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

Sugar content is an important factor affecting the flavor and processing characteristics of peanut (Arachis hypogaea L.) kernel and the sucrose content accounts for more than 90% of the total sugar content in peanut kernel. High-efficiency detection approach for sucrose content is crucial in developing high sucrose peanut varieties. In this study, 185 peanut genotypes with diversified sucrose contents were scanned in wave length of 1100-2500 nm for constructing a near-infrared spectrum of naturally dried seeds. The sucrose contents were determined by high performance liquid chromatography (HPLC) combined with standard curve method. A near-infrared calibration model of peanut seed sucrose content was established by partial least square method (PLS). For sucrose content, the coefficient of determinations (R²) was 0.962 with mean square deviation of 0.383. The coefficient of correlation between the predicted values and chemically tested value were 0.947 in 20 external samples, indicating that the model could predict sucrose content of peanut kernel. Six new sweet peanut lines with sucrose content over 7%, oleic acid over 78%, oil content less than 48% and desirable agronomic characters were selected among the hybrid progenies of “Jihua 02-1-4 × Zhonghua 26”.     

单粒花生蔗糖含量近红外预测模型的建立

蔗糖含量是影响花生口感和风味的重要因素,培育高蔗糖甜味品种已成为食用型花生遗传改良的重要目标。因此,建立单粒花生蔗糖含量的近红外预测模型有助于加快甜花生品种选育进程。本研究选择128份遗传多样性丰富的代表性材料,采集了近红外光谱,利用高效液相色谱-折光指数检测器(HPLC-RID)测得蔗糖含量化学值,并利用偏最小二乘法(PLS)建立了单粒花生蔗糖含量的数学预测模型,其决定系数(R2)为0.913,交叉验证根均方差(RMSECV)为0.750。另选用50粒花生种子对预测模型进行外部验证,预测值和化学值的相关系数达0.92,表明本研究建立的模型预测值准确可靠。本研究建立的单粒花生蔗糖含量预测模型可以应用于杂交早期世代育种材料蔗糖含量的选择,也可以应用于高蔗糖材料纯度的筛选和鉴定,为食用型花生品种选育和产业化应用提供技术支撑。     

基于HPLC-RID的花生籽仁可溶性糖含量检测方法的建立

食用型花生是我国乃至世界范围内花生育种的重要方向之一,但是花生遗传改良中缺乏与食用品质相关的可溶性糖含量的快速检测方法,限制了食用花生育种进展。本研究建立了80%乙醇和水浴快速提取花生籽仁可溶性糖的方法,该提取方法与国标法相比,简化了样品前期处理步骤,加快了提取进度。通过准确性和重复性试验对该方法的验证表明,该方法的重复性较好,而且准确有效。以20份花生品种为材料,利用高效液相-示差折光法对该方法提取的样品和国标法提取的样品进行检测发现,成熟花生籽仁中的可溶性糖主要是蔗糖,葡萄糖和果糖很少,2种方法测定的结果差异不显著。利用本研究建立的方法检测20份花生品种的结果显示,蔗糖含量最低为16.19 mg g^-1,最高为83.81 mg g^-1,平均为30.41 mg g^-1。利用国标法检测的结果显示,蔗糖含量最低为15.60 mg g^-1,最高为81.38 mg g^-1,平均为30.20 mg g^-1。这些检测结果,一方面进一步验证了所建立方法的实用性,另一方面也表明这些花生品种中的蔗糖含量差异较大。     

花生籽仁发育过程中糖分积累特征及蔗糖代谢酶活性分析

花生籽仁的含糖量与其食用品质和加工特性密切相关,为了明确花生籽仁发育过程中糖分积累特征以及与蔗糖代谢相关酶活性的关系,以3个不同蔗糖含量的花生品种为材料,分别比较了它们在籽仁发育不同时期可溶性总糖、蔗糖、果糖、葡萄糖含量以及蔗糖磷酸合酶(SPS)、蔗糖合酶(SS)、中性转化酶(NI)、酸性转化酶(SAI)等蔗糖代谢关键酶的活性差异。结果表明不同品种在籽仁发育过程中的糖组分含量及酶活性变化规律相似;无论是合成方向还是分解方向,都以SS活性值相对最高;相关性分析显示,籽仁发育后期蔗糖含量与NI呈极显著负相关,与SPS呈显著正相关。推测可以在花生籽仁趋于成熟时,通过调节NI和SPS活性来提高其蔗糖含量。     

