RELATIONSHIP BETWEEN SENSORY EVALUATIONS AND NONDESTRUCTIVE OPTICAL MEASUREMENTS OF APPLE QUALITY' ABSTRACT

Similar documents
TRS-Measurements as a Nondestructive Method Assessing Stage of Maturity and Ripening in Plum (Prunus domestica L.)

9/21/2016. Composition and Compositional Changes During Development: Part I. I. Importance of Composition. Phytonutrients or Phytochemicals

Fruit Ripening and Quality Relationships. Stages of Fruit Development. Stages of Fruit Development. Stages of Fruit Development

Relationship Between SSC/TA Ratio and Acceptability of Navel Orange

THE INFLUENCE OF MATURITY DEGREE OF VEGETABLES ON THEIR CUTTING RESISTANCE FORCE

CONSUMERS EVALUATION OF APPLE QUALITY. Anna Marin Food Innovation Center 1207 NW Naito Pkwy, suite 154 Portland, OR

QUALITY and QUALITIES in FOOD PRODUCTS

Fruit Ripening and Quality Relationships. Stages of Fruit Development. Stages of Fruit Development. Stages of Fruit Development

Loss of Flavor Precedes Loss of Appearance Quality. General Principles. General Principles Dietary Guidelines for Americans

Development of apple quality standards for slicing and optimization of sanitation procedures.

Effect of measurement of non-destructive firmness on Tomato quality and comparison with destructive methods

Scientific Papers. Series B, Horticulture. Vol. LVIII, 2014 Print ISSN , CD-ROM ISSN , Online ISSN , ISSN-L

Nondestructive Determination of Sugar Content in Potato Tubers Using Visible and Near Infrared Spectroscopy

SUPPLEMENTAL VITAMIN D 3 AND BEEF TENDERNESS

ph as a Predictor of Flavor, Juiciness, Tenderness and Texture in Pork from Pigs in a Niche Market System

Effect of Storage Conditions and Packaging on Sensory Evaluation of Rice

Vegetable Meeting Food Safety and Postharvest Handling of Vegetables Santa Maria, Sept 25, 2012

Irradiation Quarantine Treatments for Deciduous Tree Fruits

Postharvest Quality of Pitahaya. Minerals: calcium, potassium Vitamins: small amounts of Vitamin C Pigments in red flesh: Betalains Polyphenols

9/21/2016. Composition and Compositional Changes During Development: Part II. V. Major Components of Fruits and Vegetables.

OCTOBER. Apple Tasting. Directions. October Appendix

IV International Symposium Agrosym 2013

OCTOBER. Apple Tasting. Directions. October Appendix

Potential and Limitations for Determining Lycopene in Tomatoes by Optical Methods

Physics Research - Applications Education Implementation of the "Seeing Through Layers" (STL) method for Apples Categorizing

Postharvest Handling Update for Leafy Vegetables

I Pledge Allegiance to My Health

Effect of harvest dates, pre harvest calcium sprays and storage period on physico-chemical characteristics of pear cv. Bartlett.

of guava fruits (Psidium guajava L.)

Effect of Transport Vibration on Quality of Minimally Processed and Packaged Fresh-cut Cantaloupe

Rapid Quality Measurements of Flour and Wheat in the Milling industry. Phillip Clancy, Next Instruments, Australia.

Analysis of the quality attributes of osmotically dehydrated mango

HarvestLab John Deere Constituent Sensing

The Challenges of Honeycrisp Storage: A PACKER S PERSPECTIVE

FACTORS AFFECTING TOMATO SOLIDS

A long family tradition

Technical report: Storage temperatures for shelf-life extension of different cooking banana presentation forms

IMPACTS OF VARIETIES AND FREEZING STORAGE CONDITION ON THE QUALITY OF FRENCH FRIED POTATOES (SOLANUM TUBEROSUM L.)

