描得到光谱,并对所有材料的水分、蛋白质、可溶性糖和粗脂肪含量进行常规实验室分析,利用偏最小二乘法(PLS)建立近红外光谱与化学实验数据的相关模型,并进行模型优化、验证。得到的模型预测范围分别为水分含量60.03%~71.28%、可溶性糖含量2.36%~7.81%、可溶性蛋白含量1.03%~8.56%、粗脂肪含量4.33%~7.60%,预测系数(0.95)较高,标准误差(1.0)较低,实验结果显示,利用近红外分析技术建立定标模型用于检测鲜食大豆品质是可行且可靠的,该方法可快速检测鲜食大豆品质且不损坏籽粒,可用于鲜食大豆的种质资源评价、品质分级等。     

云南烤烟填充值近红外光谱预测模型

为研究采用近红外光谱技术快速预测烤烟烟丝填充值的可行性,选取云南12个烤烟品种不同部位3个等级的140份烤烟初烤烟样品,采集样品近红外光谱和烟丝填充值,采用偏最小二乘法,利用100份样品近红外光谱和填充值建立近红外光谱填充值预测模型。用40份样品近红外光谱和填充值进行模型外部验证,对填充值测定值和预测值进行t检验,T＝0.4125,在显著性水平α＝0.05下,t(0.05,39)=1.6849,T     

油用牡丹种子水分含量近红外光谱估算研究

水分含量是影响种子销售、储存及加工的重要指标之一。以156份油用牡丹种子为试验材料,利用近红外光谱技术快速检测油用牡丹种子水分含量,分析油用牡丹种子的光谱特征,应用近红外光谱技术,结合偏最小二乘回归法,建立油用牡丹种子水分含量的估算模型,并比较多种预处理方法对建模结果的影响。结果表明,油用牡丹种子水分含量特征波段为1 450 nm和1 940 nm;油用牡丹种子水分含量偏最小二乘回归估算模型精度均较高,而且比较稳定,可用于油用牡丹种子水分含量精确估算。油用牡丹种子吸收光谱经标准化处理后所建立的偏最小二乘回归模型性能最佳,估算结果最准确,其校正集和验证集决定系数分别为0.92和0.97,均方根误差分别为0.41%和0.24%,RPD值为5.94。研究表明,近红外光谱技术可进行油用牡丹种子水分含量快速无损估算。     

近红外透射光谱技术测定黍稷蛋白含量的研究

为了探索快速测定完整黍稷籽粒蛋白含量的方法,采用近红外光谱分析技术建立数学模型并进行预测,比较原始透射光谱经导数处理结合不同回归算法对模型的影响。结果表明,分别经一阶和二阶导数处理后利用偏最小二乘法和改进的偏最小二乘法,4种方法的分析效果相近,最优的是一阶导数结合改进的偏最小二乘回归法,黍稷蛋白定标模型的定标相关系数（RSQ）为0.8806,定标标准误差（SEC）为0.3424,交互验证相关系数（1-VR）为0.8570,交互验证标准误差（SECV）为0.3751,外部预测标准偏差（SEP）为0.454。最终以完整黍稷籽粒为样品所建立的蛋白NITS模型,可以用于黍稷蛋白含量的快速检测。     

近红外光谱法测定大米中的淀粉含量

用化学方法测定64个大米样品中的淀粉含量,利用近红外谷物分析仪采集样品的近红外光谱,选择合适的光谱区间和光谱预处理方法。50个定标集样品的近红外光谱经二阶导数及标准多元离散校正(Standard MSC)预处理,结合偏最小二乘法(PLS)建立了大米中的淀粉含量测定的定标模型,其相关系数为0.8780。14个验证集样品用于外部检验,大米中的淀粉含量的模型预测值与化学值之间的相关系数为0.9498。     

花生籽仁蛋白质含量近红外光谱模型的建立

采用近红外漫反射光谱非破坏性分析,结合偏最小二乘法,以河北省地方花生品种为研究对象建立了花生籽仁蛋白质含量的近红外光谱模型。结果表明,对原始光谱数据采用一阶导数+变量标准化处理的方法建立的模型其校正或预测效果最佳。该模型的校正集和验证集决定系数分别为0.9245和0.9018,校正标准误和预测标准误分别为0.3601和0.4153。用该模型对16个未参与建模的花生品种进行了预测,结果表明该模型具有很好的预测能力,可以用于花生品种蛋白质含量的快速检测。     

