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Use of a hand-held crop growth measuring device to estimate forage crude protein mass of pasture

机译:使用手持式农作物生长测量装置估算牧场的粗饲料粗蛋白质量

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This study explored a new hand-held crop growth measuring device to estimate forage quality and quantity of pasture. The device's photosensors (550nm [green], 650nm [red] and 880nm [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 (R-CV(2)). In particular, the mean R-CV(2) 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.
机译:这项研究探索了一种新型的手持式农作物生长测量装置,以估算草料的草料质量和数量。该设备的光传感器(光谱的550nm [绿色],650nm [红色]和880nm [近红外; NIR]区域)设置在上下两个方向,即使在不稳定的天气条件下,也可以缩短现场的测量时间。从2006年5月至10月,在2007年7月对牧场的50个地点和同一牧场的20个地点进行了草冠层反射率测量和草料采样,间隔时间为4周(2006年和2007年)。使用50个地点的数据集,进行线性回归对测得的光谱反射率或植被指数(VI)与草料特性之间的分析进行了分析,以确定最佳组合。根据4周间隔数据集,检查了以下几点:(i)在整个放养季节中选定组合的有效性; (ii)在光谱测量过程中太阳角的影响; (iii)整合从每个数据集中获得的回归模型。牧草特性(总生物量,绿色生物量和天然和对数[ln]形式的粗蛋白质量[CPmass,g干物质m(-2)])与所有光谱反射率或VI之间的关系都很显着验证的确定系数(R-CV(2))。特别是,ln CPmass与红色/近红外比率,归一化差异植被指数和改良土壤调整植被指数中的每一个之间的平均R-CV(2)值较高(0.74-0.75),整个期间范围从0.46至0.94。备货季节。在14个案例中,有13个案例中太阳角度对回归模型的影响不显着。此外,在5月和10月,分别在统计学上接受了回归模型的整合。这些结果表明,该设备只需花费很少的精力,就可以有效地估算整个放养季节的饲草CPmass。

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