Evaluation of 50 California Olive Oil at Marketplaces 2016

ECE 105 Chapter 19 Planning and Serving Nutritious and Economical Meals Meal Planning A Good Menu Meets Nutritional Needs

THE QUALITY OF ROSELLE (Hibiscus sabdariffa L.) JUICES MADE FROM ROSELLE CALYCES STORED AT DIFFERENT COLD TEMPERATURES

Physical and Biochemical Changes in Broccoli That May Assist in Decision-Making Related to International Marine Transport in Air or CA/MA

Quality Evaluation of Different Species of Edible Bamboo Shoots

What Are Polyols? Polyols are:

Non-Destructive Evaluation of Apple Maturity Using an. Electronic Nose System

Effect Of Bagging On Chemical Properties Of Mango (MangiferaindicaL.) CV. Alphonso

Journal of Food Biosciences and Technology, Islamic Azad University, Science and Research Branch, 1, 55-62, 2011

Nondestructive determination of total and soluble solids in fresh prune using near infrared spectroscopy

Title Physical, Chemical and Biological E Radiation, VI)

8/6/2015. Training Course. About Cyprus. Cyprus University of Technology (CUT)

COMPARISON OF DISPERSIVE AND FOURIER-TRANSFORM NIR INSTRUMENTS FOR MEASURING GRAIN

Body Composition and Sensory Characteristics of Pork from CLA-Fed Pigs

CHAPTER III MATERIALS AND METHODS

SHELF LIFE EXTENSION OF BANANA (MUSA SAPIENTUM) BY GAMMA RADIATION

Optimization of Blanching Time-Temperature Combination and Pre-Drying Durations for Production of High Quality Potato Chips

Determination of the optimal pre-storage delayed cooling regime to control disorders and maintain quality in Honeycrisp TM apples

Study on the Possibility of Eliminating Sulfuring Process in the Production of Dried Apricots

Handling & Processing Section. Color and Pigment Development of Mature-green Tomatoes Treated with Hot Water

Nutritional and Sensory Analysis of Raspberry Varieties Grown in Northern Nevada

I. Title: The effect of different types of peanut butter on the taste and palatability of

Starch Degradation of Detached Apple Fruit in Relation to Ripening and Ethylene

Preparation of Pineapple (Ananas comosus) Candy Using Osmotic Dehydration Combined With Solar Drying

Evaluation of Mandatory Testing California Olive Oil 2015/16 Season. Submitted to the Olive Oil Commission of California

MONALISA: Non-destructive technologies in post-harvest quality analysis

IRRIGATION AND NUTRITION MANAGEMENT FOR GOOD POSTHARVEST PERFORMANCE JOHN P BOWER

The Climacteric Rise in Respiration Rate of the Fuerte Avocado Fruit

Studies on Chemical Constituents of Stored Bael Squash Prepared from Different Recipes

The effect of the fertilization on biochemical composition of some nectarines fruits varieties

Seasonal Trends in Nutrient Composition of Hass Avocado Leaves 1

Quality of fresh-cut produce

PRINCIPLES OF POSTHARVEST HORTICULTURE. Midterm Exam I. 100 points possible NAME: KEY

Effects of Bio-Based Ingredients on the Development and Quality of Food Wrapper from Jackfruit (Artocarpus heterophyllus Lam.

The right number of consumers to be enrolled in a liking test strongly depends on the level of sensory complexity among products

World Congress on Root and Tuber Crops Nanning, Guangxi, China, January 18-22, 2016

STUDY ON MINERAL NUTRIENT IN MANGO ORCHARD IN IRAN. A. H. Mohebi Date Palm & Tropical Fruit Research Institute of Iran

Factors Affecting the Sensory Quality of Cooked Rice. Jean-François Meullenet University of Arkansas

Effect of packaging and storage condition on the quality of sweet orange (Citrus cinesis)

PROCESSING AND PRESERVATION OF PAPAYA JAM

fruit quality and the development of physiological disorders and rot after storage of apples

Physiological effects of Phytosanitary Irradiation and impacts on fruit quality NICSTAR 2018

Use of Cryoprotectants for Mechanically Deboned Pork

Reducing the calorie content of ingredients without compromising texture and flavour. Jenny Arthur, Head of Nutrition and Product Development

Preparation of value added products from dehydrated bathua leaves (Chenopodium album Linn.)

