Non-destructive measurement of pomegranate fruit quality
| dc.contributor.advisor | Opara, Umezuruike Linus | en_ZA |
| dc.contributor.advisor | Fawole, Olaniyi Amos | en_ZA |
| dc.contributor.advisor | Magwaza, Lembe Samukelo | en_ZA |
| dc.contributor.author | Arendse, Ebrahiema | en_ZA |
| dc.contributor.other | Stellenbosch University. Faculty of AgriSciences. Dept. of Food Science. | en_ZA |
| dc.date.accessioned | 2017-11-20T09:19:14Z | |
| dc.date.accessioned | 2017-12-11T10:34:38Z | |
| dc.date.available | 2018-05-23T03:00:05Z | |
| dc.date.issued | 2017-12 | |
| dc.description | Thesis (PhD (Food Sc))--Stellenbosch University, 2017. | en_ZA |
| dc.description.abstract | ENGLISH ABSTRACT: Pomegranate (Punica granatum L.) is an emerging fruit within the South African horticultural industry, which has experienced dramatic growth in annual production from 350 tonnes in the 2009 season to over 8000 tonnes in 2017. Literature shows that the fruit consists of considerable amount of sugars, organic acids, vitamins, mineral elements and possess potent pharmacological activities due to an array of phytochemical compounds found in the fruit. However, the fruit is highly susceptible to pest and disease infestation, including the development of physiological rind disorders during storage and shipping. The increased growth of the pomegranate industry has coincided with consumer demand for consistent supply of safe, nutritious and traceable fruit and processed products. Hence, non-destructive assessment of fruit quality and its processed products can contribute to the implementation of suitable management strategies to predict and control desired quality attributes. This will ensure delivery of high quality fruit and its derived products without the presence of defects in international and local markets. Therefore, the overall aim of this study was to develop non-destructive methods to predict external and internal quality attributes of pomegranate fruit. Section I of the thesis focuses on a critical review of non-destructive techniques for assessing the external and internal quality of fruit with thick rind. Thick rind fruits, such as pomegranate, have been reported to interfere with accurate measurement of internal quality using near-infrared spectroscopy. Hence, this review provides an overview of the issues related to quality measurement using non-destructive methods, including a concise summary of the current research and potential commercial applications. In section II (chapter 3), the feasibility of X-ray micro-computed tomography (μCT) as a non-destructive technique to characterise and quantify the internal structure of pomegranate fruit was investigated. μCT in combination with image analysis successfully characterised and quantified the volumes of the internal fruit components (arils, peel, kernel, juice content, air space). The calculated volume for total arils, peel, and air space were 162.45 ±16.21, 163.87 ±21.42 and 10.89 ±2.57 mL, respectively, which accounted for 48.04, 48.46 and 3.22% of the total fruit volume (338.19 ±22.4 mL). The calculated volume of juice content and kernels were 146.07 ±16.28 and 16.38 ±1.81 mL per fruit which were equivalent to an average of 89.92 and 10.08% of the total aril volume. Destructive validation results showed no significant difference with those obtained from the μCT-based non-invasive method. This study has demonstrated the potential use of μCT and associated image analysis as a promising tool for non-destructive characterization of the internal and external structure of pomegranate fruit. In chapter 4, the prospects of Fourier-transform near-infrared (FT-NIR) spectroscopy (FT-NIRS) and associated chemometric analysis were evaluated for the