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Influence of water on prediction of composition and quality factors: the Aquaphotomics of low moisture agricultural materials

机译:水分对成分和品质因子预测的影响:低水分农业材料的水产学

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摘要

The main constituents of agricultural materials are starch, protein, oil (lipid), cellulose and minerals. These constituents all exist in the molecular state and are constantly in motion, but are essentially functionally static in the raw materials from which foods and feeds are made. It is only when the molecules are brought together by an external medium that brings them into contact with each other in a way in which they can interact more freely, that the molecules are able to create new products. The most important medium is water. Water has a profound influence on the behaviour and the spectra of agricultural commodities. The paper will demonstrate that during the development of near infrared (NIR) calibration models, using several different approaches, the selection of wavelengths in areas where water is known to absorb in the NIR region, is widespread among calibrations for prediction of composition, and functionality in systems in which the moisture content is not high (up to about 15% moisture), and water is not the dominant constituent. Over 200 references have been made to assignments for water in some form, between 700-2200 nm. The influence of water on NIR calibration models for prediction of composition and functionality of materials of even fairly low moisture content is convincing. Evidence is presented in terms of partial least squares loadings for NIR calibration models developed On these materials. The relevance of this is discussed with respect to the possibility of interaction with other absorbers at the same, or adjacent wavelengths. The concept is presented that studies of changes in the intensity and positions of the absorbances of water, and those of other major constituents during development of NIR calibration models, can provide new information on the interaction among these constituents that result in differences in the structure and functionality of the materials, and on the efficiency of NIR analysis.
机译:农业原料的主要成分是淀粉,蛋白质,油(脂),纤维素和矿物质。这些成分均以分子状态存在并不断运动,但在制成食品和饲料的原料中基本上是功能静态的。只有当分子通过外部介质聚集在一起时,它们才能以更自由的相互作用方式相互接触,分子才能产生新产物。最重要的介质是水。水对农产品的行为和光谱具有深远的影响。本文将证明,在开发近红外(NIR)校准模型期间,使用几种不同的方法,在已知NIR区域吸收水的区域中选择波长,在预测组成和功能的校准中广泛使用在水分含量不高(水分含量最高约15%)且水不是主要成分的系统中。在700-2200 nm之间,已经有200多种关于某种形式水的参考文献。令人信服的是,水对NIR校准模型的影响很有说服力,NIR校准模型可预测水分含量相当低的材料的成分和功能。根据在这些材料上开发的NIR校准模型的偏最小二乘方负荷提供了证据。关于与相同或相邻波长处的其他吸收剂相互作用的可能性,讨论了其相关性。提出的概念是,在开发NIR校准模型期间研究水以及其他主要成分的吸光度和强度的变化和位置,可以提供有关这些成分之间相互作用的新信息,这些相互作用会导致结构和结构的差异。材料的功能性以及近红外分析的效率。

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