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Evaluating maize grain quality by continuous wavelet analysis under normal and lodging circumstances

Evaluating maize grain quality by continuous wavelet analysis under normal and lodging circumstances,10.1016/j.njas.2010.10.011,Njas-wageningen Journa

Evaluating maize grain quality by continuous wavelet analysis under normal and lodging circumstances  
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Root lodging is the most common stress that occurred in maize growing period. It has a great impact on both yield and grain quality. This study aims at developing some leaf level non-contact detecting models with respect to the grain quality of maize plants under lodging and normal circumstances separately, particularly through continuous wavelet analysis (CWT). Field experiments were conducted in Anthesis and Spinning stages, which mainly included an artificial lodging manipulation, to simulate the naturally occurred physical force like windstorm. The hyperspectral measurements of three-ear-leaves were recorded for both normal and lodged plants by the ASD FieldSpec Pro spectrometer. The content of oil, protein and starch in grain was measured by an automated near-infrared grain analyzer. From the result of a two-tailed paired t-test, only the content of protein and starch in spinning stage had significant differences between normal and lodging samples. The spectra data of those samples were further processed with the CWT analysis, which yielded a set of spectral features. The position and scale of those features varied significantly between normal and lodging samples. With the aid of partial least squares (PLS) regression method, the predicting models for each sample were thus established, which also validated against another dataset. Generally, the CWT analysis showed its potential in predicting maize grain quality parameters under both normal and lodging circumstances.
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