Effect of Replacing Sucrose with Fructose on the Physico-chemical Sensory Characteristics of Kinnow Candy

CONSUMER ACCEPTANCE TESTING PROCESSED FLORIDA BLUEBERRIES

(Equation 1) (Equation 2) (Equation 3)

Effect of fructooligosaccharide fortification on quality characteristic of some fruit juice beverages (apple &orange juice)

EFFECT OF HEAT AND COLD TREATMENTS ON POST HARVEST QUALITY OF SWEET ORANGE CV. BLOOD RED

Making Forage Analysis Work for You in Balancing Livestock Rations and Marketing Hay

Genetics of pork quality. D. W. Newcom, T. J. Baas, and K. J. Stalder. Dept. of Animal Science, Iowa State University, Ames, IA.

Snacking Your Weigh to Good Health

Update: Processed Meats Cookery and Sensory Evaluation

FATTY ACID COMPOSITION AND EATING QUALITY OF MUSCLE FROM STEERS OFFERED GRAZED GRASS, GRASS SILAGE OR CONCENTRATE-BASED DIETS

RESPONSES TO REGULATED DEFICIT IRRIGATION OF A NECTARINE ORCHARD IN SOUTHERN SPAIN (S15.215)

August 2, Dear Rich:

THE BENEFITS OF WORKING WITH FIBERSOL

Session Four: Vitamins, Minerals, and Fiber

Application of 1-methylcyclopropene reduces wound responses and maintains quality in fresh-cut apple

Effects of chalkiness level on sensory aspects of raw and cooked rice samples

NON-DESTRUCTIVE QUALITY EVALUATION OF DRAGON FRUIT USING ULTRASOUND METHOD ABSTRACT

Transcription:

RELATIONSHIP BETWEEN SENSORY EVALUATIONS AND NONDESTRUCTIVE OPTICAL MEASUREMENTS OF APPLE QUALITY' ALLEY E. WATADA, DAVID R. MASSIE and JUDITH A. ABBOTT Horticultural Crops Quality Laboratory and Instrumentation Research Laboratory, Honiculmral Science Institute, ARS, U.S. Depanment of Agriculture Beltsville, Maryland 20705 Accepted for Publication: September 12, 1983 ABSTRACT A nondestmctive optical method was studied for estimating the sensory quality of Golden Delicious and York Imperial apples. 7he coeficients of determination were signifcant for estimating sweetness of York Imperial, acidity of Golden Delicious and York Imperial, and crispness, hardness, toughness, and juiciness of Gohien Delicious apples using optical measurements. The coeficients of determination were weakest with optical data at a single wavelength, intermediate with optical data compensated for fruit size and drip of instrument current, and strongest with multiple wavelength data. nese analyses indicate that 30 to 50% of the variation in sensory attributes can be accounted for by factors affecting optical density of the fruit at specijc wavelengths. INTRODUCTION A nondestructive optical density method has been described to estimate the quality of foods (Norris 1956). The method has been used to estimate the chlorophyll content of apples, and the chlorophyll content was shown to be correlated with the eating quality (Yeatman and Norris 1965). The chlorophyll content was shown to be correlated inversely with the soluble solids, and the latter related to the dessert quality of the apple (Olsen et al. 1967). Others have shown the chlorophyll content to vary inversely with soluble solids, sweetness, and flavor, and directly with tartness of apples (Aulenbach et al. 1972). In these studies, the quality was based on the chlorophyll content which was estimated by the nondestructive method. This paper describes the use of optical density (OD) of a wide range of wavelengths for estimating sensory quality attributes of apples. Analysis was made with OD at 'Use of a company or product name by the Department does not imply approval or recommendation of the product to the exclusion of others which may also be suitable. Journal of Food Quality I (1985) 219-226. All Rights Reserved @Copyright I985 by Food & Nutrition Press, Inc., Wesport, Connecticut 219

