Non-destructive prediction and monitoring of postharvest quality of citrus fruit

Magwaza, Lembe Samukelo (2013-12)

Thesis (PhD(Agric))--Stellenbosch University, 2013.

ENGLISH ABSTRACT: The aim of this study was to develop non-destructive methods to predict external and internal quality of citrus fruit. A critical review of the literature identified presymptomatic biochemical markers associated with non-chilling rind physiological disorders. The prospects for the use of visible to near infrared spectroscopy (Vis/NIRS) as non-destructive technology to sort affected fruit were also reviewed. Initial studies were conducted to determine the optimum condition for NIRS measurements and to evaluate the accuracy of this technique and associated chemometric analysis. It was found that the emission head spectroscopy in diffuse reflectance mode could predict fruit mass, colour index, total soluble solids, and vitamin C with high accuracy. Vis/NIRS was used to predict postharvest rind physico-chemical properties related to rind quality and susceptibility of ‘Nules Clementine’ to RBD. Partial least squares (PLS) statistics demonstrated that rind colour index, dry matter (DM) content, total carbohydrates, and water loss were predicted accurately. Chemometric analysis showed that optimal PLS model performances for DM, sucrose, glucose, and fructose were obtained using models based on multiple scatter correction (MSC) spectral pre-processing. The critical step in evaluating the feasibility of Vis/NIRS was to test the robustness of the calibration models across orchards from four growing regions in South Africa over two seasons. Studies on the effects of microclimatic conditions predisposing fruit to RBD showed that fruit inside the canopy, especially artificially bagged fruit, had lower DM, higher mass loss, and were more susceptible to RBD. The study suggested that variations in microclimatic conditions between seasons, as well as within the tree canopy, affect the biochemical profile of the rind, which in turn influences fruit response to postharvest stresses associated with senescence and susceptibility to RBD. Principal component analysis (PCA) and PLS discriminant analysis (PLS-DA) models were applied to distinguish between fruit from respectively, inside and outside tree canopy, using Vis/NIRS signal, suggesting the possibility of using this technology to discriminate between fruit based on their susceptibility to RBD. Results from the application of optical coherence tomography (OCT), a novel non-destructive technology for imaging histological changes in biological tissues, showed promise as a potential technique for immediate, real-time acquisition of images of rind anatomical features of citrus fruit. The study also demonstrated the potential of Vis/NIRS as a non-destructive tool for sorting citrus fruit based on external and internal quality.

AFRIKAANSE OPSOMMING: Die studie het ten doel gestaan om nie-destruktiewe meeting metodes te toets en ontwikkel wat die interne en eksterne-kwaliteit van sitrusvrugte kan voorspel. In ʼn litratuuroorsig is biochemies verandering in die skil en wat geassosieer word met die ontwikkeling van fisiologies skildefekte geïdentifiseer, asook is die moontlikheid ondersoek om Naby Infrarooi spektroskopie (NIRS) as ‘n nie-destruktiewe tegnologie te gebruik om vrugte te sorteer. Eerstens was die optimale toestande waarby NIRS meetings van sitrusvrugte geneem moet word asook die akkuraatheid van die toerusting en chemometrika data-ontleding beproef. Daar is gevind dat die uitstralings-kop spektrofotometer in diffusie-weerkaatsings modus vrugmassa, skilkleur, totale opgeloste stowwe asook vitamien C akkuraat kan voorspel. Daarna van NIRS gebruik om na-oes fisies-chemiese eienskappe wat verband hou met skilkwaliteit en vatbaarheid vir skilafbraak van ‘Nules Clementine’ mandaryn. Deur gebruik te maak van “Partial least squares” (PLS) statistieke was gedemonstreer dat die skilkleur, droë massa (DM), totale koolhidrate en waterverlies akkuraat voorspel kon word. Chemometriese analises het ook getoon dat optimale PLS modelle vir DM, sukrose, glukose en fruktose verkry kan word deur modelle te skep wat gebaseer is op “Multiple scatter correction” (MSC) spektrale voor-verwerking. ʼn Belangrike stap in die ontwikkeling van NIRS gebaseerde indeling is om die robuustheid van die kalibrasiemodelle te toets en was gedoen deur vrugte te meet en sorteer van vier boorde en oor twee seisoene. ʼn Verder eksperiment om die impak van mikroklimaat op die skil se vatbaarheid vir fisiologiese defekte te ontwikkel het getoon dat vrugte wat binne in die blaardak ontwikkel (lae vlakke van sonlig) ʼn laer DM, hoër gewigsverlies het en was ook meer vatbaar vir skilafbraak. Die resultate dui daarop dat verskille in mikroklimaat oor die seisoen asook in die blaardak die skil se biochemiese profiel beïnvloed, wat lei tot ʼn negatiewe reaksie op na-oes stres en verhoogde voorkoms van fisiologiese skilafbraak. Die ontwikkelde “Principal component analysis” (PCA) en PLS-diskriminant analise modelle was daarna suksesvol toegepas om vrugte te skei na NIRS meetings, op die basis van vrugpossies in die blaardak. Nuwe, nie-destruktiewe tegniek, nl. “Optical coherence tomography” (OCT) was suksesvol getoets as manier om ʼn fotografiese beeld te skep van histologiese veranderinge in die skil. Die resultate dui op die potensiaal van die onontginde tegnologie om intak biologiese-materiaal te analiseer. Hierdie studie het getoon dat daar wesenlike potensiaal is om NIRS verder te ontwikkel tot ʼn tegnologie wat gebruik kan word om vrugte te sorteer gebaseer op eksterne (skil) asook interne (pulp) eienskappe

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