کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8973723 | 1552512 | 2005 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Near infrared reflectance spectroscopy (NIRS) to predict biological parameters of maize silage: effects of particle comminution, oven drying temperature and the presence of residual moisture
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کلمات کلیدی
PLSSECNIRDOMDNIRSSNVMPLSSECVPCA - PCAStandard normal variate - استاندارد عادیNear infrared reflectance - انعکاس مادون قرمز نزدیکPartial least squares - حداقل مربعات جزئی Modified partial least squares - حداقل مربعات جزئی جزئی اصلاح شدهstandard error of cross validation - خطای استاندارد اعتبارسنجی متقابلStandard error of calibration - خطای استاندارد کالیبراسیونDrying temperature - دمای خشک شدنResidual Moisture - رطوبت باقی ماندهMaize silage - سیلاغ ذرتNear infrared reflectance spectroscopy - طیف سنجی بازتابی مادون قرمزdry matter - ماده خشک
موضوعات مرتبط
علوم زیستی و بیوفناوری
علوم کشاورزی و بیولوژیک
علوم دامی و جانورشناسی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Near infrared reflectance spectroscopy (NIRS) to predict biological parameters of maize silage: effects of particle comminution, oven drying temperature and the presence of residual moisture Near infrared reflectance spectroscopy (NIRS) to predict biological parameters of maize silage: effects of particle comminution, oven drying temperature and the presence of residual moisture](/preview/png/8973723.png)
چکیده انگلیسی
Maize silage nutritive quality is routinely determined by near infrared reflectance spectroscopy (NIRS). However, little is known about the impact of sample preparation on the accuracy of the calibration to predict biological traits. A sample population of 48 maize silages representing a wide range of physiological maturities was used in a study to determine the impact of different sample preparation procedures (i.e., drying regimes; the presence or absence of residual moisture; the degree of particle comminution) on resultant NIR prediction statistics. All silages were scanned using a total of 12 combinations of sample pre-treatments. Each sample preparation combination was subjected to three multivariate regression techniques to give a total of 36 predictions per biological trait. Increased sample preparations procedure, relative to scanning the unprocessed whole plant (WP) material, always resulted in a numerical minimisation of model statistics. However, the ability of each of the treatments to significantly minimise the model statistics differed. Particle comminution was the most important factor, oven-drying regime was intermediate, and residual moisture presence was the least important. Models to predict various biological parameters of maize silage will be improved if material is subjected to a high degree of particle comminution (i.e., having been passed through a 1 mm screen) and developed on plant material previously dried at 60 °C. The extra effort in terms of time and cost required to remove sample residual moisture cannot be justified.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Animal Feed Science and Technology - Volume 120, Issues 3â4, 28 May 2005, Pages 323-332
Journal: Animal Feed Science and Technology - Volume 120, Issues 3â4, 28 May 2005, Pages 323-332
نویسندگان
D.K. Lovett, E.R. Deaville, D.I. Givens, M. Finlay, E. Owen,