Use of flesh firmness and other objective tests to determine consumer acceptability of Delicious apples

Wills, R. B. H.; Bambridge, P. A.; Scott, K. J.

doi:10.1071/ea9800252

Cited by 84 publications

(59 citation statements)

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“…As starch content decreases and sugar content increases, so acidity of most fruits decreases. Similar type of variations for TSS and acidity were reported by Ghafir et al (2009), Wills et al (1980 and El-Anany et al (2009) for apple during storage. The regression equations for TSS and acidity with their corresponding correlation coefficients are given in (Table 2).…”

Section: Resultssupporting

confidence: 87%

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Physico-chemical quality parameters and overall quality index of apple during storage

Jha

Shrama

2011

J Food Sci Technol

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Physico-chemical quality parameters of apple were measured during storage using standard techniques and fitted to model expressions for developing an overall quality index (I q ). Predicted I q was validated with the trends of sensory scores. Total Soluble Solids (TSS) and acidity varied from 13.2 to 12.3 ºBrix and 0.161 to 0.079%, respectively whereas, Hunter colour values L, a, b and yellowness index were 48.7-56.1, 11.0-19.4, 18.8-20.2 and 84.6-98.2, respectively. The gloss at 45 and 60º incidence angles, density and I q varied from 7.5 to 4.3 and 6.7 to 2.6 GU, 1.01 to 0.96 kg m −3 and 0.26 to 1.02, respectively. The variation in sensory overall quality scores with storage period was found to be in line with computed overall quality index. The I q thus, could be defined as the ratio of product of acidity and TSS to the mode of product of a and b Hunter colour values. The polynomial regression equations for I q with TSS, acidity, a, b, and storage period yielded the correlation coefficients of 0.8443, 0.9838, 0.7130, 0.7183 and 0.9665, respectively; which indicated that overall quality index could be predicted nondestructively using any one of these parameters during storage.

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Section: Resultssupporting

confidence: 87%

“…In the initial period, it decreased from 13.2 to 12.3°Brix. The decrease was probably due to conversion of sugar into starch (Wills et al 1980), which shows that apple may become less sweet with the passage of time. Later on, it again increased due to re-conversion of starch into monosaccharide (Duque et al 1999).…”

Section: Resultsmentioning

confidence: 99%

Physico-chemical quality parameters and overall quality index of apple during storage

Jha

Shrama

2011

J Food Sci Technol

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“…10%which was statistically at par with the gum acacia 20%, paraffin liquid 5% and 10%. The increase in TSS and sugar content during storage may possibly be due to hydrolysis of starch into sugars as on complete hydrolysis of starch no further increase occurs and subsequently a decline in these parameters is predictable as they along with other organic acids are primary substrate for respiration (Wills et al, 1980). Kagzi lime fruits treated with coconut oil recorded minimum (8.4%) increase in TSS followed by (8.5%) liquid paraffin wax (Bisen et al, 2012).…”

Section: Total Soluble Solids (Tss)mentioning

confidence: 99%

Postharvest Treatments on Storage Life of Guava (Psidium guajava L.) in Himalayan Terai Region of West Bengal

Bhowmick¹,

Ghosh²,

Ghosh³

2017

Int.J.Curr.Microbiol.App.Sci

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“…Climatic conditions, cultivars (Phillips and Poapst, 1952) and seasons (Poapst et al, 1959) all influence starch pattern. According to Wills et al (1980) the organoleptic changes in the fruit do not correlate very well with the changes in starch index value, so using starch index values alone should not be used to determine apple maturity (Blanpied, 1974;Smock, 1948).…”

Section: Starch-iodine Testmentioning

confidence: 99%

Non-destructive evaluation of apple maturity using an electronic nose system

Pathange

Mallikarjunan

Marini

et al. 2006

Journal of Food Engineering

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The apple growers and packaging houses are interested in methods that can evaluate the quality of apples non-destructively. Harvested fruits are a mixture of immature, mature, and over mature fruits, thereby posing a great problem in deciding their end use and storage time. It is expected that the technique developed from the present project could be effectively used to classify the harvested fruit into immature, mature and over mature apples, rapidly and nondestructively. It would also help the growers to predict the optimum dates to harvest the fruits.York and Gala were the varieties of apples that were used in this study and were obtained from Virginia Tech College of Agriculture and Life Sciences Kentland Farm. Apples were harvested at different times resulting in different maturity groups (immature, mature and ripe).Gala apples were harvested on three dates with an interval of 10 days, while York apples were harvested on four dates with an interval of 14 days. They were stored at 0 o C until sampled. For each harvest date, the experiments were conducted in two sets (10 each) on two consecutive days. First the ethylene levels were measured, followed by gas chromatograph and electronic nose. Then the maturity indices were measured.Three maturity indices, starch index, firmness and soluble solids were used as the three variables for the statistical analysis to identify and categorize the fruits into three maturity categories referred as immature, mature and over mature fruits. Apples were also categorized into three maturity groups based on the emanation levels of the aroma compounds evolved from the fruits. Then electronic nose sensor responses were categorized into the above maturity categories, and their effectiveness was determined using a statistical procedure called Discriminant Analysis (DA). From the DA cross validation results the correct classification percentage for Gala andYork apples into maturity groups was 95%. The Electronic nose sensor's effectiveness to categorize the same observations based on sensor responses in to the above classified maturity categories was 83% correct in case Gala apples and 69% for York apples. The EN sensors response data were analyzed by the EN system software and the correct classification percentage for Gala was 83% and for York was 81%. Aroma-based categorization for Gala apples was 100% correct, while the electronic nose for the same analysis was 80%.Based on the three physical parameters, an objective evaluation of maturity could be accomplished. Principal Component Analysis, Canonical Discriminant Analysis and DA results demonstrated that the electronic nose could be used to classify apples into three identified maturity-based groups. The EN sensors (Gala apples), could also classify the apples into aromabased categories. Thus, it can be concluded that the EN system holds promise as non-destructive evaluation technique to determine the maturity of an apple.iv Acknowledgements

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Use of flesh firmness and other objective tests to determine consumer acceptability of Delicious apples

Cited by 84 publications

References 0 publications

Physico-chemical quality parameters and overall quality index of apple during storage

Physico-chemical quality parameters and overall quality index of apple during storage

Postharvest Treatments on Storage Life of Guava (Psidium guajava L.) in Himalayan Terai Region of West Bengal

Non-destructive evaluation of apple maturity using an electronic nose system

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