prediction of external and internal quality parameters of intact pomegranate fruit. Two diffuse reflectance spectral acquisition modes were assessed, namely, direct contact between the sample with an integrating sphere (IS) using the Multi-Purpose Analyser (MPA) and a contact-less measurement (distance 17 cm) using an optic fibre coupled emission head (EH) of the MATRIXTM-F analyser. Partial least squares (PLS) regression was used to construct calibration models over a spectral region of 800-2500 nm, and the results showed that optimal model performance was obtained using first derivative and second derivative spectral pre-processing methods. It was found that models obtained from the EH spectral data predicted fruit firmness, colour components (a* and C*), total soluble solids, titratable acidity, BrimA, total phenolics and vitamin C with high accuracy (RPD values ranging from 2.06 to 3.34), while the IS showed good prediction ability for h° colour component (RPD = 2.50), TSS:TA (RPD = 2.72) and total anthocyanin (RPD = 1.64). The results suggest that the contactless option of the MATRIX-F could be used to evaluate quality attributes of intact pomegranate fruit. In chapter 5, the development of calibration models by FT-NIRS for the evaluation of pomegranate aril quality was investigated using two different FT-NIR acquisition methods (IS and EH) over 800-2500 nm spectral region. Model development was based on pre-processing methods that yielded higher values of coefficient of determination (R2) and residual predictive deviation (RPD), lower root mean square error estimation (RMSEE) and root mean square error of prediction (RMSEP). The results showed that models based on the EH provided good prediction of TSS, pH, TA, BrimA, aril hue, total phenolic, total anthocyanin and vitamin C concentration, while those based on IS provided the best results for TSS:TA, firmness, arils redness (a*) and colour intensity (chroma). Furthermore, a follow-up study was conducted to compare near and mid infrared (MIR) spectrometers for predicting organoleptic and phytochemical quality attributes of pomegranate juice (chapter 6 (section II)). Three Fourier transform infrared (FT-IR) spectrometers (representing three different spectral acquisition modes) were assessed; namely, MPA FT-NIR spectrometer, Alpha-P FT-MIR spectrometer and WineScan FT-NIR/MIR spectrometer. Results obtained showed that spectral acquisition mode affected model ability to accurately predict various pomegranate quality attributes, with the WineScan in the NIR/MIR region outperforming the Alpha-P and MPA instruments. However, statistical comparison using Bland and Altman and Passing-Bablok analytical algorithms showed no statistical differences among the three spectrometers for the prediction of selected aril quality parameters. Section III of the thesis investigated the prospects for non-destructive detection and classification of pomegranate fruit affected by internal defects and postharvest rind scald. In chapter 7, the feasibility of μCT with a calibration function to differentiate between fruit fractions (albedo and arils) and detect the presence of false codling moth and blackheart disease in pomegranate fruit was assessed. A calibration function was implemented using different homogenous polymeric materials with a density ranging from 910 to 2150 kg m−3. The estimation of fruit density was successfully accomplished within the calibration range. The density of whole fruit (1070 ±20 kg m−3), arils (1120 ±40 kg m−3) and albedo 1040 ±30 kg m−3) were significantly higher compared to the larva of codling moth (940 ±40 kg m−3) inside the fruit. Furthermore, healthy fruit had significantly higher density (1070 ±20 kg m−3) compared to those with