Spectroscopic investigation of the seeds of chilli (<i>Capsicum annum</i>L.)

Barua, Anurup Gohain; Hazarika, Simanta; Pathak, Jumisree Sarmah; Kalita, C. J.

doi:10.1080/09638280701623810

Cited by 12 publications

(4 citation statements)

References 14 publications

(15 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Because the spectral response is linear with analyte concentration, it is possible to develop a calibration (mathematical model) to predict the concentration of an analyte; however, this mathematical model must first be developed using a primary/reference analytical method for the range of concentrations that are of interest for a particular sample. The mathematical model used is usually some form of a linear regression (PCR or PLS); however, neural network algorithms also have been used. − There are only a few examples − of using a Raman based approach for seeds/grain analysis and no reports to apply the methodology to whole intact soybeans. Despite the potential for higher chemical specificity and the availability of data analysis methods, the use of Raman spectroscopy for seed/grain analysis has not been widespread, largely due to a relatively weak Raman signal.…”

Section: Introductionmentioning

confidence: 99%

Protein and Oil Composition Predictions of Single Soybeans by Transmission Raman Spectroscopy

Schulmerich

Gelber

Kong

et al. 2012

J. Agric. Food Chem.

View full text Add to dashboard Cite

The soybean industry requires rapid, accurate, and precise technologies for the analyses of seed/grain constituents. While the current gold standard for nondestructive quantification of economically and nutritionally important soybean components is near-infrared spectroscopy (NIRS), emerging technology may provide viable alternatives and lead to next generation instrumentation for grain compositional analysis. In principle, Raman spectroscopy provides the necessary chemical information to generate models for predicting the concentration of soybean constituents. In this communication, we explore the use of transmission Raman spectroscopy (TRS) for nondestructive soybean measurements. We show that TRS uses the light scattering properties of soybeans to effectively homogenize the heterogeneous bulk of a soybean for representative sampling. Working with over 1000 individual intact soybean seeds, we developed a simple partial least-squares model for predicting oil and protein content nondestructively. We find TRS to have a root-mean-standard error of prediction (RMSEP) of 0.89% for oil measurements and 0.92% for protein measurements. In both calibration and validation sets, the predicative capabilities of the model were similar to the error in the reference methods.

show abstract

Section: Introductionmentioning

confidence: 99%

Protein and Oil Composition Predictions of Single Soybeans by Transmission Raman Spectroscopy

Schulmerich

Gelber

Kong

et al. 2012

J. Agric. Food Chem.

View full text Add to dashboard Cite

show abstract

“…To the weak band at 3509.51 cm -1 in the FTIR spectrum, one could assign the O-H stretching vibration. As no doublet at a separation of approximately 70 cm -1 is evident, the N-H stretching vibration is ruled out (Colthup et al, 1964;Gohain Barua et al, 2008). A strong and broad band in the region 3700-3100 cm -1 is usually due to O-H stretching vibrations in water (Colthup et al, 1964).…”

Section: Resultsmentioning

confidence: 99%

Prediction of Ripening Stage of Cameo Apple Using Fourier-Transform Infrared Spectroscopy

Hazarika

Hebb

Rizvi

2017

International Journal of Fruit Science

Self Cite

View full text Add to dashboard Cite

Traditionally, farmers determine when a crop is ready for harvest by observing sensible attributes. They inspect the color or other physical observables which their crops exhibit and make decisions based on these observations and their past experience. This research presents for the first time a mathematical method employing Fourier-transform infrared spectroscopy to quantify the maturation or ripeness of Cameo apple based on the changes in concentrations of selected constituent components (e.g., glucose) in the apple fruit. Cameo apple fruit samples were collected from a single tree every 15 days during the last 60 days of the apple fruit maturation cycle and then analyzed with Fourier-transform infrared spectroscopy. The vibrational bands from the Fourier-transform infrared spectra were assigned to specific functional group. The peak intensities of the vibrational bands corresponding to glucose molecule were normalized and plotted against the number of days remaining before the apple fruit maturity and were observed to show a linear relationship. This relationship can be used to calculate the time required for the apple fruit to reach maturity and also to calculate the concentration of constituent components at any stage of its growth cycle.

show abstract

“…Ustunda 242 also exploited the sensitivity of polarised EDXRF to assess elemental concentrations in peppermint (Mentha piperita), thyme (Thymus vulgaris) and sumac (Rhus glabra), all plants commonly used in the preparation of Turkish foods. Barua et al 243 used XRF for elemental analysis of the seeds of chilli (Capsicum annum L.), popular as a spice and also used in homoeopathic treatments. Fourier transform Raman and FTIR spectra showed the presence of specific functional groups but ascorbic acid, a vitamin found in chilli peppers was conspicuous by its absence in the seeds.…”

Section: Geological and Industrial Mineralsmentioning

confidence: 99%