chalkiness
1.Computer Vision Based Rice Chalkiness Detection Using MATLAB
2.Correlation analyses of chalkiness and other characters in Japonica rice
3.The Relationship Between Chalkiness Formation and Filling Dynamics of Rice Grains
4.Jinshan A-1, a CMS Line of Indica Rice with Aroma and Good Quality and without Chalkiness
5.Rice varieties with higher chalkiness had significant AAC, HPV, CPV, SBV and CSV. (2) RVA profiles characteristics had significant correlation with AAC and GC, but no significant with GT.
6.but the chlorophyll content, the number of headingbranches and spikelets and chalkiness had been comparatively increased. As for LAI, itreduced in period I and rose in periodⅡ.
7.Rice appearance quality trait is mainly referred to grain length (GL), grain width (GW), ratio of length and width (L/W), chalkiness (CH), degree of white core (DWC), milling rice (MR) and transparence (TR).
8.If rice with high translucency and low chalkiness rate had high BDV, low CPV, low SBV and low CSV, their eating quality might be good. Grain length, grain length/width had significant correlation with PaT only.
9.(2) While SWP was ≤-30 kPa, head milled rice was significantly decreased, both the percentage of chalky grain and chalkiness significantly increased. There was a conic relationship between gel consistency and SWP, and no significant difference among treatments in other quality indices, such as kernel shape, amylase and protein content, were found;
10.Application of 1 μmol/L ACC to panicles at mid and late grain filling stages significantly loosened amyloplast arrangement and increased chalky kernel percentage, chalky area and chalkiness of rice, and the results were reversed when 1 μmol/L amino-ethoxyvinylglycine, an inhibitor of ACC synthetic enzyme, was applied to panicles.