blackheart (870–1000 ±50 kg m−3). An increase in the severity of blackheart infestation was characterised by a decrease in density of affected fruit. The results of this study suggested that the use of X-ray μCT, in combination with a calibration function of polymers and image analysis, could be applied to non-destructively identify and differentiate between fruit fractions, and detect the presence of larva of false codling moth and blackheart in pomegranate fruit. The research reported in chapter 8 (section III) evaluated several biochemical markers associated with the development of husk scald (peel browning) and based on these markers, assess the feasibility of non-destructive discrimination of healthy and scalded affected fruit using Fourier transform near-infrared (FT-NIR) spectroscopy. The results suggest that enzymatic browning was the main cause of husk scald, phenolic compounds such as tannins acting as substrates for polyphenol oxidase and peroxidase activity. The severity of browning index increased with storage temperature and duration. FT-NIR reflectance spectroscopy spectral data and reference data were subjected to orthogonal partial least squares discriminant analysis (OPLS-DA) to discriminate between healthy and scalded fruit. Resulting in high classification accuracy (100%, 93% and 92.6% for healthy, severe and moderately scalded fruit, respectively). Therefore, this study has successfully demonstrated that biochemical markers associated with the development of husk scald could potentially be used to non-destructively discriminate between healthy and scalded fruit. | en_ZA |
| dc.description.abstract | AFRKAANSE OPSOMMING: Die granaat (Punica granatum L.) is ‘n opkomende vrug in die Suid-Afrikaanse tuinboubedryf wat dramatiese produksie groei getoon het van 350 ton in die 2009-seisoen tot meer as 8000 ton in 2017. Literatuur dui aan dat die vrug bestaan uit aansienlike hoeveelhede suikers, organiese sure, vitamiene en minerale; asook kragtige farmakologiese aktiwiteite as gevolg van 'n verskeidenheid fitochemiese verbindings. Die vrugte is egter hoogs vatbaar vir plaag- en siektesbesmetting, insluitend die ontwikkeling van fisiologiese skil kwale tydens berging en besending. Die stygende groei van die granaatbedryf beweeg saam met verbruikersvereiste na konsekwente voorsiening van veilige, voedsame en opspoorbare vrugte en verwerkte produkte. Gevolglik kan nie-vernietigende assessering van vrugkwaliteit en verwerkte produkte bydra tot die implementering van geskikte bestuurstrategieë om gewenste kwaliteitseienskappe te voorspel en te beheer. Dit sal verseker dat vrugte en produkte van ‘n hoë gehalte, sonder kwale, in die internasionale en plaaslike markte sal voorkom. Die oorhoofse doel van hierdie studie was dus om nie-vernietigende metodes te ontwikkel om die eksterne en interne kwaliteitseienskappe van granaatvrugte te voorspel. Afdeling I van die proefskrif fokus op 'n kritiese oorsig van nie-vernietigende tegnieke wat gebruik word om die eksterne en interne kwaliteit van vrugte met ‘n dik skil te assesseer. Volgens literatuur word die akkuraatheid van interne kwaliteitsmetings deur middel van naby infrarooi spektroskopie beïnvloed deur vrugte met ‘n dik skil, soos granate. Hierdie oorsig bespreek kwessies wat verband hou met gehaltemeting deur middel van nie-destruktiewe metodes, insluitend 'n bondige opsomming van die huidige navorsing en potensiële kommersiële toepassings. In afdeling II (hoofstuk 3) word die lewensvatbaarheid van X-straal mikro-berekende-tomografie (μCT) as 'n nie-vernietigende tegniek ondersoek, om die interne struktuur van granaatvrugte te karakteriseer en te kwantifiseer. Die kombinasie van μCT en beeldontleding het die volumes van die interne