scholarly journals Non-invasive assessment of pineapple and mango fruit quality using near infra-red spectroscopy

1997 ◽  
Vol 37 (2) ◽  
pp. 253 ◽  
Author(s):  
J. Guthrie ◽  
K. Walsh
Keyword(s):  
Fruit Quality ◽  
Standard Error ◽  
Monochromatic Light ◽  
Nir Spectroscopy ◽  
Ananas Comosus ◽  
Coefficient Of Determination ◽  
Mango Fruit ◽  
Calibration Equation ◽  
Non Invasive ◽  
Infra Red

Summary. The potential of near infra-red (NIR) spectroscopy for non-invasive measurement of fruit quality of pineapple (Ananas comosus var. Smooth Cayenne) and mango (Magnifera indica var. Kensington) fruit was assessed. A remote reflectance fibre optic probe, placed in contact with the fruit skin surface in a light-proof box, was used to deliver monochromatic light to the fruit, and to collect NIR reflectance spectra (760–2500 nm). The probe illuminated and collected reflected radiation from an area of about 16 cm2. The NIR spectral attributes were correlated with pineapple juice Brix and with mango flesh dry matter (DM) measured from fruit flesh directly underlying the scanned area. The highest correlations for both fruit were found using the second derivative of the spectra (d2 log 1/R) and an additive calibration equation. Multiple linear regression (MLR) on pineapple fruit spectra (n = 85) gave a calibration equation using d2 log 1/R at wavelengths of 866, 760, 1232 and 832 nm with a multiple coefficient of determination (R2) of 0.75, and a standard error of calibration (SEC) of 1.21 °Brix. Modified partial least squares (MPLS) regression analysis yielded a calibration equation with R2 = 0.91, SEC = 0.69, and a standard error of cross validation (SECV) of 1.09 oBrix. For mango, MLR gave a calibration equation using d2 log 1/R at 904, 872, 1660 and 1516 nm with R2 = 0.90, and SEC = 0.85% DM and a bias of 0.39. Using MPLS analysis, a calibration equation with R2 = 0.98, SEC = 0.54 and SECV = 1.19 was obtained. We conclude that NIR technology offers the potential to assess fruit sweetness in intact whole pineapple and DM in mango fruit, respectively, to within 1° Brix and 1% DM, and could be used for the grading of fruit in fruit packing sheds.

scholarly journals Application of commercially available, low-cost, miniaturised NIR spectrometers to the assessment of the sugar content of intact fruit

2000 ◽  
Vol 27 (12) ◽  
pp. 1175 ◽  
Author(s):  
Kerry B. Walsh ◽  
John A. Guthrie ◽  
Justin W. Burney
Keyword(s):  
Light Source ◽  
Standard Error ◽  
Sugar Content ◽  
Smoothing Function ◽  
High Signal ◽  
Narrow Slit ◽  
Non Invasive ◽  
Array Detectors ◽  
Infra Red ◽  
Wavelength Resolution

Recent decreases in costs, and improvements in performance, of silicon array detectors open a range of potential applications of relevance to plant physiologists, associated with spectral analysis in the visible and short-wave near infra-red (far-red) spectrum. The performance characteristics of three commercially available ‘miniature’ spectrometers based on silicon array detectors operating in the 650–1050-nm spectral region (MMS1 from Zeiss, S2000 from Ocean Optics, and FICS from Oriel, operated with a Larry detector) were compared with respect to the application of non-invasive prediction of sugar content of fruit using near infra-red spectroscopy (NIRS). The FICS–Larry gave the best wavelength resolution; however, the narrow slit and small pixel size of the charge-coupled device detector resulted in a very low sensitivity, and this instrumentation was not considered further. Wavelength resolution was poor with the MMS1 relative to the S2000 (e.g. full width at half maximum of the 912 nm Hg peak, 13 and 2 nm for the MMS1 and S2000, respectively), but the large pixel height of the array used in the MMS1 gave it sensitivity comparable to the S2000. The signal-to-signal standard error ratio of spectra was greater by an order of magnitude with the MMS1, relative to the S2000, at both near saturation and low light levels. Calibrations were developed using reflectance spectra of filter paper soaked in range of concentrations (0–20% w/v) of sucrose, using a modified partial least squares procedure. Calibrations developed with the MMS1 were superior to those developed using the S2000 (e.g. coefficient of correlation of 0.90 and 0.62, and standard error of cross-validation of 1.9 and 5.4%, respectively), indicating the importance of high signal to noise ratio over wavelength resolution to calibration accuracy. The design of a bench top assembly using the MMS1 for the non-invasive assessment of mesocarp sugar content of (intact) melon fruit is reported in terms of light source and angle between detector and light source, and optimisation of math treatment (derivative condition and smoothing function).

