Chlorotrimethylsilane, a reagent for the direct quantitative analysis of fats and oils present in vegetable and meat samples

Acylglycerides present in oil seeds and meat can be transformed into volatile fatty esters using chlorotrimethylsilane (CTMS) and 1-pentanol as reagents. The volatile esters can then be analysed by GC. The method is quantitative and involves only minor sample manipulation. It often permits major recoveries of the total saponifiable lipids present in solid samples. A 40 min reaction time is enough to ensure the total conversion of saponifiable lipids to the corresponding FAPEs.     

小茴香超临界CO_2萃取产物脂肪酸成分分析

通过脂肪酸的衍生化处理，再利用色谱（GC）和色谱一质谱（GC－MS）等分析手段，对小茴香超临界CO2萃取产物的脂肪酸成分进行了剖析，共鉴定出九种脂肪酸，其中，十八碳一烯酸、十八碳二烯酸和棕榈酸是其主要成分，分别占脂肪酸总量的75．12％、15．18％和5．34％．     

Studies on the methods of identification of irradiated food I. Seedling growth test

A seedling growth test for the identification of gamma irradiated edible vegetable seeds was described. The identification of gamma irradiated grape and the other seeds has been investigated. The purpose of this study was to develop an easy, rapid and practical technique for the identification of irradiated edible vegetable seeds. Seven different irradiated edible vegetable seeds as: rice ( ), peanut ( ), maize ( ), soybean ( ), red bean ( ), mung bean ( ) and catjang cowpea ( ) were tested by using the method of seedling growth. All of the edible vegetable seeds were exposed to gamma radiation on different doses, O(CK), 0.5, 1.0, 1.5, 2.0, 3.0, 5.0 kGy. After treatment with above 1.0 kGy dose to the seeds, the seedling rate was less than 50% compared with the control. Although the seedling rate of rice seeds can reached 58%, the seedling growth was not normal and the seedling leaves appeared deformed. The results by this method were helpful to identify gamma treatment of the edible vegetable seeds with above 1.0 kGy dose.     

Log-det approximation based on uniformly distributed seeds and its application to Gaussian process regression

Maximum likelihood estimation (MLE) of hyperparameters in Gaussian process regression as well as other computational models usually and frequently requires the evaluation of the logarithm of the determinant of a positive-definite matrix (denoted by C hereafter). In general, the exact computation of is of O(N³) operations where N is the matrix dimension. The approximation of could be developed with O(N²) operations based on power-series expansion and randomized trace estimator. In this paper, the accuracy and effectiveness of using uniformly distributed seeds for approximation are investigated. The research shows that uniform-seed based approximation is an equally good alternative to Gaussian-seed based approximation, having slightly better approximation accuracy and smaller variance. Gaussian process regression examples also substantiate the effectiveness of such a uniform-seed based log-det approximation scheme.     

A New Abeotaxane Diterpenoid from the Seeds of Taxus mairei

Phytochemical investigation on the methanolic extracts of the Taxus mairei seeds resulted in the isolation of a new abeotaxane diterpenoid. The structure was characterized as 2α, 5α, 13α-trihydroxy-7β, 10β-diacetoxy-2(3→20)abeotaxa-4(20), 11- dien-9     

