近红外（NIR）光谱法测定完整苹果糖的含量

介绍一种快速分析完整苹果糖分的新方法──近红外光谱法。在波长９１０ｎｍ附近，高、中、低糖含量的二阶导数光谱之间有明显差异，该波长选作定标的第一波长。经９１０ｎｍ、８８４ｎｍ、８４３ｎｍ、９９１ｎｍ四波长线性回归分析，其相关系数为０．９８４，标准误差为０．３６０，检验时的标准误差为０．４５０，离差为０．１１。ＮＩＲ光谱法在实际应用中可满足完整苹果糖含量的测定精度。     

用近红外光谱法测定大白菜的营养成分

选用来自我国主要产地的大白菜不同品种及不同成熟期等材料２４２份，进行常规成分的定标和检验。结果表明：粗蛋白、中性纤维、还原糖及维生素Ｃ的近红外（ＮＩＲ）法测值与化学法测值的复相关系数（ＭＲ）分别为０．９９５８、０．９８５２、０．９８２１和０．９８１４，定标的标准误差（ＳＥＣ）分别为０．３９８％、０．１３４％．０．０９８％和０．５１ｍｇ／１００ｇ。用一定数量的检验样品以４种成分化学法与近红外法进行比     

非破坏评价黄瓜的营养成分

用近红外光谱法非破坏分析黄瓜中的维生素Ｃ、还原糖、干物重三种成分，与国际法相比，其相关系数分别为０．９９３２、０．９９３０、０．９８１６，标准误差为０．３６８ｍｇ／１００ｇ、０．０６８％和０．０８５％，说明两种方法有着相似的准确性和精密度，而近红外光谱法分析效率可提高上百倍，且不需要任何前处理，也不用化学试剂，分析后的黄瓜样品仍可食用或作商品出售。既适用于大批量样品的分析测定，又为品质育种和种质资     

豆天蛾核型多角体病毒病的研究

从豆天蛾的幼虫中分离到一株核型多体病毒，其多角体的平面图象多为六边形和近圆形，直径０．６－２．０μｍ，病毒粒子杆状，两端圆滑，大小约５０ｎｍ×３２０ｎｍ．室内和田间试验表明，该株病毒对豆天蛾幼虫有比较强的致病力，对三龄幼虫的致死中浓度（ＬＣ５０）为１．４×１０＾４．８个多角体／ｍｌ，ｙ＝３．２４＋０．５４ｘ。田间防效效果可达７０％左右，与苏云金杆菌制剂或其他害虫病毒制剂混用，防治效果达９０×以上，     

检测草莓果中多组分的新方法——近红外光谱法

用近红外光谱法（ＮＩＲｓ）分析草莓中的蔗糖、葡萄糖、果糖、柠檬酸、苹果酸和维生素Ｃ等６种成分，与高效液相色谱法（ＨＰＬＣ）有测值相比较，其相关系数分别为０．９９２０、０．９９１４、０．９８８８．０．９９５４．０。９９４９和０．９９８０，标准误差为０．０２１、０．０３５、０．０６５、０．０４４、０．０２９．０。７２７。说明ＮＩＲｓ法与ＨＰＬＣ法的准确度相似。由于此法具有快速、非破坏、样品不需要预处理     

铁氰化钾分光光度法测定单宁的适用性

分析了ＦｅＣｌ３—Ｋ３Ｆｅ（ＣＮ）６分光光度法测定植物单宁的适用性。结果表明，在ｐＨ＜２．２时的酸性介质中单宁－ＫＦｅ［Ｆｅ（ＣＮ）６］最大吸收峰在６８０～７２０ｎｍ之间，绝大多数情况下吸收峰在６９５ｎｍ处，比色液单宁浓度在０～８０μｇ·ｍｌ－１时未形成沉淀前，遵守朗伯—比耳定律。时间变异系数每分钟±０．０５％，回收率９４．７％～１０５．２％，相对误差１．２％～５．３％。该方法受在酸性条件下能将Ｆｅ３＋还原为Ｆｅ２＋的物质和形成沉淀的物质干扰。测定结果与靛红—高锰酸钾滴淀法相接近。     