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。     

高产高油花生品种选育概况

花生是我国重要的经济和油料作物,现在我国每年的生产量接近1500万t,离实际每年的需求量1800万t尚有300万t的缺口。据预测:到2020年花生年需求量将达2100万t,而要达到这一目标,就需要在目前生产能力的基础上增长40%以上,就必须从提高花生的单产和增加种植面积来实现。靠大规模扩大花生种植面积来提高总产显然是不符合中国的国情的,只有依靠提高花生的单产来达到提高总产的目的,这就必须培育出产量高的花生新品种。     

花生品种蛋白质含量、含油量及脂肪酸组成的分析

４０００多份花生品种的种子蛋白质含量平均值为２７．４５％，平均含油量为５０．５７％。油酸和亚油酸之和占总脂肪酸的８０％以上。国外引进品种的蛋白质含量和含油量比国内品种的对应值略高。在国内花生品种中，河南品种的平均蛋白质含量最低，平均含油量最高。广东品种的平均蛋白质含量和含油量比山东品种的对应值高。多粒型和珍珠豆型品种的平均蛋白质含量比龙生型和普通型的对应值高，珍珠豆型和中间型品种的平均含油量较高。筛选出高蛋白资源３１７份，高油分资源１８８份，优质脂肪资源５０份。     

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。     

单粒花生主要脂肪酸含量近红外预测模型的建立及其应用

脂肪酸组成是影响花生营养价值和货架寿命的主要因素,高油酸花生以其营养保健价值高、化学稳定性好、耐储藏等特点,深受广大消费者和花生加工企业的喜爱。因此,培育高油酸品种是花生育种的重要目标,建立快速、高效、准确检测花生中主要脂肪酸含量的无损方法是加快花生脂肪酸改良和高油酸品种选育进程的重要技术保障。本研究利用近红外光谱技术建立了可以非破坏性地快速检测单粒花生中油酸、亚油酸、棕榈酸含量的数学模型,其中油酸模型的决定系数(R2)为0.907,均方差为3.463;亚油酸模型的决定系数为0.918,均方差为2.824;棕榈酸模型的决定系数为0.824,均方差为0.782。使用100粒花生验证该模型的准确性,结果油酸、亚油酸和棕榈酸的近红外预测值与化学值的相关系数分别为0.88、0.90和0.71,表明此模型可以准确地预测单粒花生中这3种脂肪酸的含量。本研究借助该模型建立了一种不依赖分子标记的快速、高效选育高油酸花生的方法,并成功应用于高油酸花生育种,选育出高油酸花生品种中花215。     

近红外光谱技术鉴别猪肉和牛肉的研究

本文以近红外光谱分析技术结合模式判别方法建立一种鉴别猪肉和牛肉的方法为目的。采用近红外漫反射光谱法,通过多元散射校正（MSC）、一阶导数加Norris导数平滑点（5,3）处理光谱,波段范围选取5996.42～5805.84,9058.85～8546.36 cm-1,采用TQ Analyst光谱分析软件中的马氏距离设为1建立判别分析模型。结果表明,模型能够准确的鉴别出猪肉、牛肉。因此,近红外光谱技术用于猪肉、牛肉鉴别分析具有可行性。     

Analysis of total glucosinolate content and individual glucosinolates in Brassica spp. by near-infrared reflectance spectroscopy

This study was conducted to test the applicability of near-infrared reflectance spectroscopy (NIRS) for estimating the total glucosinolate (GSL) content in samples of intact seed from a wide range of Brassica species, and to develop calibration equations to estimate simultaneously the percentage of individual GSLs. A total of 290 samples from 15 different Brassica species were scanned by NIRS and analysed for glucosinolate content by high-pressure liquid chromatography (HPLC). A calibration equation for total GSL content was developed using 270 samples of 14 species in a range between 6 and 193μmol/g seed, resulting in an r² of 0.99 in calibration and cross-validation, and 0.95 in independent validation with 20 samples of Brassica rapa, a species not represented in the calibration. Furthermore, calibration equations to estimate the relative amount (mol/mol) of progoitrin, sinigrin, and gluconapin were successfully developed (r² > 0.85 in cross-validation) and validated with samples from species not included in the calibration. It was also possible to discriminate between entries with high and low values of glucoiberin, 4-hydroxyglucobrassicin and glucoerucin.     