220 ALLEY E. WATADA, DAVID R. MASSIE and JUDITH A. ABBOTT each single wavelength and with multiple wavelengths. Use of multiple wavelengths has been very effective for predicting quality of forage crops (Norris et al. 1956). MATERIALS AND METHODS Golden Delicious and York Imperial cultivars were selected for the study to represent apples that differ widely in color, flavor, and texture. To ensure variation in maturity and storage period, apples were harvested 3 times at weekly intervals and stored for durations of 0, 2.5, and 5 months. At each harvest, about 200 fruit were picked randomly from a commercial orchard and divided into 3 comparable lots for initial analysis and for analysis after 2.5 and 5 months storage in 0 C air. Apples were stored in perforated plastic bags within fiberboard containers. Freshly harvested or stored apples were held for 7 days at 20 "C before they were analyzed. Sixteen apples were selected from each lot and coded for maintaining identity throughout the analyses. The OD of each fruit was measured individually, and 8 of the 16 fruit were individually puncture tested (Magness-Taylor firmness probe mounted in an Instron Universal Testing Machine) and rated for sensory textural attributes, and the remaining 8 were individually rated for flavor sensory attributes and chemically analyzed for soluble solids and titratable acid. Thus, a total of 144 apples of each cultivar were tested for flavor and 144 for texture. The optical densities were measured from 640 to 950 nm at 10 run intervals with a high-intensity spectrophotometer (Massie and Norris 1975). To compensate for the variation in fruit size, the OD of each wavelength was divided by the cube-root of the mass and these values are noted as ODADJ. To compensate for variation in both fruit size and instrument current drift, the OD at 720 nm was subtracted from the OD at each of the other wavelengths, and these values are noted as AOD. Regression analyses were made with all 3 sets of data, i.e., OD, ODADJ, and AOD for the textural study, and only OD and AOD for the flavor study because fruit-mass data were not collected in the flavor study. The 14 panelists for the sensory evaluations were trained in basic profile techniques as described elsewhere (Watada ef al. 1980). Each individual fruit was rated for textural or flavor attributes by four panelists, and the average scores of the 4 panelists were used in the statistical analyses. Firmness tests and analyses for soluble solids and titratable acids have been described elsewhere (Watada et al. 1980). Individual fruit data were used for the correlation analyses between optical measurements and sensory and chemical data. The individual fruit data were also used for the stepwise multiple regression analyses for each of the 15 sensory attributes on the OD, ODADJ, or AOD for each cultivar. The maximum RZ improvement program (SAS) was set with significance to enter and to remain at the 0.05 level and with a maximum of 5 steps.

APPLE QUALITY MEASURED OPTICALLY 22 1 Table 1. Sensory and objective evaluations of Golden Delicious and York Imperial apples. Attribute Golden Delicious York Imperial Average Minh M w h Average Mininnun Maximum sensory maluationl Flavor Sweetness kidity Starchiness Spiciness Wstiness Astringency Texture Crispness lixdness l'bu@ness Mealiness Juiciness Cbjective Evaluation Firmness (newtons) Soluble solids (%) Titratable acids (%) 55 36 80 49 22 61 32 5 76 45 14 71 22 2 57 25 2 59 21 3 44 22 6 54 11 2 47 13 1 41 26 2 69 32 3 70 40 11 81 61 35 84 28 4 75 50 24 88 22 3 69 40 9 80 30 3 74 16 1 42 44 21 70 48 28 74 45 26 88 78 50 131 13.3 10.6 18.5 12.6 9.6 15.0 0.34 0.13 0.80 0.49 0.25 0.23 1 ~ased on 100-point intensity scale. Sensory RESULTS AND DISCUSSION The flavor profile panel selected sweetness, acidity, astringency, mustiness, floralfruitiness, and starchiness as attributes associated with the flavor and taste of apples. Scores for all attributes, except floral-fruitiness of Golden Delicious and York Imperial and sweetness of York Imperial, changed significantly with storage (data not presented). Thus, a wide range of scores was available for the correlation analysis. On a 100-point scale, the range between the minimum and maximum scores was 44 points or greater for all attributes except spiciness of Golden Delicious (Table 1). The range differed with attribute. For a given attribute, the width of ranges of the 2 cultivars were similar, except for acidity; the acidity range for York Imperial was about 90% of the range for Golden Delicious.

