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This paper explores the feasibility of particle-based detection and grading of seed vigor based on a self-built seed single-granulation device using near infrared spectroscopy (NIRS). Sweet corn with uniform kernel size was used for this study. The seed samples were divided into three types, they were normal seeds, artificially aged seeds and heat-damaged seeds. A 2-part spectral acquisition of each seed were performed, one for the collection of seeds that fall into the detection zone within the separation pipe, another was on the static platform, whose collection was performed on 5 faces of each seed. Partial least squares discriminant analysis (PLS-DA) was used to classify the original data of the seeds. In the 2 parts, the discriminant results of the unprocessed normal seeds and the artificial accelerated aging seeds, the untreated normal seeds and the heat-damaged seeds showed that classification accuracy was higher than 98%. The research indicates that the spectral data of different positions of seeds can reflect their activity information, and it is feasible to detect and classify seeds in real time in the detection area of the separation pipeline. 相似文献
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基于拐点集合判别的TBUD方法主要思路是分析拐点集合间的关系，并在高维空间进行划分，从而搭建判别模型，并将分析框架应用在特质波动率等若干指标上，利用实证数据得到结论。应用TBUD判别框架可以发现，特质波动率等指标无法对拐点集合进行清晰划分，因而并不具有预测能力。 相似文献
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应用RAPD标记进行茶树优异种质遗传多态性、亲缘关系分析与分子鉴别 总被引：9，自引：0，他引：9
采用RAPD分子标记技术,对茶树优异种质资源的遗传多态性、亲缘关系和分子鉴别进行了研究。结果表明,20个引物在15份优异资源中得到1050个RAPD位点,平均52．5个位点／引物,70个位点／资源。在所获得的137条可重现谱带中,8条是单态的,129条是多态的,多态性程度达94．2％;引物的多态性相对频度为0．24～0．83,总平均为0．47;遗传距离在0．16～0．62之间,平均为0．37,这可能与我国是茶树的原产地和起源中心有密切关系。RAPD数据的类平均法聚类结果显示,15份资源可划分为3个类群,从相似性系数讨论了资源间的亲缘关系。应用12个引物产生的20个特异标记的存在和11个特异的缺失,可以鉴别所有15份优异茶树种质资源。RAPD可以作为茶树优异种质资源遗传多态性、系统演化和分子鉴别研究的有效手段之一。 相似文献
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Feasibility of near infrared spectroscopy for analyzing corn kernel damage and viability of soybean and corn kernels 总被引：1，自引：0，他引：1
Lidia Esteve Agelet David D. Ellis Susan Duvick A. Susana Goggi Charles R. Hurburgh Candice A. Gardner 《Journal of Cereal Science》2012
The current US corn grading system accounts for the portion of damaged kernels, measured by time-consuming and inaccurate visual inspection. Near infrared spectroscopy (NIRS), a non-destructive and fast analytical method, was tested as a tool for discriminating corn kernels with heat and frost damage. Four classification algorithms were utilized: Partial least squares discriminant analysis (PLS-DA), soft independent modeling of class analogy (SIMCA), k-nearest neighbors (K-NN), and least-squares support vector machines (LS-SVM). The feasibility of NIRS for discriminating normal or viable-germinating corn kernels and soybean seeds from abnormal or dead seeds was also tested. This application could be highly valuable for seed breeders and germplasm-preservation managers because current viability tests are based on a destructive method where the seed is germinated. Heat-damaged corn kernels were best discriminated by PLS-DA, with 99% accuracy. The discrimination of frost-damaged corn kernels was not possible. Discrimination of non-viable seeds from viable also was not possible. Since previous results in the literature contradict the current damage-discrimination results, the threshold of seed damage necessary for NIRS detection should be analyzed in the future. NIRS may accurately classify seeds based on changes due to damage, without any correlation with germination. 相似文献
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J. Pinhas V. Soroker A. Hetzroni A. Mizrach M. Teicher J. Goldberger 《Computers and Electronics in Agriculture》2008,63(2):131-139
