endosperm mutant
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Genetica ◽  
2020 ◽  
Vol 148 (2) ◽  
pp. 55-68
Author(s):  
Yaya Zou ◽  
Huaping Tang ◽  
Ting Li ◽  
Min Sun ◽  
Xiangru Qu ◽  
...  

Phyton ◽  
2020 ◽  
Vol 89 (4) ◽  
pp. 861-871
Author(s):  
Sen Wang ◽  
Fei Zheng ◽  
Meijing Zhang ◽  
Jun Tu ◽  
Yanping Chen ◽  
...  

Rice Science ◽  
2015 ◽  
Vol 22 (4) ◽  
pp. 162-170 ◽  
Author(s):  
Sheng Zhong-hua ◽  
Fang Peng-fei ◽  
Li San-feng ◽  
Jiao Gui-ai ◽  
Xie Li-hong ◽  
...  

2012 ◽  
Vol 30 (6) ◽  
pp. 1303-1312 ◽  
Author(s):  
Dapeng Zhang ◽  
Jianguo Wu ◽  
Yujiang Zhang ◽  
Chunhai Shi

2011 ◽  
Vol 41 (No. 3) ◽  
pp. 89-95 ◽  
Author(s):  
L. Munck ◽  
B. Møller

Near infrared technology, now widespread in quality control, makes it possible to obtain a total multivariate physical chemical fingerprint of the barley endosperm with high precision. Whole spectroscopic fingerprints of the physics and chemistry of barley seeds can be interpreted by multivariate analysis (chemometrics), by Principal Component Analysis (PCA) for classification and Partial Least Squares Regression (PLSR) for correlation. PCA classification of Near Infrared Reflectance (NIR) spectra can differentiate between mutants and alleles in the lys3 and lys5 loci. PCA on NIR can also be used as a routine in barley breeding to select for a multi-gene quality complex in barley as a whole e.g. increasing starch and reducing fibre content. This is done directly from the PCA classification plot by “data breeding” selecting the recombinants which are approaching the position of the normal high starch controls on the plot. Based on classification of NIR spectra, two alleles in the lys5 locus were characterised as a new class of (1→3,1→4)--glucan compensating starch mutants indicating a metabolic connection between starch and -glucan.  


2004 ◽  
Vol 99 (3) ◽  
pp. 189-201 ◽  
Author(s):  
Isao ARAMAKI ◽  
Ryoko KANDA ◽  
Yukie KIKUNAGA ◽  
Mika YOSHII ◽  
Hiroshi IWATA ◽  
...  

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