Near Infrared Spectroscopy (NIRS) i

Near Infrared Spectroscopy (NIRS) is a rapid and non-destructive technique, which does not use
chemicals but can simultaneously determine numerous constituents in root crops. Spectrophotometers
are simple to manipulate and the simple spectral collection reduces the risks of operator errors.
However, NIRS is not a stand-alone technology and its performance depends upon the relationships
between the spectral information and an accurate chemical method to measure the constituents of
interest. The major constraint is, therefore, the need to build a reliable equation of prediction, also
called a calibration model. This paper reviews the practical steps involved in the development of a
model, including: 1. the collection of highly variable samples for calibration and validation sets;
2. the production of chemical data for these samples; 3. the collection of spectra on samples from
the calibration and validation sets; 4. the development of the multivariate model; 5. its validation
using descriptive statistics and 6. the monitoring of the model performance. The paper also reviews
recent studies conducted on six root crops, including four tropical species (cassava, sweet potato,
yam and taro) and two temperate (potato and sugar beet). Their results and the perspectives for
further studies are discussed.

ผลลัพธ์ (อังกฤษ) 2:

Near Infrared Spectroscopy (NIRS) is a Rapid and non-Destructive Technique, which does Not Use
Chemicals Can Simultaneously Determine but numerous constituents in root Crops. Spectrophotometers
are Simple to Manipulate and The Simple Spectral Collection Reduces Errors The risks of operator.
However, NIRS is Not a stand-alone ITS Technology and Performance depends upon The Relationships
between The Spectral information and an Accurate Chemical Method to measure The constituents of
interest. The Major constraint is, Therefore, The Need to Build a Reliable Equation of Prediction, also
Called a Model calibration. The Practical Steps Involved in this Paper reviews The Development of a
Model, including: 1. The Collection of samples for calibration and validation sets highly Variable;
2. the production of chemical data for these samples; 3. The Collection of samples from Spectra on
The calibration and validation sets; 4. the development of the multivariate model; 5. ITS validation
using descriptive Statistics and 6. The Monitoring of The Performance Model. The Paper also reviews
recent Studies Conducted on Six root Crops, including Four Tropical Species (Cassava, Sweet Potato,
Yam and Taro) and Two Temperate (Potato and Sugar beet). Their results and The Perspectives for
Further Studies are discussed.