ESTIMATION OF MICROFIBRIL ANGLE OF INCREMENT CORES BY NEAR INFRARED SPECTROSCOPY

IAWA Journal ◽  
2002 ◽  
Vol 23 (3) ◽  
pp. 225-234 ◽  
Author(s):  
Laurence R. Schimleck ◽  
Robert Evans
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Standard Error ◽  
Near Infrared ◽  
Microfibril Angle ◽  
Nir Spectroscopy ◽  
Radiata Pine ◽  
Coefficient Of Determination ◽  
Increment Core ◽  
Large Numbers

Eight Pinus radiata D. Don (Radiata pine) increment core samples representative of a total of thirty-two increment cores were selected. NIR spectra were obtained from the radial–longitudinal face of each core in 10-mm increments and used to develop a microfibril angle (MFA) calibration. The MFA calibration was developed using seven factors giving an excellent relationship between SilviScan-2 determined MFA and NIR fitted MFA (coefficient of determination (R2) = 0.95) and a standard error of calibration (SEC) of 1.8 degrees.The MFA calibration was used to predict the MFA of NIR spectra obtained in 10-mm sections from the radial–longitudinal face of two intact P. radiata increment cores. NIR predicted MFA was found to be in excellent agreement with MFA determined by SilviScan-2, with R2 of 0.98 (core A) and 0.96 (core B). The standard error of prediction (SEP) for core A (1.0 degree) was much lower than for core B (2.5 degrees). Both sets of predictions closely followed the patterns of MFA radial variation determined by SilviScan-2. NIR spectroscopy provides a rapid method for determining MFA variation in increment cores and is suitable for the routine analysis of large numbers of samples.

scholarly journals Predicting rapeseed oil content with near-infrared spectroscopy

2013 ◽  
Vol 48 (12) ◽  
pp. 1601-1605 ◽  
Author(s):  
Roberta Rossato ◽  
Cássio Egídio Cavenaghi Prete ◽  
César de Castro ◽  
Gilberto Omar Tomm ◽  
Rodrigo Santos Leite ◽  
...  
Keyword(s):  
Rapeseed Oil ◽  
Chemical Method ◽  
Oil Content ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Coefficient Of Determination ◽  
Near Infrared Reflectance ◽  
Calibration Equation ◽  
Sib Families ◽  
The One

The objective of this work was to establish a calibration equation and to estimate the efficiency of near-infrared reflectance (NIR) spectroscopy for evaluating rapeseed oil content in Southern Brazil. Spectral data from 124 half-sib families were correlated with oil contents determined by the chemical method. The accuracy of the equation was verified by coefficient of determination (R²) of 0.92, error of calibration (SEC) of 0.78, and error of performance (SEP) of 1.22. The oil content of ten genotypes, which were not included in the calibration with NIR, was similar to the one obtained by the standard chemical method. NIR spectroscopy is adequate to differentiate oil content of rapeseed genotypes.

Development of near Infrared Analysis of Faeces to Estimate Non-Grass Proportions in Diets Selected by Cattle Grazing Tropical Pastures

2008 ◽  
Vol 16 (5) ◽  
pp. 471-480 ◽  
Author(s):  
David B. Coates ◽  
Rob M. Dixon
Keyword(s):  
Standard Error ◽  
Nutritive Value ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Grass Species ◽  
Infrared Analysis ◽  
Tropical Pastures ◽  
Calibration Equation ◽  
Ruminant Diets ◽  
Modified Formula

Grass (monocots) and non-grass (dicots) proportions in ruminant diets are important nutritionally because the non-grasses are usually higher in nutritive value, particularly protein, than the grasses, especially in tropical pastures. For ruminants grazing tropical pastures where the grasses are C4 species and most non-grasses are C3 species, the ratio of 13C/12C in diet and faeces, measured as δ13C‰, is proportional to dietary non-grass%. This paper describes the development of a faecal near infrared (NIR) spectroscopy calibration equation for predicting faecal δ13C from which dietary grass and non-grass proportions can be calculated. Calibration development used cattle faeces derived from diets containing only C3 non-grass and C4 grass components, and a series of expansion and validation steps was employed to develop robustness and predictive reliability. The final calibration equation contained 1637 samples and faecal δ13C range (‰) of [12.27]–[27.65]. Calibration statistics were: standard error of calibration (SEC) of 0.78, standard error of cross-validation (SECV) of 0.80, standard deviation ( SD) of reference values of 3.11 and R2 of 0.94. Validation statistics for the final calibration equation applied to 60 samples were: standard error of prediction ( SEP) of 0.87, bias of −0.15, R2 of 0.92 and RPD of 3.16. The calibration equation was also tested on faeces from diets containing C4 non-grass species or temperate C3 grass species. Faecal δ13C predictions indicated that the spectral basis of the calibration was not related to 13C/12C ratios per se but to consistent differences between grasses and non-grasses in chemical composition and that the differences were modified by photosynthetic pathway. Thus, although the calibration equation could not be used to make valid faecal δ13C predictions when the diet contained either C3 grass or C4 non-grass, it could be used to make useful estimates of dietary non-grass proportions. It could also be used to make useful estimates of non-grass in mixed C3 grass/non-grass diets by applying a modified formula to calculate non-grass from predicted faecal δ13C. The development of a robust faecal-NIR calibration equation for estimating non-grass proportions in the diets of grazing cattle demonstrated a novel and useful application of NIR spectroscopy in agriculture.