vrug komponente (arils, skil, pitte, sap inhoud, lugruimte) suksesvol gekenmerk en gekwantifiseer. Die berekende volume vir totale arils, skil en lugruimte was onderskeidelik 162.45 ±16.21 mL, 163.87 ±21.42 mL en 10.89 ±2.57 mL, wat verantwoordelik was vir 48.04%, 48.46% en 3.22% van die totale vrugvolume (338.19 ±22.4 mL). Die berekende volume vir sap-inhoud en pitte was onderskeidelik 146.07 ±16.28 mL en 16.38 ±1.81 mL per vrug wat gelykstaande is aan 'n gemiddeld van 89.92 en 10.08% van die totale aril volume. Destruktiewe validasie resultate het geen betekenisvolle verskil getoon met dié wat verkry is uit μCT-gebaseerde nie-indringende metode. Hierdie studie het die potensiële gebruik van μCT en geassosieerde beeldanalise getoon as 'n belowende instrument vir nie-vernietigende karakterisering van interne en eksterne struktuur van granaatvrugte. In hoofstuk 4 is die vooruitsigte van Fourier-transform naby-infrarooi (FT-NIR) spektroskopie (FT-NIRS) en geassosieerde chemometriese analise geëvalueer vir die voorspelling van eksterne en interne gehalte-parameters van ongeskonde granaatvrugte. Twee diffusie weerkaatsde spektrale verkrygingsmetodes is geassesseer naamlik, direkte kontak tussen die monster met 'n integrerende sfeer (IS) met behulp van die Multi-Purpose Analyser (MPA) en 'n kontaklose meting (afstand 17 cm) met behulp van 'n optiese vesel-gekoppelde emissiekop (EH) van die MATRIXTM-F ontleder. Gedeeltelike minimum vierkantpassing (PLS) regressie is gebruik om kalibrasie modelle oor 'n spektrale gebied van 800-2500 nm te bou, en die resultate het getoon dat optimale modelprestasie verkry is deur gebruik te maak van eerste afgeleide en tweede afgeleide spektrale voorafverwerkingsmetodes. Daar is gevind dat modelle verkry uit die EH-spektrale data, die vrugte se gehalte-graad, kleurkomponente (a* en C*), totale oplosbare vastestowwe (TSS), titreerbare suurheidsgraad (TA), BrimA, totale fenolieke en vitamien C met hoë akkuraatheid (RPD waardes wat wissel tussen 2.06 en 3.34) voorspel, terwyl die IS goeie voorspellingsvermoë vir h° kleurkomponent (RPD = 2.50), TSS: TA (RPD = 2.72) en totale antosianien (RPD = 1.64) getoon het. Die resultate dui daarop dat die kontaklose opsie van die MATRIX-F, gebruik kan word om gehalte-eienskappe van ongeskonde granaatvrugte te evalueer. In hoofstuk 5 is die ontwikkeling van kalibrasie-modelle deur FT-NIRS vir die evaluering van aril-kwaliteit ondersoek met behulp van twee verskillende FT-NIR-verkrygingsmetodes (IS en EH) oor 800-2500 nm spektrale gebied. Die model-ontwikkeling is gebaseer op voorafverwerkingsmetodes wat hoër waardes van bepalingskoëffisiënt (R2) en residuele voorspellende afwyking (RPD), laer wortel gemiddelde vierkante foutberaming (RMSEE) en wortel gemiddelde vierkante fout van voorspelling (RMSEP) gegee het. Die resultate het getoon dat modelle wat op die EH gebaseer is, goeie voorspelling van TSS, pH, TA, BrimA, aril tint, totale fenoliese, totale anthosianien en vitamien C konsentrasie gegee het, terwyl dié wat op IS gebaseer is, die beste resultate vir TSS:TA, fermheid, aril rooiheid (a*) en kleurintensiteit (chroma) verskaf het. Verder is 'n opvolgstudie gedoen om naby- en middelinfrarooi (MIR) spektrometers te vergelyk vir die voorspelling van organoleptiese en fito-chemiese gehalte-eienskappe van granaatsap (hoofstuk 6 (afdeling II)). Drie Fourier-transform infrarooi (FT-IR) spektrometers (wat drie verskillende spektrale verkrygingsmetodes verteenwoordig) is beoordeel; naamlik MPA FT-NIR spektrometer, Alpha-P FT-MIR spektrometer en WineScan FT-NIR / MIR spektrometer. Resultate het getoon dat die spektrale verkrygingsmodus die vermoë gehad het om verskeie eienskappe van granaatkwaliteit akkuraat voor te stel, met die