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Investigating aquaphotomics for fruit quality assessment

The methods of aquaphotomics were explored for internal fruit quality assessment, such as dry matter (DM) and soluble solid content (SSC) measurement using near infrared spectroscopy (NIRS). Fruits like apple and kiwifruit are more than 80% water. The NIR spectrum of whole intact fruit is dominated by water absorption peaks that shift and vary in shape with changes in quantities such as SSC, DM, and temperature. These variations can significantly reduce predictive model performance for fruit quality parameters. Because the absorption peak at 1450 nm (first overtone of the OH stretch of water) and 970 nm (second overtone of the OH stretch of water) in the samples varies with SSC, DM concentration, and temperature, an investigation was undertaken on the aquaphotomics approach to quantify changes in the water structure that are apparent in the two wavelength regions. The key question examined was whether aquaphotomics can help in the development of better and simpler prediction models or hardware for intact fruit quality measurements beneficial to the industry. To find answers to this question, several experiments were conducted. Much work in aquaphotomics has been done in the longer wavelength region, that is, at the first overtone (1300–1600 nm), which requires short pathlength cells due to higher water absorption. Experiments were performed on simple aqueous systems such as sucrose solution of various concentrations and an aqueous system such as apple and kiwifruit juice. The second overtone wavelength region (800‒1100 nm) was also scrutinized for fruit juice measurements using a long pathlength cell. Eventually, experiments were conducted on whole intact fruit. A Fourier transform near infrared (FT-NIR) spectrophotometer was used to acquire spectra of aqueous samples over the wavelength range of 900 to 1800 nm. For whole, intact fruit spectra collection, spectrophotometers in the wavelength range below 1100 nm were utilized. An in-house benchtop spectrometer based on the Zeiss MMS-1 NIR spectrometer operated in interactance mode was used along with some commercially available handheld spectrophotometers such as the F-750 produce quality spectrometer and the SCiO spectrometer. The spectra acquired with the instruments were analyzed using multivariate data analysis. The calibration models were developed using partial least square regression (PLSR) and multiple linear regression to estimate quality attributes. The NIR spectrum of fruit is affected by temperature. Therefore, a calibration equation developed at one fixed temperature cannot reliably predict samples at a different temperature. Using the framework of aquaphotomics, the changes within the water structure of fruit juice and whole intact fruit occurring with changes in temperature were analysed. Water wavelengths affected by temperature variation were identified in the first and second overtone regions. Using aquagrams, it appeared that different water species were activated in the first and second overtone region. The influence of increasing temperature on the peak absorbance of the juice was a lateral shift in the first overtone region, whereas it was vertical in the second overtone region of water. Two correction pre-treatments; extended multiplicative scatter correction (EMSC) and external parameter orthogonalization (EPO) were used in conjunction with principal component loading of water as an interferent spectrum. They were able to correct for temperature effects by at least a factor of 10 to insignificant levels. It was concluded that the aquaphotomics paradigm offers fundamental insights into the role of the various light absorption mechanisms but only in conjunction with chemometrics tools, like EMSC and EPO, leading to an improvement in predictive model performance. The investigated methods have good potential to be used for quality assessment of fruit in industry.
Type of thesis
Kaur, H. (2020). Investigating aquaphotomics for fruit quality assessment (Thesis, Doctor of Philosophy (PhD)). The University of Waikato, Hamilton, New Zealand. Retrieved from https://hdl.handle.net/10289/13693
The University of Waikato
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