IoT-aware extreme machine learning for efficient health monitoring. [PDF]
Sivakumar NR.
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Prediction of gas chromatographic retention times of narcotic and hazardous drugs in blood using QSRR and machine learning models. [PDF]
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The Effects of Chinese Dwarf Cherry (<i>Cerasus humilis</i>) Kernel Oil on Defecation and the Gut Microbiota in Constipated Mice. [PDF]
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Correction to "Genome-wide association study identifies QTL and candidate genes for grain size and weight in a Triticum turgidum collection". [PDF]
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Black soldier fly larval oil as a renewable substrate for tailored PHA production. [PDF]
Keshaini S, Zainab-L I, Sudesh K.
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iLDA-SGCN: Identifying Associations Between Age-Related Diseases and Long Non-Coding RNAs Using Dual Graph Convolutional Networks. [PDF]
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Kernel size and morphology influence the market value and milling yield of bread wheat (Triticum aestivum L.). The objective of this study was to identify quantitative trait loci (QTLs) controlling kernel traits in hexaploid wheat. We recorded 1000-kernel weight, kernel length, and kernel width for 185 recombinant inbred lines from the cross Rye ...
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Large‐scale breeding population validating significant loci for the 1000‐kernel weight of wheat
Crop ScienceAbstract As an important component of wheat ( Triticum aestivum L.) yield, 1000‐kernel weight (TKW) has played a crucial role in yield improvement in recent decades. Marker‐assisted selection is an effective tool for improving quantitative traits; however, most markers have ...
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The inheritance of plant height, tiller number per plant, spike height and 1000-kernel weight was studied using a Jinks-Hayman diallel analysis in a 8×8 wheat ( Triticum aestivum L.) cross population with the following bread wheat cultivars: Cumhuriyet (1), Kasifbey (2), Ziyabey (3), Marmara (4), Basribey (5), Malabadi (6), Yuregir (7) and Seri-82 (8).
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