Prediction of post-storage quality in canning apricots and peaches using near infrared spectroscopy (NIRS) and chemometrics

Myburgh, Lindie (2003-12)

Thesis (MSc Food Sc)--Stellenbosch University, 2003.

Thesis

ENGLISH ABSTRACT: Post-storage quality of the stone fruit, apricots and peaches, is the major factor determining their suitability for canning after cold storage in South Africa. Short harvesting periods and the limited capacity of the factory to process the large quantities of fruit within two days after delivery, necessitates cold storage until canning. Apricots develop internal breakdown, whereas peaches develop internal breakdown accompanied by loosening of the skin and adhesion of the flesh to the stone. The deterioration takes place within the fruit during a cold storage period of one to two weeks. The tendency of the fruit to develop internal defects can, to date, not be identified prior to storage and are only discovered after destoning during canning. Near infrared spectroscopy (NIRS) combined with chemometrics were investigated as a non-destructive method to predict post-storage quality in Bulida apricots and clingstone peach cultivars. Near infrared (NIR) spectra (645-1201 nm), measured on the intact fruit just after harvesting, were correlated with subjective quality evaluations performed on the cut and destoned fruit after cold storage. The cold storage periods for apricots were four weeks (2002 season) and three and two weeks for peach cultivars for the 2002 and 2003 seasons, respectively. Soft independent modelling by class analogy (SIMCA) and multivariate adaptive regression splines (MARS) were applied to the spectral and reference data to develop models for good and poor post-storage quality. The ability of these models to predict post-storage quality was evaluated in terms of recognition (sensitivity) and rejection (specificity) of the samples in independent validation sets. Total correct classification rates of 50.00% and 69.00% were obtained with Bulida apricots, using SIMCA and MARS, respectively. Classification results with apricots showed that MARS performed better than SIMCA and is thus recommended for this application. Total correct classification rates of 53.00% to 60.00% (SIMCA) and 57.65% to 65.12% (MARS) were obtained for data sets of combined peach cultivars within seasons and over both seasons. Additional aspects of fruit quality were investigated to identify possible indices of post-storage quality. Classification trees were used to find correlations between the post-storage quality and the fruit mass, diameter, firmness and soluble solids content (SSC). Among these, fruit diameter and firmness were the major indices of post-storage quality. Accurate predictions of firmness could not be achieved by near infrared spectroscopy (NlRS), making the combination of NIRS and classification trees not yet suitable for predicting post-storage quality. NIRS was further used to predict poststorage SSC within seasons in Bulida apricots and intact peach cultivars. This confirmed sufficient NIR light penetration into the intact fruit and also provided a further application of NIRS for ripeness evaluation in the canning industry. Validations on peach samples obtained correlation coefficients (r) of 0.77-0.85 and SEP-values of 1.35-1.60 °Brix using partial least squares (PLS) regression. MARS obtained r = 0.77-0.82 and SEP = 1.42-1.55 °Brix. Predictions of sse in apricots were less accurate, with r = 0.39-0.88, SEP = 1.24-2.21 °Brix (PLS) and r = 0.51-0.82, SEP = 1.54-2.19 °Brix (MARS). It is suggested that the accuracy of sse measurements, and the subsequent predictions, were affected by the cold storage periods as well as internal variation within the fruit. This study showed that a combination of NIRS and chemometrics can be used to predict post-storage quality in intact peaches and apricots. A small scale feasibility study showed that 4% (R117 720) (apricot industry) and 3% (R610 740) (peach industry) of production losses can be saved if this method is implemented in the South African canning industry. Although it was difficult to assign specific chemical components or quality attributes to the formulation of the storage potential models, important hidden information in the spectra could be revealed by chemometric classification methods. NIRS promises to be a useful and unique quality evaluation tool for the South African fruit canning industry. Several recommendations are made for the canning practices to reduce losses and for future research to improve the current prediction models.