The red palm weevil (RPW) is a key pest of horticultural and ornamental palm species in Asia, the Middle East and the Mediterranean region, currently dispersing in Mediterranean European countries, endangering the landscape. The RPW larvae bore deep into palm crowns, trunks and offshoots, concealed from visual inspection until the palms are nearly dead. Traded palm trees are intensively transported between and within countries, spreading the pest worldwide. Consequently, an urgent need exists to identify and monitor concealed RPW larvae. Acoustic signals of boring RPW larvae can be recorded from the infested palms using off-the-shelf recording devices, but the resolution of the signals emitted by healthy palms is often difficult to discriminate. The purpose of this research was to develop a mathematical method to automatically detect acoustic activity of RPW in offshoots and implement it in a prototype setup. The methodology applied was similar to techniques used in the field of speech recognition, utilizing Vector quantization (VQ) or Gaussian mixture modeling (GMM). The algorithm successfully achieved detection ratios as high as 98.9%. The study shows that it is feasible to detect RPW sounds using the mathematical method of speech recognition and commercial recording devices, which could be utilized to monitor trade and transportation of offshoots. 相似文献
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《中国油料作物学报(英文)》2020,5(3):121-128
Rapeseed variety needs to be tested by regional trial in multiple sites for many years before being applied in market in China. Performants of rapeseed were affected by the interaction of sites and varieties. Evaluation of regional trials is very important for guiding rapeseed breeding. GGE (genotype main effects and genotype × environment interaction) biplot was used to evaluate yield, stability, adaptability, representativeness and discrimination of national winter rapeseed trials in the upper reaches of Yangtze River in 2017-2018. Results showed that the main effects of genotype (G), environment (E) and genotype × environment interaction (G × E) were significant (P < 0.01) for yield. Among them, E accounted for 46.95% total variation on average, G and G × E accounted for 19.34% and 33.71% respectively. Eight varieties were found with high-yield, excellent stability and adaptability, including ‘Yiyou 29’, ‘Xiwang 920’, ‘Liyouza 108’, ‘Nanyou 546’, ‘Dadi 195’, ‘Jiayou 1’, ‘Huayouza 28’ and ‘Yuhua 2’. Test sites included Nanchong, Mianyang, Wanzhou, Shuangliu and Chengdu in Sichuan Province and Zunyi together with Guiyang in Guizhou Province were selected for their excellent representativeness and discrimination. These results would provide theoretical basis for rapeseed breeding. 相似文献
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One of the most important quality traits in popcorn breeding programs is the popping expansion (PE) capacity of the kernel, which is the ratio of the volume of the popcorn to the weight of the kernel. In this study, we evaluated whether near infrared spectroscopy (NIR spectroscopy) could be used as a tool in popcorn breeding programs to routinely predict and/or discriminate popcorn genotypes on the basis of their PE. Three generations (F1, F2, and F2:3) were developed in three planting seasons by manual cross-pollination and self-pollination. A total of 376 ears from the F2:3 generation were selected, shelled, and subjected to phenotypic analysis. Genetic variability was observed in the F2 and F2:3 generations, and their average PE value was 31.5 ± 6.7 mL g−1. PE prediction models using partial least square (PLS) regression were developed, and the root mean square error of calibration (RMSEC) was 6.08 mL g−1, while the coefficient of determination (RC2) was 0.26. The model developed by principal component analysis with quadratic discriminant analysis (PCA-QDA) was the best for discriminating the kernels with low PE (≤30 mL g−1) from those with high PE (>30 mL g−1) with an accuracy of 78%, sensitivity of 81.2%, and specificity of 72.2%. Although NIR spectroscopy appears to be a promising non-destructive method for assessing the PE of intact popcorn kernels for narrow breeding populations, greater variability and larger sample sizes would help improve the robustness of the predictive and classificatory models. 相似文献
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大兴安岭樟子松火烧死亡判别模型 总被引：5，自引：0，他引：5
通过对大兴安岭地区1987年“5．6”大火后中幼龄樟子松个体死亡情况与火烧状况之间关系的研究,建立了该地区樟子松个体火烧后死亡状况的线性判别模型。判别因子包括个体的树高、胸径、胸高处皮厚、第一枯枝高和树干熏黑高度。模型准确率达80％。 相似文献