苹果叶片过氧化物酶理化性质分析

以“青富１３”苹果叶片为试材，研究了苹果过氧化物酶（ＰＯＤ）的理化性质。结果表明：苹果叶片ＰＯＤ同工酶可粗分为酸性酶和碱性酶两大类，酸性酶的最适ｐＨ在６．０左右，碱性酶的最适ｐＨ在９．０左右；在最适ｐＨ条件下，不同的缓冲液体系对ＰＯＤ活性有一定的影响；该酶系最适温度综合表现为２５℃左右，热稳定性试验表明苹果ＰＯＤ相当耐热，８０℃可维持活性２ｍｉｎ左右 ，５５℃可保持活性７２ｈ；底物试验证明，该酶系     

苹果种质资源的离体保存

苹果（ＭａｌｕｓｄｏｍｅｓｔｉｃａＢｏｒｋｈ）试管苗在ＭＳ附加０．５ｍｇ／ｌＢＡ、０．２ｍｇ／ｌＩＡＡ、０．５％甘露醇、３０ｇ／ｌ蔗糖和５ｇ／ｌ琼脂的培养基上，在４℃黑暗条件下连续保存１２个月，其存活率达８７％，并且保持其遗传稳定性     

利用近红外反射光谱快速测定大豆籽粒蛋白质、脂肪和部分氨基酸含量

利用固定滤光片式近红外反射光谱仪测定大豆籽粒中的蛋白质、脂肪含量，只要用３～４个滤光片就可获得较高的精度。其定标和预测相关系数都在０．９５以上。测定天门冬氨酸、谷氨酸、赖氨酸和精氨酸各组分的含量则需要５～７个滤光片，其定标和预测相关系数在０．８６以上。表明该方法测定蛋白质、脂肪与部分氨基酸含量是可行的。     

高分子有机酸复合碱式硫酸铜的杀菌效果研究

通过室内和田间试验，高分子有机酸复合碱式铜具有较好的杀菌效果，对作物的安全性明显提高，以高分子有机酸复合碱式铜３００、４００和５００倍液，波尔多液（１：１）３００倍液、绿得保悬浮剂３００倍液和琥胶肥酸铜３００倍液，室内测定对苹果轮纹病孢子萌发抑制率分别为９３．５％，８５．２％，６５．４％，８５．９％和７５．６％，对苹果轮纹病菌丝生长抑制效果分别为７２．６％、６５．３％、５１．０％、４２．３％、７２     

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.     

Estimating the fatty acid composition of the oil in intact-seed rapeseed (Brassica napus L.) by near-infrared reflectance spectroscopy

The objective of this work was to evaluate the potential of near-infrared reflectance spectroscopy (NIRS) as a rapid method to estimate the fatty acid composition of the oil in intact-seed samples of rapeseed. A total of 549 samples (3 g intact seed) from selected mutant and breeding lines were scanned by NIRS, and 220 of them were selected and scanned again by using two different adapters, which reduced the sample size to 300 and 60 mg, respectively. Selected samples were analysed by gas liquid chromatography and calibration equations for individual fatty acids were developed. Calibrations for oleic, linoleic, linolenic, and erucic acid were highly accurate, with values of r² in cross validation from 0.95 to 0.98 (samples of 3 g), from 0.93 to 0.97 (300 mg), and from 0.84 to 0.96 (60 mg). Calibrations for palmitic and stearic acid were less accurate, with values of r² in cross validation always lower than 0.8, probably because of the narrow range available for these fatty acids. The accuracy of the calibration equations for eicosenoic acid was very low (r² = 0.69 in 3 g samples), although improved equations were developed (r² from 0.78 to 0.91) when the relationship between erucic and eicosenoic acid was taken into account. We conclude that NIRS is a powerful technique to estimate the fatty acid composition of the oil in rapeseed, provided that samples covering a wide range of fatty acid levels are available, with the advantage that such estimation is possible with few additional costs when NIRS is used for the determination of other seed quality traits. This revised version was published online in July 2006 with corrections to the Cover Date.     