Measurement of the Concentrations of Mannosyl Erythritol Lipid and Soybean Oil in the Glycolipid Fermentation Process Using near Infrared Spectroscopy

2002 ◽  
Vol 10 (1) ◽  
pp. 53-61 ◽  
Author(s):  
Kazuhiro Nakamichi ◽  
Ken-Ichiro Suehara ◽  
Yasuhisa Nakano ◽  
Koji Kakugawa ◽  
Masahiro Tamai ◽  
...  
Keyword(s):  
Soybean Oil ◽  
Ethyl Acetate ◽  
Spectral Data ◽  
Standard Error ◽  
Fermentation Process ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Raw Material ◽  
Second Derivative ◽  
Calibration Equation

In a glycolipid fermentation, mannosyl erythritol lipid (MEL) is produced from soybean oil added to a medium as a source of carbon. A measurement system for the concentrations of MEL and soybean oil in the fermentation process has been developed using near infrared (NIR) spectroscopy. MEL and soybean oil in the culture broth were extracted with ethyl acetate. NIR spectra of the ethyl acetate extract were measured in the wavelength range between 400 and 2500 nm at 2 nm intervals. The absorption caused by MEL was observed at 1436, 1920 and 2052 nm. To obtain a calibration equation, a multiple linear regression (MLR) was carried out between the second derivative NIR spectral data at 2040 and 1312 nm and MEL concentrations obtained using thin-layer chromatography with a flame-ionisation detector (TLC/FID) method. The values of the regression coefficient ( R) and the standard error of calibration ( SEC) were 0.994 and 0.48 g L−1, respectively. The absorption caused by soybean oil was observed at 1208, 1716, 1766, 2182 and 2302 nm. A calibration equation for soybean oil was formulated with the second derivative NIR spectral data at 2178 and 2090 nm. The values of R and SEC were 0.974 and 0.77 g L−1, respectively. After validation of the calibration equation, good agreement was observed between the results of the TLC/FID method and those of the NIR method for both constituents. The values of the correlation coefficient ( r) for MEL and the standard error of prediction ( SEP) were 0.994 and 0.45 g L−1, respectively. The values of r and SEP for soybean oil were 0.979 and 0.56 g L−1, respectively. The NIR method was applied to the measurement of the concentrations of MEL and soybean oil in an actual fermentation process and good results were obtained. The study indicates that NIR spectroscopy is a useful method for the measurement of the raw material and product in glycolipid fermentation.

scholarly journals Histamine Control in Raw and Processed Tuna: A Rapid Tool Based on NIR Spectroscopy

Foods ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 885
Author(s):  
Sergio Ghidini ◽  
Luca Maria Chiesa ◽  
Sara Panseri ◽  
Maria Olga Varrà ◽  
Adriana Ianieri ◽  
...  
Keyword(s):  
Root Mean Square ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Coefficient Of Determination ◽  
Mean Square ◽  
Tuna Fish ◽  
Mean Square Errors

The present study was designed to investigate whether near infrared (NIR) spectroscopy with minimal sample processing could be a suitable technique to rapidly measure histamine levels in raw and processed tuna fish. Calibration models based on orthogonal partial least square regression (OPLSR) were built to predict histamine in the range 10–1000 mg kg−1 using the 1000–2500 nm NIR spectra of artificially-contaminated fish. The two models were then validated using a new set of naturally contaminated samples in which histamine content was determined by conventional high-performance liquid chromatography (HPLC) analysis. As for calibration results, coefficient of determination (r2) > 0.98, root mean square of estimation (RMSEE) ≤ 5 mg kg−1 and root mean square of cross-validation (RMSECV) ≤ 6 mg kg−1 were achieved. Both models were optimal also in the validation stage, showing r2 values > 0.97, root mean square errors of prediction (RMSEP) ≤ 10 mg kg−1 and relative range error (RER) ≥ 25, with better results showed by the model for processed fish. The promising results achieved suggest NIR spectroscopy as an implemental analytical solution in fish industries and markets to effectively determine histamine amounts.

