Potential of imaging spectroscopy as tool for pasture management

Potential of imaging spectroscopy as tool for pasture management
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成像光谱作为牧场管理工具的潜力

DOI:
10.1111/j.1365-2494.2005.00449.x
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发表时间:
2005
影响因子:
2.4
通讯作者:
G. Kasper
G. Kasper
中科院分区:
农林科学2区
文献类型:
--
作者:
A. Schut;C. Lokhorst;M. Hendriks;J. Kornet;G. Kasper

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评价了利用成像光谱分析技术预测牧草干物质质量、牧草干物质含量、粗纤维含量、灰分、总糖和矿物质(N、P、K、S、Ca、Mg、Mn、Zn、Fe)含量的可行性。该实验系统使用在高空间(0.281·45mm2)和光谱分辨率下测量的404到1650 nm的反射率。两个黑麦草微型牧草试验的数据被用于不同草地危害程度或不同氮肥施用量的试验。对回归模型进行了校准和验证,并估计了多个观测值的预测误差的潜在减少。对干物质质量、干物质含量和氮、总糖、灰分和粗纤维含量的平均预测误差分别为235268 kgHA1、9.616.8g kg1、2.43.4gdm1、16.227.7gdm1、5.86.5gdm1和8.410.4gkgdm1。对磷、钾、S和镁浓度的预测可以识别出缺乏的程度,而对钠、锌、锰和钙的浓度则不能很好地预测。每场25次重复测量,DM质量的预测误差最大可减少到95142千克/公顷。因此,成像光谱分析技术可以为直立牧草干物质质量的准确评估提供一种准确的手段。对常量营养素含量和饲用价值的预测令人满意。该方法需要在实地条件下进一步评估。
The use of imaging spectroscopy to predict the herbage mass of dry matter (DM), DM content of herbage and crude fibre, ash, total sugars and mineral (N, P, K, S, Ca, Mg, Mn, Zn and Fe) concentrations was evaluated. The experimental system used measured reflectance between 404 and 1650 nm at high spatial (0·281·45 mm2) and spectral resolution. Data from two experiments with Lolium perenne L. mini-swards were used where the degree of sward damage or N-fertilizer application varied. Regression models were calibrated and validated and the potential reduction in prediction error with multiple observations was estimated. The mean prediction errors for DM mass, DM content and N, total sugars, ash and crude fibre concentrations were 235268 kg ha1, 9·616·8 g kg1, 2·43·4 g kg DM1, 16·227·7 g kg DM1, 5·86·5 g kg DM1 and 8·410·4 g kg DM1 respectively. The predictions for concentrations of P, K, S and Mg allowed identification of deficiency levels, in contrast to the concentrations of Na, Zn, Mn and Ca which could not be predicted with adequate precision. Prediction errors of DM mass may be maximally reduced to 95142 kg ha1 with 25 replicate measurements per field. It is concluded that imaging spectroscopy can provide an accurate means for assessment of DM mass of standing grass herbage. Predictions of macronutrient content and feeding value were satisfactory. The methodology requires further evaluation under field conditions.
口腔医学杂志。51-4。
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