近红外光谱技术与常规方法检测紫花苜蓿品质的对比研究

从黑龙江省国家牧草产业技术体系绥化综合试验站的试验田中采集的10 种（每种取7 个样品）紫花苜蓿样品分别采用近红外光谱技术和常规化学测定法,对其含有的粗蛋白（CP）、中性洗涤纤维（NDF）、酸性洗涤纤维（ADF）、脂肪（FAT）、灰分（ASH）、干物质（DM）成分进行了测定,并将测试结果用SPSS 软件进行配对T值分析比较,结果表明：两种方法的X ± S 相近,|t|<0.05,P>0.05,差异不显著。分别计算两种方法的标准偏差（S）和相对标准偏差（RSD）,发现近红外分析方法的值均小于常规化学分析方法。试验结果表明：基于与常规化学方法的比较,近红外方法可以作为一种新的检测方法被使用,值得广泛应用于各种牧草饲养品质的测定与推广。     

近红外光谱法非破坏性测定玉米子粒粗淀粉含量的研究

采用偏最小二乘回归法,对近红外光谱法测定玉米完整子粒粗淀粉含量的可行性进行研究。结果表明,定标集和检验集的预测值与化学测定值间均达极显著正相关,相关系数分别为0.9610和0.9820,并具有较小的定标标准差和预测标准差,分别为0.707和0.666。所建立的校正模型具有较高的预测精度。     

向日葵籽仁脂肪和脂肪酸含量近红外光谱模型的建立

为实现向日葵品质的快速无损检测,选取50份具有代表性的油用向日葵材料,采用偏最小二乘法（PLS）构建籽仁脂肪、亚油酸、油酸、硬脂酸和棕榈酸含量的近红外光谱（NIRS）模型。结果表明,脂肪、亚油酸、油酸含量模型校正和验证相关系数均大于0.96,且预测值与化学值相对误差均在10%以下,能够达到样品成分含量的快速测定。硬脂酸和棕榈酸含量模型校正相关系数分别为0.92和0.82,验证相关系数分别为0.83和0.74,预测值与化学值相对误差在4.66%~17.99%之间,可用于样品成分含量的初步预测。本研究构建的NIRS模型,有助于油用向日葵种质资源品质鉴定和快速筛选。     

基于小麦籽粒高光谱特征的品种鉴别研究

为探究高光谱成像技术在小麦籽粒品种鉴别等的研究,以15种品种已知的小麦籽粒为对象,分别采集样品的光谱和图像信息。运用主成分分析法优选三个特征波长(447nm、615nm、955nm),提取特征波长下小麦籽粒图像的形态特征(面积、周长、圆度、长轴长度、短轴长度)和纹理特征(均值、标准差、熵)。应用Bayes判别分析法进行多元统计分析,建立判别函数判别回代准确率为99.9%,交叉验证的准确率为98%,模型的判别效果良好。研究表明利用高光谱成像技术结合Bayes判别分析的方法可用于小麦籽粒品种的鉴别。     

近红外光谱技术在果蔬品质无损检测中的应用

水果蔬菜的无损检测对生产和贸易都具有重要价值。近红外光谱法由于其高效、快速的特点,已经广泛应用于果蔬品质的无损检测中。本文介绍了近红外光谱技术的多项优点、相关仪器的研制,以及应用该技术检测果蔬糖度、酸度、成熟度、维生素、以及病变等多种品质指标的国内外研究进展,提出了目前近红外光谱技术在果蔬品质检测中存在的不足,认为便携式的近红外光谱测定仪器将在未来果疏产业中发挥更重要的作用。     

Near infrared reflectance spectroscopy analysis of digestibility traits of maize stover