AFRIKAANSE OPSOMMING: Die kwaliteit van die steenvrugte, appelkose en perskes, is die hoof bepalende faktor vir hul geskiktheid vir inmaakdoeleindes na koelopberging in Suid-Afrika. Die vrugte moet opgeberg word by lae temperature vir een tot twee weke, aangesien die oestydperk kort is en die kapasiteit van die fabriek te beperk is om die groot hoeveeheid vrugte dadelik in te maak. Tydens hierdie opbergingstydperk vind agteruitgang in die vrugte plaas. Dit word in appelkose gekenmerk deur interne verval en in perskes gekenmerk aan interne verval, tesame met enlos skil en die vaskleef van die vrugvlees aan die pit. Tot dusver, bestaan daar geen metode om hierdie tipe agteruitgang in vrugte voor opberging te identifiseer nie. Dit word eers na opberging opgemerk wanneer die vrugte ontpit word. Naby-infrarooi spektroskopie (NIRS), gekombineerd met chemometriese metodes is gebruik om opbergingspotensiaal in Bulida appelkose en taaipitperske kultivars te bepaal. enKorrelasie is gemaak tussen naby-infrarooi (NIR) spektra, gemeet op die heel vrugte voor opberging en subjektiewe evaluering van kwaliteit, geïdentifiseer op die gesnyde vrugte na opberging. Die opbergingstydperke vir perskes was vir drie en twee weke vir die 2002 en die 2003 seisoene, onderskeldeflk, terwyl die appelkose vir vier weke opgeberg is. Twee chemometriese metodes, "soft independent modelling by class analogy" (SIMCA) en "multivariate adaptive regression splines" (MARS) is gebruik om die spektra en ooreenstemmende subjektiewe data te kombineer en modelle is ontwikkel vir goeie en swak opbergingspotensiaal. Die vermoë van die modelle om die vrugkwaliteit na die opbergingstydperk te voorspel, is geêvalueer in terme van herkenning en verwerping van vrugtemonsters in onafhanklike toetsstelle. Totale korrekte klassifikasies van 50.00% and 69.00% is verkry vir Bulida appelkose, met SIMCA en MARS, onderskeidelik. Die klassifikasie resultate het gewys dat MARS beter gevaar het as SIMCA en word dus sterk aanbeveel vir hierdie toepassing. Totale korrekte klassifikasies van 53.00% tot 60.00% (SIMCA) and 57.65% tot 65.12% (MARS) is verkry vir gekombineerde perskekultivars tussen seisoene en oor seisoene. Verdere aspekte van vrugkwaliteit is geêvalueer om enmoontlike indeks van opbergingspotensiaal te verkry. Klassifikasiebome is gebruik om en korrelasie te vind tussen kwaliteit na opberging en vrugmassa, deursnee, fermheid en totale oplosbare vastestowwe (TOV). Diameter en fermheid het die meeste gekorreleer met die kwaliteit na opberging. Voorspellings van fermheid deur die gebruik van naby infrarooi spektroskopie (NIRS) was ~gter nie akkuraat nie. Dus word die kombinasie van klassifikasiebome en NIRS om opbergingspotensiaal te voorspel nie tans aanbeveel nie. NIRS is verder gebruik om TOV te voorspel binne seisoene in heel Bulida appelkose en perskekultivars. Dit is uitgevoer om voldoende NIR ligpenitrasie in die vrugte te bevestig en ook om 'n verdere toepassing van kwaliteitsbepaling (as indeks van soetheid en rypheid) vir die inmaakindustrie te verskaf. Validasies is op perskemonsters uitgevoer en korrelasiekoêffisiente (r) van 0.77-0.85 en voorspellingsfoute van 1.35-1.60 °Brix is verkry met "partial least squares" (PLS) regressie. MARS het r = 0.77-0.82 and voorspellingsfoute = 1.42-1.55 °Brix verkry. Die akkuraatheid van die TOV meetings en gevolglike voorspellings is waarskynlik beïnvloed deur interne variasie binne die vrugte sowel as die opbergings tydperke wat verloop het tussen metings. Hierdie studie wys dat NIRS en chemometriese metodes wel gebruik kan word om opbergingspotensiaal in heel perskes in appelkose te voorspel. 'n Kosteberekening het gewys dat besparings van 4% (R117 720) (appelkoos industrie) en 3% (R610 740) (perske industrie) moontlik is indien NIRS en MARS geïmplementeer word. Alhoewel dit moeilik was om spesifieke chemiese komponente en .sekere kwaliteitsaspekte aan die ontwikkeling van die modelle te koppel, is belangrike verborge informasie in die spectra uitgebring deur chemornetriese metodes. NIRS beloof om 'n bruikbare en unieke kwaliteitskontrole maatstaf te wees vir die Suid-Afrikaanse inmaakindustrie. Verskeie aanbevelings is gemaak vir die inmaakpraktyke om verliese te voorkom en ook vir toekomstige navorsing om die huidige klassifikasiemodelle te verbeter.

Please refer to this item in SUNScholar by using the following persistent URL: http://hdl.handle.net/10019.1/53557
This item appears in the following collections: