Spectroscopic Quantitative Analysis

Duckworth, James

doi:10.1016/b978-012764070-9/50006-8

Cited by 38 publications

(28 citation statements)

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“…The common way of assessing statistical indicators such as R 2 and RMSE is to divide the data set into training and test sets and predict the response variable from the test data set (in this study n = 64) using models developed from the training data set (in this study n = 127). Using a completely different and independent test data set to test the model's performance is important in determining a model's long-term stability (Duckworth, 1998). However, it should also be noted that an arbitrary division of data sets into calibration and validation samples may lead to strongly biased results (Atzberger et al, 2003b).…”

Section: Validationmentioning

confidence: 98%

LAI and chlorophyll estimation for a heterogeneous grassland using hyperspectral measurements

Darvishzadeh¹,

Skidmore²,

Schlerf³

et al. 2008

ISPRS Journal of Photogrammetry and Remote Sensing

360

271

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Section: Validationmentioning

confidence: 98%

LAI and chlorophyll estimation for a heterogeneous grassland using hyperspectral measurements

Darvishzadeh¹,

Skidmore²,

Schlerf³

et al. 2008

ISPRS Journal of Photogrammetry and Remote Sensing

360

271

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“…Another environment was located on a lowland site underlain by a Nodaway Silt Loam (fine-silty, mixed, superactive, nonacid, mesic, Mollic Udifluvent) at the Horticulture and Agroforestry Research Center near New Franklin, MO (39°0¢ N, 92°12¢ W). Calibration equations were developed by regressing spectra of these 120 samples against their corresponding chemical data; the regression method was modified partial least squares regression (Duckworth, 1998;Shenk and Westerhaus, 1991). This site flooded to a depth of 0.2 m for eight continuous days in August 2008 when sorghum varieties were at approximately samples were selected for calibration development (Shenk and Westerhaus, 1991) and analyzed for CP and IVTD.…”

Section: Sites and Sweet Sorghum Production Conditionsmentioning

confidence: 99%

Evaluation of Sweet Sorghum Bagasse as an Alternative Livestock Feed

2013

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Recently, sweet sorghum [Sorghum bicolor (L) Moench] has garnered renewed attention as a promising feedstock for ethanol production. A byproduct of this is bagasse, which is sweet sorghum stalks remaining after juice extraction. It is possible that sweet sorghum bagasse could provide a source of livestock feed and that its nutritive value could be increased by ammoniation. Ammoniation refers to the treatment of low‐quality forages with NH3 to improve crude protein concentration, digestibility, and animal intake. The main objective of this study was to evaluate sweet sorghum bagasse as a livestock feed and determine the effect of ammoniation on in vitro true digestibility (IVTD) and crude protein (CP) of sweet sorghum bagasse. In vitro true digestibility and CP were determined on bagasse of 12 sweet sorghum cultivars grown in three environments and treated with and without anhydrous NH3 (39.0 g kg−1). Across environments, ammoniation increased bagasse IVTD from a mean of 731 g kg−1 dry matter (DM) to a mean of 750 g kg−1 DM, but IVTD of bagasse from only two of three environments was increased. Crude protein averaged 117 g kg−1 DM for ammoniated samples compared to 26 g kg−1 DM for nontreated samples. Ammoniation increased CP in every cultivar and in every environment. Sweet sorghum bagasse IVTD and CP characteristics combined with large yields indicate that this byproduct could serve as livestock feed and merits further investigation.

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“…The use of a wider spectral range may be considered advantageous in that many more spectral responses are used in the calibration model [55]. The differences in the spectral range used may be related to the scattering of powders and tablets.…”

Section: Calculation Of Calibration Model and Evaluationmentioning

confidence: 99%

A Procedure for Developing Quantitative Near Infrared (NIR) Methods for Pharmaceutical Products

Romañach

Román-Ospino

Alcalà

2016

Methods in Pharmacology and Toxicology

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The pharmaceutical industry uses procedures to describe all the instructions needed to perform a process in a consistent manner. Procedures are based on process knowledge and the desire to consistently meet desired specifications. This chapter proposes a procedure for the development of NIR partial least squares (PLS) calibration models for pharmaceutical applications. The chapter captures the lessons learned for more than a decade in studies where NIR spectroscopy has been used for quantitative determinations of drug concentration, moisture, polymorphs, and other important applications. Two examples of recent initiatives to develop NIR calibration models in a more efficient manner reducing the number of calibration samples are also discussed. The procedure differs from previously published guidelines since it is based on specific examples of method validations for pharmaceutical processes and provides clear instructions for method development and validation. The procedure and tutorial should advance the implementation of near infrared spectroscopic (NIRS) quantitative methods in the pharmaceutical industry.

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Spectroscopic Quantitative Analysis

Cited by 38 publications

References 0 publications

LAI and chlorophyll estimation for a heterogeneous grassland using hyperspectral measurements

LAI and chlorophyll estimation for a heterogeneous grassland using hyperspectral measurements

Evaluation of Sweet Sorghum Bagasse as an Alternative Livestock Feed

A Procedure for Developing Quantitative Near Infrared (NIR) Methods for Pharmaceutical Products

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