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首页> 外文会议>Annual Australian Society of Sugar Cane Technologists Conference >DEVELOPMENT OF NEAR INFRARED (NIR) SPECTROSCOPIC METHODS TO PREDICT CARBON, NITROGEN, SILICON, PHOSPHORUS AND POTASSIUM LEVELS IN MILL BY-PRODUCTS
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DEVELOPMENT OF NEAR INFRARED (NIR) SPECTROSCOPIC METHODS TO PREDICT CARBON, NITROGEN, SILICON, PHOSPHORUS AND POTASSIUM LEVELS IN MILL BY-PRODUCTS

机译：近红外（NIR）光谱法的研制预测碳，氮，硅，磷和钾水平的研磨副产物

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Mill by-products have been utilised on cane farms as a nutrient source and soil ameliorant for many years; however, the nutrient content is not usually measured on a regular basis. Concerns exist over the long term application of mill mud and ash without appropriate product monitoring, but these can be at least partially addressed by developing simple, rapid measurement techniques that can be employed at the sugar mill. This paper presents near infrared (NIR) spectroscopic methods for the predictionof nutrient elements: carbon (C), nitrogen (N), silicon (Si), phosphorus (P) and potassium (K) levels in mill mud and mixed mill mud/ash by-products. Eighty eight mill mud and mud/ash samples were obtained from three sugar mills in the Mackay region across two crushing seasons. Each sample was analysed using standard chemical methods for C, N, Si, P and K and also had an NIR scan recorded on the wet sample prior to preparing the sample for subsequent laboratory analysis. Partial Least Squares (PLS) regression models were constructed for each constituent. High R2 values were obtained for correlations between NIR predicted results and laboratory results for all components, with values ranging from 0.890 to 0.962, together with very good standard errors of cross validation (SECV). This early work has confirmed that NIR calibrations can be developed for the measurement of nutrient elements in mill by-products. The technique once implemented will provide benefits for both millers and growers and additionally will address pressing environmental requirements.
机译：在甘蔗农场中被用作营养农场作为营养源和土壤改良剂多年来的碾磨剂;然而，营养含量通常通常是定期测量的。在没有适当的产品监测的情况下，在轧机泥和灰的长期应用中存在担忧，但是通过开发可在糖厂采用的简单快速测量技术，这些可以至少部分地解决。本文介绍了用于预测营养素的红外线（NIR）光谱法：碳（C），氮（N），硅（Si），磷（Si），磷（P）和钾（K）水平在研磨泥和混合磨机泥浆/灰分中副产品。在两个破碎季节的麦田地区的三种糖厂获得了八十八毫米泥浆和泥浆/灰样品。使用C，N，Si，P和K的标准化学方法分析每个样品，并且在制备随后的实验室分析之前，还在湿样品上记录湿样品上的NIR扫描。为每个组成部分构建局部最小二乘（PLS）回归模型。获得高R2值，用于所有组分的NIR预测结果和实验室结果之间的相关性，值范围为0.890至0.962，以及非常好的交叉验证标准误差（SECV）。这项早期工作证实，可以开发NIR校准用于测量磨机副产物中的营养素。该技术一旦实施，将为米勒和种植者提供益处，另外将解决压力环境要求。

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