Revolutionising Fish Ageing: Using Near Infrared Spectroscopy to Age Fish

The project aimed to evaluate the innovative application of NIRS as a reliable, repeatable, and cost-effective method of ageing fish, using otoliths of Barramundi and Snapper as study species. Specific research questions included assessing how geographic and seasonal variation in otoliths affects NIRS predictive models of fish age, as well as how the NIR spectra of otoliths change in the short-term (i.e., <12 months) and long-term (i.e., historical otolith collections) and what effect this has on the predictive ability of NIRS models. The cost-effectiveness of using NIRS to supplement standard fish ageing methods was also evaluated using a hypothetical case study of Barramundi

Novel method for shark age estimation using near infrared spectroscopy

Accurate age determination is an important component of assessing and managing fish populations, yet traditional ageing using growth bands is time-consuming and has limitations. In the present study, an alternative approach to shark age estimation using near infrared spectroscopy (NIRS) was investigated using two species. The ages of Sphyrna mokarran and Carcharhinus sorrah vertebrae that had been traditionally aged and validated were successfully predicted up to 10 years of age using NIRS. The correlations between the known ages of the vertebrae and their near infrared spectra were strong, with R2 values of 0.89 and 0.84 for S. mokarran and C. sorrah respectively. The major advantage of the NIRS ageing approach was the rapid speed of age estimation, which could enable large numbers of sharks to be aged quickly. This would offer the fisheries management benefit of improving the reliability of age information for stock and risk assessments

Near infrared spectroscopy as a rapid, non-invasive method for sandalwood oil determination

Fourier Transform (FT) - near infra-red spectroscopy (NIRS) was investigated as a non-invasive technique for predicting -santalol content in sandalwood chip samples. The correlation between the NIR spectral data and the a-santalol content from the GC-MS analysis was very high (R2 = 0.93). The feasibility study indicates that it is possible to use FT-NIRS to predict -santalol content in sandalwood chip samples. The technique of utilising NIRS technology for sandalwood quality and quantity determination needs to be further developed to be utilised as a tool for commercial applications

The application of FT-NIRS for the detection of bruises and the prediction of rot susceptibility of ‘Hass’ avocado fruit

BACKGROUND: A rapid non-destructive in-line grading system that can rapidly and accurately assess individual avocado fruit for internal quality attributes, including bruises and rots, would allow the avocado industry to provide a more consistent fruit quality to the consumer, optimise market distribution and ensure maximum yield for the producer and retailer. Fourier transform–near-infrared (FT-NIR) spectroscopy was investigated to detect bruises and rot susceptibility as an indication of shelf-life in avocado fruit at both the sprung stage of ripeness and eating ripe fruit. RESULTS: The classification models (principal component linear discriminant analysis, partial least squares discriminant analysis and support vector machine) for each of three growing seasons found hard green fruit that were deliberately bruised could be correctly detected with 70–78% accuracy after 2–5 h following impact damage and with 83–89% accuracy after 24 h. For eating ripe fruit, the accuracy was 60–100% after 2–5 h following impact damage and 66–100% after 24 h. The ability of the classification models to accurately predict rot development into two classes, ≤10% and >10% of flesh affected, ranged from 65% to 84% over the three growing seasons. When the rot classes were defined as ≤30% and >30% the accuracy was 69–77%. CONCLUSIONS: The results of the study highlight the potential of FT-NIR reflectance spectroscopy for application in a commercial, in-line setting for the non-destructive evaluation of impact damage and rot susceptibility of whole avocado fruit. The study indicates that fruit should be held for approximately 24 h prior to scanning to allow bruise development to occur, particularly in hard fruit (i.e., stage 2) prior to bruise assessment. © 2018 Society of Chemical Industry. © 2018 Society of Chemical Industr

Near Infrared Spectroscopy as a rapid method\ud for sandalwood oil determination

The remaining chips from 295 sandalwood (S. austrocaledonicum) cores previously\ud analysed using GC-MS were scanned using Near infrared Spectroscopy\ud (NIRS). The correlation between the NIR spectral data and the a-santalol content\ud from the GC-MS analysis was very high (R2 = 0.9258). Such a high correspondence\ud between these two techniques indicates that it is possible to use NIRS to\ud predict a-santalol content in sandalwood chip samples. The relative advantages\ud of using NIRS for quantifying a-santalol content in raw sandalwood is discussed\ud in terms of its rapid and potentially inexpensive application to quality control for\ud processing and breeding new cultivars

Near Infrared Spectroscopy as a rapid non-invasive tool for agricultural management

Near Infrared Spectroscopy (NIRS) is a non-invasive method of measuring internal/external quality and safety attributes of agricultural products using optical light to determine chemical composition. The technology offers the advantage of being non-destructive, fraction of a second per test, with the potential to test every piece of product in an in-line application for various internal/external attributes simultaneously. Such technologies may also be utilised as tools for quality and sustainable management in the production environment. Field applications for soil and crop management would enable the primary producer to readily monitor individual plants and orchard/crop quality regularly for breeding programs, assist in water and fertilizer management and allow the primary producer to make informative decisions to achieve final product specifications.\ud \ud The aim of this study was to assess the potential of Fourier Transform (FT) NIRS as an objective and non-invasive tool in the agricultural environment. Avocado maturity was selected for this purpose as commercial avocado maturity estimation is currently based on destructive assessment of the percentage dry matter (DM), and sometimes percent oil, both of which are highly correlated with maturity. This study demonstrated the ability of FT-NIRS as a noninvasive method to predict Hass avocado maturity based on DM content and its ability to predict over different geographical locations

