Abstract

AbstractThis study explored a new hand‐held crop growth measuring device to estimate forage quality and quantity of pasture. The device's photosensors (550 nm [green], 650 nm [red] and 880 nm [near‐infrared; NIR] regions of the spectrum) are set up in both upward and downward directions, which shorten the measuring time in the field even under unstable weather conditions. The sward canopy reflectance measurements and forage sampling were conducted at 50 sites of pasture in July 2007 and at 20 sites in the same pasture at 4‐week intervals from May to October in 2006 and 2007. Using the 50‐site dataset, the linear regression analyses between the measured spectral reflectances or the vegetation indices (VIs) and the forage properties were examined to determine the best combinations. Based on the 4‐week interval datasets, the following points were examined: (i) effectiveness of the selected combinations throughout stocking seasons; (ii) influence of the sun angle during the spectral measurement; and (iii) integration of the regression models obtained from each dataset. The relationships between the forage properties (total biomass, green biomass and crude protein mass [CPmass, g dry matter m−2] in natural and logarithmic [ln] forms) and all of the spectral reflectances or VIs were significant in the cross‐validated coefficient of determination (R2CV). In particular, the mean R2CV values between the ln CPmass and each of red/NIR ratio, normalized difference vegetation index and modified soil‐adjusted vegetation index were high (0.74–0.75), ranging from 0.46 to 0.94 throughout the stocking seasons. The influence of the sun angle on the regression models was not significant in 13 cases out of 14. Additionally, in May and October, the integration of the regression models was statistically accepted, respectively. These results demonstrated that the device is effective for estimating forage CPmass throughout stocking seasons with a little effort.

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