我国主栽棉花品种的棉籽油资源评价与分析

【目的】探讨不同地区、不同棉花品种棉籽油脂肪酸含量与组成的差异。【方法】以收集于我国棉花主产区的82份棉花品种的棉籽为试验材料,采用索氏法提取种子中粗脂肪,并利用气相色谱法分析脂肪酸组成和含量,最后通过聚类分析等分析脂肪酸组成与棉花品种和产地之间的内在联系。【结果】棉籽仁脂肪总含量在188.4~302.8 mg·g~(-1),平均为249.52 mg·g~(-1)。棉籽仁中主要脂肪酸为亚油酸(104.88~180.68 mg·g~(-1))、棕榈酸(41.53~69.77 mg·g~(-1))、油酸(28.29~48.86 mg·g~(-1))和硬脂酸(3.56~6.8 mg·g~(-1));各品种脂肪酸含量具有差异。聚类分析表明,棉籽脂肪酸总含量和脂肪酸组成与产地具有相关性。【结论】本研究筛选得到棉籽脂肪酸总含量以及油酸、亚油酸、亚麻酸高的材料,明确了82份种质资源的棉籽油分特征、特性和利用价值。     

Correlation Analysis of Seed Kernel Oil Content and Major Economic Traits in Cotton (Gossypium hirsutum L.)

One of the new directions in cotton breeding is to develop varieties with high oil content. In this study, we analyzed the relationships between the oil content of cottonseed kernels and other selected major economic traits of cotton. We used the DPS V3.01 data processing system to calculate linear correlation coefficients using experimental data for cottonseed oil content and other agronomic characteristics obtained from 108 cotton lines. There were no significant correlations between oil content and lint yield, boll numbers per plant, boll weight, and lint percentage. There were significant positive correlations between oil content and fiber uniformity, and oil content and elongation. The positive correlation between oil content and the fiber upper half mean length was not statistically significant. There were no significant correlations between oil content and fiber strength or fiber fineness. Oil content was weakly negatively correlated with Fusarium wilt resistance, but showed no correlation with Verticillium wilt resistance. The results of this study indicated that improvement of the oil content of cottonseed kernels will not affect lint production, and only weakly affect disease resistance. The results further indicated that such improvement may improve the fiber quality to some extent. Cottonseed kernel protein content and oil content were significantly negatively correlated. The findings indicated that it will be feasible to produce new varieties with high oil contents combined with good disease resistance, high lint yield, and better fiber quality. However, it will be very difficult to breed new varieties with both high oil and high protein content.     

棉仁高油分材料筛选及其脂肪酸发育分析

对2个主要栽培棉种共61个棉花材料的棉仁油分含量测定表明,棉花种间的棉仁油分含量差异较大。陆地棉和海岛棉材料的平均棉仁油分含量分别为30.42%和37.25%。陆地棉材料中棉仁油分含量变幅较大,从25.27%到35.42%;海岛棉材料的棉仁油分含量相对一致。分别以海岛棉‘Pima90-53’和陆地棉‘徐州142’、‘T586’为材料,考察了棉子发育过程中,油分含量及成分的发育变化进程。研究发现,棉仁油分含量在开花后20d时已达到棉仁干重的25%左右,棉子完全成熟时油分相对含量达到最高。气相色谱分析表明,棉仁脂肪酸主要包括棕榈酸、硬脂酸、油酸、亚油酸等,其中亚油酸的含量可达50%以上。随着棉子的发育,棉仁亚油酸含量逐渐减少,而棕榈酸、硬脂酸和油酸含量逐渐增加。棉花种间和种内材料的棉仁油分含量差异较大,说明对棉花材料的棉仁油分含量进行遗传改良具有较大的潜力。     

基于异速生长关系的棉籽油分含量模拟模型

基于不同熟性棉花品种的异地分期播种和施氮量试验,分析棉籽油分含量与棉籽生物量间的异速关系,综合品种特性、主要气象条件,以棉籽生物量为驱动,建立基于异速生长关系的棉籽油分含量模拟模型。利用不同生态点品种、播期和施氮量的田间试验资料的检验结果表明:安阳、淮安和徐州试点模拟值与实测值的RMSE分别为2.2%、2.9%和2.4%。说明依据棉籽油分含量与生物量间的异速生长关系预测棉籽油分含量切实可行,模型预测性好,广适性较强。     