Summary Near infrared reflectance spectroscopy (NIRS) is emerging as a potentially useful tool in breeding plants for quality traits. Information is lacking, however, on its use in forage maize (Zea mays L.). The objectives of the present investigation were to evaluate the prediction of digestibility traits of maize stover using NIRS technique and to study the effect of laboratory (Lab) and NIRS assays on the estimates of variation and covariation. Twelve inbred lines, 66 diallel crosses among them and eight hybrid checks were evaluated at silage and grain harvests for 2 years at two agro-climatically diverse locations in the Federal Republic of Germany. Standard methods were used for Lab analysis of in vitro digestible organic matter (IVDOM), neutral detergent fibre (NDF), acid detergent fibre (ADF) and acid detergent lignin (ADL). In NIRS evaluation, calibration equations were developed by modified stepwise regression. The standard error of calibration was 2.5, 1.7, 1.4 and 0.4 for IVDOM, NDF, ADF and ADL, respectively. The coefficient of multiple determination was high (0.9) except for ADL. The validation statistics (standard error and correlation coefficient) were similar. In the diallel crosses, the estimates of variation (heritabilities in broad and narrow sense, genotypic and error coefficients of variation), generally, did not vary appreciably and consistently in the comparisons between Lab and NIRS methods particulary at silage harvest. Simple and rank correlations between Lab and NIRS analyses were positive and significant. These correlation coefficients based on the mean performance of the diallel crosses at silage harvest were >0.9 and at least 16 hybrids were common between the two analyses, among the upper one-third or lower one-third (22) hybrids. The study showed that NIRS analysis should be useful in maize breeding programmes wherein a large number of genotypes need to be evaluated.Abbreviations NIRS near infrared reflectance spectroscopy - Lab laboratory - IVDOM in vitro digestible organic matter - NDF neutral detergent fibre - ADF acid detergent fibre - ADL acid detergent lignin - SEC standard error of calibration - SEV standard error of validation - SD standard deviation - r simple correlation coefficient - r_s rank correlation coefficient - R² coefficient of multiple determination - h_b ² heritability in broad sense - h_n ² heritability in narrow sense - CV_g genotypic coefficient of variation - CV_e error coefficient of variation - GCA general combining ability effect     

花生自然风干种子油酸、亚油酸和棕榈酸含量的近红外分析模型构建

利用不同来源、不同种皮颜色的大粒型和小粒型材料,构建了花生自然风干种子油酸、亚油酸和棕榈酸含量的近红外定量分析模型。经优化,最佳光谱预处理方法均为“一阶导数+矢量归一化法”,油酸含量谱区范围为8717.1~5446.3cm-1（厘米波数）,维数为9,模型的决定系数（R2）为89.16,均方差（RMSECV）为2.62;花生种子亚油酸含量谱区范围为9,666~5,785.7cm-1,维数为9,模型R2为90.85,RMSECV为2.00;花生种子棕榈酸含量谱区范围为8,717.1~5,446.3cm-1,维数为8,模型R2为79.21,RMSECV为0.525。该模型可用于花生品质育种。     

Analysis of protein, starch and oil content of single intact kernels by near infrared reflectance spectroscopy (NIRS) in maize (Zea mays L.)

Maize samples (n = 309) containing 3090 single intact kernels from a broad variety of breeding materials were scanned by Near Infrared Reflectance Spectroscopy (NIRS) to develop non-destructive determination calibrations for crude protein, starch and oil content in kernels. Calibration equations of single kernels were developed by partial least square regression (PLS). Regression parameters between the chemical values, determined by reference methods, and the predicted values, determined by Near Infrared Reflectance Spectroscopy, were verified by cross validation and external validation. It was found that embryo position had a significant influence on the effect of calibrations. Reliable calibrations were developed for the prediction of protein and starch contents with the embryo upwards, whereas the oil content required the embryo to be downwards. The cross validation and external validation coefficients for protein were 0.91 and 0.94, for starch 0.90 and 0.89 and for oil 0.94 and 0.95, respectively. The data suggested that NIRS could be successfully used in breeding programmes, as an accurate and non-destructive tool to predict protein, starch and oil contents at the level of single kernels.