WineScan in die NIR / MIR-streek beter as die Alpha-P en MPA-instrumente. Statistiese vergelyking met behulp van Bland en Altman, en Passing-Bablok-analitiese algoritmes het egter geen statistiese verskille tussen die drie spektrometers getoon vir die voorspelling van geselekteerde arilkwaliteit parameters nie. Afdeling III van die proefskrif het die vooruitsigte vir nie-vernietigende ontdekking en klassifikasie van interne defekte en na-oes-skil-verbruining in granaatvrugte ondersoek. In hoofstuk 7 is die uitvoerbaarheid van μCT geassesseer om met 'n kalibrasie funksie tussen vrugte dele (albedo en arils) te onderskei, en die teenwoordigheid van valskodlingmot en swarthartbloutjie in granaatvrugte te bepaal. Die kalibreringsfunksie is geïmplementeer deur verskillende homogene polimeermateriale te gebruik met digthede wat wissel van 910 tot 2150 kg m-3. Die skatting van vrugtedigtheid was suksesvol binne die kalibrasie bereik. Die digtheid van heelvrugte (1070 ±20 kg m-3), arils (1120 ±40 kg m-3) en albedo (1040 ±30 kg m-3) was aansienlik hoër in vergelyking met die larwes van valskodlingmot (940 ±40 kg m-3) binne-in die vrugte. Verder is die digtheid van gesonde vrugte aansienlik hoër (1070 ±20 kg m-3) in vergelyking met dié met swarthartbloutjie (870-1000 ±50 kg m-3). 'n Toename in die graad van swarthartbloutjie-besmetting is gekenmerk deur 'n afname in die digtheid van geaffekteerde vrugte. Die resultate van hierdie studie het voorgestel dat die gebruik van X-straal μCT, in kombinasie met 'n kalibreringsfunksie van polimere en beeldontleding, toegepas kan word om nie-destruktief te identifiseer en te onderskei tussen vrugte dele, sowel as om larwes van valskodlingmot en swarthartbloutjie in granaatvrugte te ontdek. Die navorsing wat in hoofstuk 8 (afdeling III) gerapporteer is, het verskeie biochemiese merkers geëvalueer wat verband hou met die ontwikkeling van skilverbruining. Hierdie merkers is gebruik as ‘n grondslag om die uitvoerbaarheid te assesseer van nie-vernietigende diskriminasie van gesonde en verbruinde vrugte, met behulp van Fourier transform naby- Infrarooi (FT-NIR) spektroskopie. Die resultate dui daarop dat skilverbruining hoofsaaklik deur ensimatiese verbruining veroorsaak word met fenoliese verbindings, soos tanniene, wat as substrate vir polifenol-oksidase en peroksidase-aktiwiteite optree. Die graad van verbruining het toegeneem met bergingstemperatuur en –duur. FT-NIR-weerkaatsde spektroskopie spektrale data en verwysingsdata is onderskei deur middel van ortogonale gedeeltelike minimale vierkante diskriminasie analise (OPLS-DA) om gesonde en verbruinde vrugte aan te dui. Dit het gelei tot hoë klassifikasie akkuraatheid (100%, 93% en 92.6% vir onderskeidelik gesonde, erge en matig verbruinde vrugte). Daarom was hierdie studie suksesvol om te wys dat die biochemiese merkers, wat geassosieer word met die ontwikkeling van verbruining, moontlik gebruik kan word om nie-vernietigend te onderskei tussen gesonde en verbruinde vrugte. | af_ZA |
| dc.embargo.terms | 2018-05-23 | |
| dc.format.extent | 272 pages : illustrations | en_ZA |
| dc.identifier.uri | http://hdl.handle.net/10019.1/102633 | |
| dc.language.iso | en_ZA | en_ZA |
| dc.publisher | Stellenbosch : Stellenbosch University | en_ZA |
| dc.rights.holder | Stellenbosch University | en_ZA |
| dc.subject | Pomegranate industry -- South Africa | en_ZA |
| dc.subject | Pomegranate -- Quality measurement | en_ZA |
| dc.subject | Pomegranate (Punica granatum) | en_ZA |
| dc.subject | Pomegranate -- Postharvest technology | en_ZA |
| dc.subject | UCTD | en_ZA |
| dc.title | Non-destructive measurement of pomegranate fruit quality | en_ZA |
| dc.type | Thesis | en_ZA |
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