基于近红外光谱的粳稻种子快速鉴别方法研究

黑龙江省是我国最大的粳稻产区和商品粮生产基地。水稻种植过程中,选择合适的水稻品种是实现高产的关键环节。在农业生产中,水稻品种的选择受多方面因素影响,一般说来,同一积温带所种植的不同水稻品种在外观上差别不大,甚至没有差别,很难通过肉眼观察进行准确区分。为了快速鉴别肉眼不便区分的不同类别粳稻种子,提出了一种基于近红外光谱技术的粳稻品种快速无损鉴别方法。以黑龙江垦区大量种植的3种不同品种的粳稻种子（垦粳5号、垦粳6号和绥粳4号）作为研究对象,每个品种选取40个样本,其中30个样本做为建模集,10个样本作为预测集,扫描获取全部120个样本的近红外光谱数据。对原始光谱数据（11 520～4 000 cm-1）两端进行裁剪,选取吸光度较强的8 250～5 779cm-1范围内的光谱数据进行研究。首先建立参照模型,即直接对光谱数据建立BP模型1, 同时光谱数据经过一阶导数和Savitzky-Golay平滑预处理后建立BP模型2。模型1的分类正确率为93.3%,预测集均方根误差RMSEP=0.232 8,迭代时间t=3 882.9 s。模型2的分类正确率为100%,RMSEP=0.070 6,迭代时间t=954.5 s。比较两种模型的评价参数RMSEP发现FD+SG预处理可以提高模型的预测能力,但是由于两种模型未进行降维处理,数据量过大,模型的输入节点过多,迭代时间太长,不利于实际应用。因此利用小波变换多分辨率的特点对数据进行降维处理,采用预测集残差平方和Press值作为评价指标,在多个小波类别和参数中选取分解尺度为5的sym2（symlet2）小波对光谱数据进行压缩和降维处理,将光谱数据由601维降到21维。以小波变换结果作为神经网络输入,建立模型3,并与模型1比较,模型3的分类正确率为93.3%, RMSEP=0.225 0, 迭代时间t缩短至198.9 s,比较结果显示小波降维可以减少神经网络的输入,简化神经网络的结构,从而提高迭代速度,但对提高模型的预测能力效果不明显。上述三种模型比较结果表明,FD+SG预处理可以提高模型的预测能力,小波降维可以提高模型的迭代速度,综合上述三种模型的比较结果分析,最终建立“FD+SG+小波降维”的21输入、15个隐层、3个输出的神经网络鉴别模型4,其分类正确率达100%,RMSEP=0.029 3, 迭代时间为98.8 s,表明模型4能够完全实现对三种不同水稻品种的快速、准确、无损鉴别。因此,所提出的基于近红外光谱的小波降维和反向传播人工神经网络鉴别模型的方法完全可以用于粳稻种子的快速无损鉴别,同时也为其他农作物种子的快速鉴别提供了参考。     

利用热像与生理实验法研究种子的优化传热传质

本文运用工程热物理和种子生理学科交叉的研究方法，在辐射振动流化干燥装置中，对白菜种子的动、静态干燥进行了热象测试分析，并且同步进行了种子的生理实验研究．结果表明种子的临界干燥温度是干燥时间和含水率的函数，当含水率较低及干燥周期较短时，种子的临界干燥温度可以提高，为种子的优化传热传质提供了理论依据．     

高静水压对水稻种子萌发及同工酶的影响

 利用不同静水压力和不同保压时间处理了籼稻粤香占种子，研究发现，随着压力的增加和保压时间的延长，水稻发芽率和成苗率明显下降，高压处理后的水稻在苗期的生长受到明显抑制，大约生长30 d株高才赶上对照；聚丙烯酰胺凝胶电泳显示高静水压力抑制了种子幼苗的酯酶（Esterase）同工酶的表达，但对其它几种同工酶如过氧化物酶（Peroxidase）、超氧化物歧化酶（Superoxider Dismutase）和苹果酸酶（Malic Enyme）等影响较小。利用同一压力和保压时间处理，不同类型的水稻（Oryza sativa L.）品种种子，其中包括籼稻（粤香占和南京11）、粳稻（秋光和台中65）和中间类型Bulu稻（Bulu Gendjah 和Bulu Rusa），结果发现所有类型水稻种子的发芽率和成苗率都显著降低，但因水稻类型的不同其影响程度也不同，籼型水稻南京11和粤香占的耐压性最弱，粳型水稻秋光和台中65最强，中间型Bulu水稻Bulu Gendjah和 Bulu Rusa居中。上述结果表明，静水高压能够显著降低水稻的种子的发芽率和成苗率，抑制幼苗前期的生长和酯酶同工酶的表达。     

微量注射进样导数火焰原子吸收法测定油料作物中铅锌

采用微量注射进样导数火焰原子吸收法测定油料作物黄豆、花生、葵花子和芝麻中铅、锌含量,采用导数测量系统使检测灵敏度提高了5.6～8倍,检出限改善了8.8～10.5倍,经测定,黄豆、花生、葵花子、黑芝麻、白芝麻中铅含量分别为:4.638,3.420,1.076,0.304,1.996μg·g~(-1),锌含量分别为:34.72,28.69,64.61,20.55,18.97μg·g~(-1)。方法的灵敏度、检出限、相对标准偏差分别为:铅:0.0522,0.242μg·mL~(-1),3.50％,锌:0.0131,0.000452μg·mL~(-1),2.9％。     

Effect of amorphous seeds on the crystallization kinetics of Na-A zeolite

The formation of crystal nuclei occurs when alkaline aluminosilicate gels are treated at temperatures below the crystallization temperature or during crystallization of gels rather than during precipitation of the gels. The linear growth rate of the crystals of Na-A zeolites yielded by alkaline aluminosilicate gels in the presence of amorphous seeds is a function of the product of the concentrations of the silicate and aluminate ions in the intermicellar liquid.Translated fromIzvestiya Akademii Nauk. Seriya Khimicheskaya, No. 5, pp. 799–804, May, 1994.