scholarly journals The grades and freshness assessment of eggs based on density detection using machine vision and weighing sensor

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Supakorn Harnsoongnoen ◽  
Nuananong Jaroensuk
Keyword(s):  
Machine Vision ◽  
Vision System ◽  
Low Cost ◽  
Measuring System ◽  
Coefficient Of Determination ◽  
Water Displacement ◽  
Non Invasive ◽  
Future Potential ◽  
Non Destructive ◽  
Egg Freshness

AbstractThe water displacement and flotation are two of the most accurate and rapid methods for grading and assessing freshness of agricultural products based on density determination. However, these techniques are still not suitable for use in agricultural inspections of products such as eggs that absorb water which can be considered intrusive or destructive and can affect the result of measurements. Here we present a novel proposal for a method of non-destructive, non-invasive, low cost, simple and real—time monitoring of the grading and freshness assessment of eggs based on density detection using machine vision and a weighing sensor. This is the first proposal that divides egg freshness into intervals through density measurements. The machine vision system was developed for the measurement of external physical characteristics (length and breadth) of eggs for evaluating their volume. The weighing system was developed for the measurement of the weight of the egg. Egg weight and volume were used to calculate density for grading and egg freshness assessment. The proposed system could measure the weight, volume and density with an accuracy of 99.88%, 98.26% and 99.02%, respectively. The results showed that the weight and freshness of eggs stored at room temperature decreased with storage time. The relationship between density and percentage of freshness was linear for the all sizes of eggs, the coefficient of determination (R2) of 0.9982, 0.9999, 0.9996, 0.9996 and 0.9994 for classified egg size classified 0, 1, 2, 3 and 4, respectively. This study shows that egg freshness can be determined through density without using water to test for water displacement or egg flotation which has future potential as a measuring system important for the poultry industry.

scholarly journals Phytochemical changes in mango fruit in response to Alternaria alternata infection

2018 ◽  
Vol 36 (No. 3) ◽  
pp. 227-232 ◽  
Author(s):  
Jiao Li ◽  
Liangang Mao ◽  
Yanning Zhang ◽  
Lan Zhang ◽  
Hongyun Jiang
Keyword(s):  
Superoxide Dismutase ◽  
Vitamin C ◽  
Fruit Quality ◽  
Alternaria Alternata ◽  
Enzyme Activities ◽  
Phenylalanine Ammonia Lyase ◽  
Titratable Acidity ◽  
Mango Fruit ◽  
Malondialdehyde Content

Changes in mango fruit quality, malondialdehyde content, and enzymatic activities in response to pathogen Alternaria alternata infection were studied. A. alternata significantly affected the appearance of mango fruit at 5 and 7 days after treatment (DAT). The quality of pathogen-infected fruit first showed a significant decrease in titratable acidity and vitamin C content and a significant increase in pH since 3 DAT. The malondialdehyde content was higher than that in the untreated controls at 3 and 7 DAT. The enzyme activities of ascorbate peroxidase and polyphenol oxidase showed significant increases since 3 DAT. Significant increases in l-phenylalanine ammonia-lyase and superoxide dismutase activities were observed at 7 DAT. These results indicate that A. alternata infection first significantly affects some biochemical constituents and enzyme activities in mango fruit since 3 DAT and that there was no significant effect on appearance until 5 DAT.

Guaranteed Sweet or Guaranteed Non–Sweet – Fruit and the Future of Hortical Pty Ltd

2003 ◽  
Vol 9 (2) ◽  
pp. 8-16
Author(s):  
John Jackson
Keyword(s):  
Business Models ◽  
Nir Spectroscopy ◽  
New Product ◽  
New Venture ◽  
Product Service ◽  
First Mover Advantage ◽  
The World ◽  
Infra Red ◽  
Key Issues ◽  
Viable Business

ABSTRACTWe pick up the case as the new venture moves from a decade of dedicated scientific research into the early stages of becoming a commercially viable business. The case considers the potential of the Near Infra Red (NIR) spectroscopy technology to revolutionise the fruit markets of the world as well as the realities of trying to change existing practices and culture. The dilemma of first-mover advantage as compared to learning from the mistakes of early competitors is included. Various possible business models are introduced. The case also asks the students to consider some of the key issues of a new product/service launch.

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