Non-invasive assessment of internal quality attributes of whole avocado fruit by NIRS

The utility of Fourier Transform (FT) - near infra-red\ud spectroscopy (NIRS) was investigated as a non-invasive\ud technique for estimating percentage dry matter (%DM) of whole intact ‘Hass’ avocado fruit. Partial least square (PLS) regression models were developed from the diffuse reflectance spectra to predict %DM, taking into account effects of intra-seasonal variation and orchard conditions. The study found that combining three harvests (early, mid and late seasons) yielded a predictive model for %DM with Rv\ud 2=0.86, root mean square error of prediction (RMSEP)=1.18% for the DM in the range 18.2 – 35.0%. These results indicate the potential of FT-NIRS, in diffuse reflectance mode to non-invasively predict the %DM (and thus internal fruit quality) of whole ‘Hass’ avocado fruit

Prediction of hass avocado maturity via FT-NIRS

Most commercial quality classification systems for fruit and vegetables are based on external\ud features of the product, for example: shape, colour, size, weight and blemishes. For avocado fruit,\ud external colour is not a maturity characteristic. Also its smell is too weak, and appears later in its\ud maturity stage.1 Because maturity is a major component of avocado quality and palatability, it is\ud important to harvest mature fruit, so as to ensure that fruit will ripen properly and have acceptable\ud eating quality. Currently, commercial avocado maturity estimation is based on destructive\ud assessment of the percentage of Dry Matter (%DM), and sometimes percent oil, both of which\ud are highly correlated with maturity.2, 3 A rapid and non-destructive system that can accurately and\ud rapidly monitor internal quality attributes would allow the avocado industry to provide better,\ud more consistent eating quality fruit to the consumer, and thus improve industry competitiveness\ud and profitability.\ud The aim of this study was to assess the potential of FT-NIR diffuse reflectance spectroscopy as\ud an objective non-invasive method to determine Hass avocado maturity and thereby eating quality,\ud based on %DM, and its ability to predict over several growing seasons

Effects of seasonal variability on FT-NIR prediction of dry matter content for whole Hass avocado fruit

Fourier Transform (FT)-near infra-red spectroscopy (NIRS) was investigated as a non-invasive technique for estimating percentage (%) dry matter of whole intact 'Hass' avocado fruit. Partial least squares (PLS) calibration models were developed from the diffuse reflectance spectra to predict % dry matter, taking into account effects of seasonal variation. It is found that seasonal variability has a significant effect on model predictive performance for dry matter in avocados. The robustness of the calibration model, which in general limits the application for the technique, was found to increase across years (seasons) when more seasonal variability was included in the calibration set. The Rᵥ² and RMSEP for the single season prediction models predicting on an independent season ranged from 0.09 to 0.61 and 2.63 to 5.00, respectively, while for the two season models predicting on the third independent season, they ranged from 0.34 to 0.79 and 2.18 to 2.50, respectively. The bias for single season models predicting an independent season was as high as 4.429 but ≤ 1.417 for the two season combined models. The calibration model encompassing fruit from three consecutive years yielded predictive statistics of Rᵥ² = 0.89, RMSEP = 1.43% dry matter with a bias of -0.021 in the range 16.1-39.7% dry matter for the validation population encompassing independent fruit from the three consecutive years. Relevant spectral information for all calibration models was obtained primarily from oil, carbohydrate and water absorbance bands clustered in the 890-980, 1005-1050, 1330-1380 and 1700-1790 nm regions. These results indicate the potential of FT-NIRS, in diffuse reflectance mode, to non-invasively predict the % dry matter of whole 'Hass' avocado fruit and the importance of the development of a calibration model that incorporates seasonal variation

Robustness of NIR calibrations for soluble solids in intact melon and pineapple

The soluble solids content of intact fruit can be measured non-invasively by near infrared spectroscopy, allowing “sweetness” grading of individual fruit. However, little information is available in the literature with respect to the robustness of such calibrations. We developed calibrations based on a restricted wavelength range (700–1100 nm), suitable for use with low-cost silicon detector systems, using a stepwise multiple linear regression routine. Calibrations for total soluble solids (°Brix) in intact pineapple fruit were not transferable between summer and winter growing seasons. A combined calibration (data of three harvest dates) validated reasonably well against a population set drawn from all harvest dates (r2 = 0.72, SEP = 1.84 °Brix). Calibrations for Brix in melon were transferable between two of the three varieties examined. However, a lack of robustness of calibration was indicated by poor validation within populations of fruit harvested at different times. Further work is planned to investigate the robustness of calibration across varieties, growing districts and seasons