Identification of genetic variation in Brassica napus seeds for tocopherol content and composition using near‐infrared spectroscopy technique

Tocopherol is an essential fat‐soluble nutrient for humans. Increasing the tocopherol content in Brassica napus seeds can add value to rapeseed vegetable oil; this has become an important breeding target. However, there is no efficient and non‐destructive method for selecting rapeseed accessions with high tocopherol contents. Here, we report the first near‐infrared reflectance spectroscopy (NIRS)‐based technique for predicting rapeseed tocopherol content. Individual seed tocopherol compositions were estimated from 373 rapeseed genotypes of different origins. This method and chemical methods produced comparable predicted values of the tocopherol constituents in the seeds. Three equations were generated for the prediction of tocopherol content by using a modified partial least squares (MPLS) model. The total tocopherol content for the determination coefficient of cross‐validation (R²_cv) (0.74), determination coefficient (RSQ) (0.76) and one minus the ratio of unexplained variance to total variance (1‐VR) (0.65) values indicates a strong correlation between the calibration and validation sets. Overall, our model confirmed the NIRS method as feasible for predicting tocopherol content in rapeseed and as an efficient screening tool for future breeding programs.     

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。     

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.     

Temperature compensation for near infrared reflectance measurement of apple fruit soluble solids contents

Near infrared reflectance (NIR) spectroscopy has been used successfully to measure soluble solids in apple fruit. However, for practical implementation, the technique needs to be able to compensate for fruit temperature fluctuations, as it was observed that the sample temperature affects the near infrared reflectance spectrum in a non-linear way. Temperature fluctuations may occur in practice because of varying weather conditions or improper conditioning of the fruit immediately after harvest. Two techniques were found well suited to control the accuracy of the calibration models for soluble solids with respect to temperature fluctuations. The first, and most practical one, consisted of developing a global robust calibration model to cover the temperature range expected in the future. The second method involved the development of a range of temperature dedicated calibration models. The drawback of the latter approach is that the required data collection is very large. When no precautions are taken, the error on the soluble solids content reading may be as large as 4%brix.     

花生巢式群体的脂肪含量遗传分析

巢式群体可以利用多个亲本解析复杂性状的遗传机制。本研究利用1个共同亲本与6个基础亲本所配置巢式组合F_2:3家系的种子脂肪含量数据,分析了花生脂肪含量的遗传模型,旨在探明不同的基础亲本组合中脂肪含量性状的遗传差异,为制定脂肪含量遗传改良的亲本选配和后代选择策略提供依据。6个组合的共同亲本为高脂肪含量的普通型大果品种豫花15号,其他6个基础亲本为不同脂肪含量和不同植物学类型的品种。结果表明,在不同杂交组合中脂肪含量的遗传模式有所不同,6个组合分别符合无主基因模型、1对主基因加性显性模型和2对主基因等显性模型3种遗传模式。各种遗传效应的估计值也各不相同,主基因遗传力从32%到80%,说明不同杂交组合中,控制脂肪含量的基因位点差异及其重组和分离方式不同。高脂肪含量双亲杂交后代的高脂肪含量个体较多,但主基因遗传力较低,不宜在早代实施表型选择;双亲脂肪含量差异较大的后代脂肪含量变异幅度更大,能够选择到不同脂肪含量的类型。本研究也表明,巢式组合具有较丰富的脂肪含量变异类型,揭示出脂肪含量性状遗传的复杂性和多基因调控的特点,为较全面地了解脂肪含量的遗传提供了基础。该巢式群体也将有助于进一步开展脂肪含量的QTL定位研究。