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Development of dispersive and Fourier transform near infrared spectroscopy methodology for food and edible seed analysis.

机译:用于食品和食用种子分析的色散和傅立叶变换近红外光谱方法的开发。

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Fast and economical measurements of food composition allow online quality control and chemical analysis in food production. Soybean breeding programs require rapid and accurate composition determinations for large populations through a suitable technique, such as Near Infrared (NIR). Novel calibrations for soy and other health foods were developed with Fourier Transform Near Infrared Reflectance Spectroscopy (FT-NIRS). Accurate calibrations were also developed for soy tofu and soymilk. All major food components protein, fat, moisture and carbohydrates were quantitated. These calibrations are characterized by low standard errors (∼1.0% for protein, fat and moisture) and also by high degrees of correlation (∼99%). The first calibrations for soybean isoflavones reported here were also characterized by low standard errors (0.02%) and high degrees of correlation (∼99%). Improved data processing procedures, novel calibration models and improved high quality calibrations were developed for both whole and ground soybeans with Dual Diode Array NIR Reflectance Spectroscopy. NIR calibrations for total small sugars in whole soybean seeds were developed for the first time. Black seed coat effects on soybean composition were eliminated by measuring ground soybean samples with FT-NIR. Data analysis of 17 different soybean groups indicates that there is a high level of inverse correlation between protein and oil mean contents of soybeans (-R > 0.90). The protein-oil inverse correlations are similarly high for soybean groups with a large number of lines developed over ten years (-R between 0.80 and 0.97), which can be another indicator for consistent and accurate measurements. Validation and evaluation of four new dispersive NIR instruments that are suitable for soybean composition analysis showed that, novel NIR methodology developed over last four years in this research establishes NIR as a secondary analytical method in agriculture and food industry.
机译:快速经济地测量食品成分,可在线进行食品生产中的质量控制和化学分析。大豆育种计划要求通过合适的技术(例如近红外(NIR))对大量种群进行快速准确的成分测定。使用傅立叶变换近红外反射光谱仪(FT-NIRS)开发了用于大豆和其他保健食品的新型校准品。还开发了大豆豆腐和豆浆的精确校准。对所有主要食品成分的蛋白质,脂肪,水分和碳水化合物进行了定量。这些校准的特点是标准误差低(蛋白质,脂肪和水分的<1.0%)和高度相关(〜99%)。本文报道的大豆异黄酮的首次校准还具有低标准误(<0.02%)和高相关度(〜99%)的特征。利用双二极管阵列近红外反射光谱技术为全大豆和磨碎大豆开发了改进的数据处理程序,新颖的校准模型和改进的高质量校准。首次开发了用于整个大豆种子中总小糖含量的NIR校准。通过用FT-NIR测量磨碎的大豆样品,消除了黑种皮对大豆成分的影响。对17个不同大豆类别的数据分析表明,大豆的蛋白质和油平均含量之间存在很高的逆相关性(-R> 0.90)。大豆组的蛋白质与油的逆相关性同样很高,十年来已开发出许多品系(-R在0.80至0.97之间),这可能是一致性和准确测量的另一个指标。对四种适用于大豆成分分析的新型分散式近红外光谱仪的验证和评估表明,本研究近四年来开发的新型近红外光谱法将近红外光谱法确立为农业和食品行业的辅助分析方法。

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