棉籽蛋白质和油分形成的模拟模型

基于不同熟性棉花品种的异地分期播种和施氮量试验,综合量化品种特性、主要气象条件(温度、太阳辐射)和栽培措施(施氮量)对棉籽蛋白质和油分的影响,基于棉籽氮素积累和油分合成的“库限制”假设,结合棉花铃期与棉籽干物质积累模型,建立基于过程的棉籽蛋白质和油分形成模拟模型。利用不同生态点不同品种、播期和施氮量的田间试验资料对模型进行检验的结果表明,供试品种科棉1号和美棉33B棉籽的蛋白质含量模拟值与实测值的根均方差(RMSE)分别为2.05%和2.33%,其油分含量模拟值与实测值的RMSE分别为2.45%和2.95%。模型以主要气象资料(日平均温度、日太阳辐射量)和栽培措施(施氮量)作为模型输入,以棉花铃期与棉籽干物质积累模拟模型为基础,实现了较广泛生态条件下对不同品种棉花棉籽蛋白质和油分形成过程的模拟及其含量的动态预测。模型预测精度高,广适性强。     

棉籽蛋白质和油分形成的模拟模型

基于不同熟性棉花品种的异地分期播种和施氮量试验,综合量化品种特性、主要气象条件(温度、太阳辐射)和栽培措施(施氮量)对棉籽蛋白质和油分的影响,基于棉籽氮素积累和油分合成的“库限制”假设,结合棉花铃期与棉籽干物质积累模型,建立基于过程的棉籽蛋白质和油分形成模拟模型。利用不同生态点不同品种、播期和施氮量的田间试验资料对模型进行检验的结果表明,供试品种科棉1号和美棉33B棉籽的蛋白质含量模拟值与实测值的根均方差(RMSE)分别为2.05%和2.33%,其油分含量模拟值与实测值的RMSE分别为2.45%和2.95%。模型以主要气象资料(日平均温度、日太阳辐射量)和栽培措施(施氮量)作为模型输入,以棉花铃期与棉籽干物质积累模拟模型为基础,实现了较广泛生态条件下对不同品种棉花棉籽蛋白质和油分形成过程的模拟及其含量的动态预测。模型预测精度高,广适性强。     

Estimation of seed weight, oil content and fatty acid composition in intact single seeds of rapeseed ( Brassica napus} L.) by near-infrared reflectance spectroscopy

The potential of near-infrared reflectance spectroscopy (NIRS) for the simultaneous analysis of seed weight, total oil content and its fatty acid composition in intact single seeds of rapeseed was studied. A calibration set of 530 single seeds was analysed by both NIRS and gas-liquid chromatography (GLC) and calibration equations for the major fatty acids were developed. External validation with a set of 75 seeds demonstrated a close relationship between NIRS and GLC data for oleic (r = 0.92) and erucic acid (r = 0.94), but not for linoleic (r = 0.75) and linolenic acid (r = 0.73). Calibration equations for seed weight and oil content were developed from a calibration set of 125 seeds. A gravimetric determination was used as reference method for oil content. External validation revealed a coefficient of correlation between NIRS and reference methods of 0.92 for both traits. The performance of the calibration equations for oleic and erucic acid was further studied by analysing two segregating F2 seed populations not represented in the calibration set. The results demonstrated that a reliable selection for both fatty acids in segregating populations can be made by using NIRS. We concluded that a reliable estimation of seed weight, oil content, oleic acid and erucic acid content in intact, single seeds of rapeseed is possible by using NIRS technique. This revised version was published online in July 2006 with corrections to the Cover Date.     

Effects of Genotype and Environment on the Main Components in Cottonseed of Upland Cotton

[Objective] The aim of this study is to investigate the effect of cotton genotypes, growth environment, and their interaction on major components in cottonseeds. [Method] Eleven upland cotton cultivars were planted in 10 different locations in the middle and lower reaches of Yangtze River region as research materials. Cottonseeds were collected to determine the contents of six main components including protein content (PC), oil content (OC), gossypol, phytic acid (PA), α-tocopherol and γ-tocopherol, then the genotypes, environment, and their interaction effects were analyzed accordingly. [Result] The results showed that the genotypes, environment, and their interaction had extremely significant effect on the protein and oil content in cottonseeds. The environment had extremely significant effect on the gossypol and phytic acid content in cottonseed. The genotypes had extremely significant effect on the gossypol content and had significant effect on the phytic acid content in cottonseed, but their interaction was insignificant. The genotype effects of α-tocopherol and γ-tocopherol were not significant, but the environmental effects were significant. The differences of tocopherols between different regions reached the extremely significant level. In addition, protein content and oil content were significantly negatively correlated and the sum of the protein and oil contents remained stably at 75%. [Conclusion] In cotton seed quality breeding, not only the differences in varieties, but also the environment and the interaction between varieties and environment should be considered. The expression of the main components of cottonseed is the result of a combination of genotype and ecological environment.