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首页> 外文期刊>Journal of near infrared spectroscopy >Near infrared spectroscopy of plantation forest soil nutrients in Sabah, Malaysia, and the potential for microsite assessment
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Near infrared spectroscopy of plantation forest soil nutrients in Sabah, Malaysia, and the potential for microsite assessment

机译:沙巴,马来西亚沙巴林土壤养分的近红外光谱近红外光谱,以及微型材料评估的潜力

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摘要

Knowledge of soil physical and chemical properties is vital to the optimal growing performance of agricultural crops, including plantation forest trees. Near infrared (NIR) spectroscopy has been shown to be a tool that enables rapid and low-cost assessment of soils, however its use in forest plantations has been slow to develop. This study shows the development of calibrations for total organic carbon, total nitrogen and soil pH using a handheld NIR spectrometer for soils at three sites in Sabah, Malaysia. Soil samples were collected, dried, milled and scanned after which they were analysed using standard chemical methods to obtain total organic carbon (TOC) and total nitrogen (TN). Partial least squares regression was used to develop calibrations between reference data and NIR spectra and validated using an independent sample set. The calibration of soil pH is made using a subset of samples across A- and B-horizons for samples from two of the three sites. The most effective spectral pre-treatment was the standard normal variate for TOC and TN while the Savitzky-Golay first derivative was the best pre-treatment for predicting soil pH. Principal component analysis was performed on the raw NIR spectra of all samples to confirm that the samples from different sites were able to be used in a single regression analysis. Kennard-Stone selection was used to create calibration sets and validation sets from the combined spectra from all sites and both soil horizons. Calibrations were also developed independently on the A- and B-horizon samples, but there were insufficient sample numbers to utilize an independent validation set. The coefficients of determination for the validation set (r(p)(2)) were 0.77 and 53 for TOC and TN respectively while the root mean square error of prediction (RMSEP) was 0.44 g 100 g(-1) for TOC and 0.051 g 100 g(-1) for TN. In addition, it showcases the application of these calibrations to provide spatial assessment of two differing micro-sites within a single Eucalyptus pellita progeny breeding trial. Combined with the potential to monitor foliar nutrients, the ability to obtain high spatial details of soil composition will assist tree plantation growers and also other agricultural producers, such as oil palm plantation managers, to better manage their soil and fertiliser regimes.
机译:对土壤物理和化学性质的了解对农作物(包括人工林)的最佳生长性能至关重要。近红外光谱(NIR)已被证明是一种能够快速、低成本地评估土壤的工具,但其在森林种植中的应用发展缓慢。这项研究表明,在马来西亚沙巴的三个地点,使用手持式近红外光谱仪对土壤进行了总有机碳、总氮和土壤pH值的校准。采集土壤样品,干燥、研磨和扫描,然后使用标准化学方法对其进行分析,以获得总有机碳(TOC)和总氮(TN)。偏最小二乘回归用于在参考数据和NIR光谱之间建立校准,并使用独立样本集进行验证。土壤pH值的校准使用三个场地中两个场地的a层和B层样本子集进行。最有效的光谱预处理是TOC和TN的标准正态变量,而Savitzky-Golay一阶导数是预测土壤pH值的最佳预处理。对所有样品的原始NIR光谱进行主成分分析,以确认来自不同地点的样品能够用于单一回归分析。Kennard Stone selection用于根据所有场地和土壤层的组合光谱创建校准集和验证集。校准也在A和B水平样品上独立开发,但没有足够的样品编号来使用独立的验证集。对于TOC和TN,验证集(r(p)(2))的确定系数分别为0.77和53,而对于TOC和TN,预测均方根误差(RMSEP)分别为0.44 g 100 g(-1)和0.051 g 100 g(-1),它展示了这些校准的应用,以在一个单一的厚皮桉子代育种试验中提供两个不同微位点的空间评估。结合监测叶片养分的潜力,获得土壤组成的高空间细节的能力将有助于树木种植园种植者和其他农业生产者,如油棕榈种植园管理者,更好地管理其土壤和肥料制度。

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