222 ALLEY E. WATADA. DAVID R. MASSE and JUDITH A. ABBOTT The average scores of a given attribute were similar for the 2 cultivars except sweetness and acidity. The average score for sweetness of Golden Delicious was higher than that of York Imperial and the reverse of this occurred with acidity. The texture profile panel selected crispness, hardness, toughness, mealiness, and juiciness as attributes associated with texture of apples. Scores of all these attributes, except mealiness of York Imperial, changed significantly with storage (data not presented). The range between the minimum and maximum scores was 46 points or higher for all attributes except mealiness of York Imperial (Table 1). As with flavor, the range differed with attribute; however, the ranges for a given textural attribute were not similar for the 2 cultivars. The average scores of the 2 cultivars differed by about 20 points for each attribute except juiciness. The average scores for crispness, hardness, and toughness were lower, and mealiness was higher for Golden Delicious than those for York Imperial. Flavor Versus Optical Measurements Of the flavor attributes, only acidity and sweetness of York Imperial and acidity of Golden Delicious were significantly correlated with the optical data (Table 2). The wavelengths correlating with acidity were not the same for the 2 cultivars. With York Imperial, the correlation occurred with wavelengths in the 650 to 690 nm range, whereas, with Golden Delicious, the correlation was with wavelengths in the 650 to 670 nm and 931) to 940 nm range. The coefficient of determination (R2) was larger when the AOD were used rather than the OD value, which would be expected because variations in h it size and instrument current drifts are compensated in the AOD values. Wavelengths correlating with sweetness of York Imperial were the same as those correlating with acidity when the analysis was made with OD. When the analysis was made with AOD, additional wavelengths in the 780 to 820 nm range and the 930 to 950 nm range were found to be correlated with sweetness. In examining the best 5-wavelength combination for estimating sweetness, the wavelengths were not similar for both cultivars. With York Imperial, the selected wavelengtb covered a broad spectrum of 640 to 930 nm; whereas, with Golden Delicious they were concentrated in the longer wavelength range of 870 to 940 nm. The R2 was only 0.50 and 0.43, respectively. The best 5-wavelength combination for estimating sweetness of York Imperial covered a broad spectrum similar to that noted with acidity, but the wavelengths were slightly longer. No 5-wavelength combination was significant for estimating sweetness of Golden Delicious. Constituents responsible for sensory acidity and affecting the OD appear to differ between the 2 cultivars. This is indicated by the fact that the 2 cultivars differed in the multiple wavelengths that were selected for both sensory acidity and titratable acids. The multiple wavelengths selected for estimating titratable acids were longer for Golden Delicious than for York Imperial with the R2 being 0.46 and 0.53, respectively.

APPLE QUALITY MEASURED OPTICALLY 223 Table 2. Coefficient of determinations (Rz) for sensory flavor and chemical attributes versus optical density of apples. A range of RZ values presented for a range of wavelengths. Cult ivar Optical Wavelergth Pcidity Sweetness value (nm) (R2) (RZ) Titratable acids Soluble solids (R21 (R2) York Imperial 09 650-690.27-. 34.28-. 31 AOD~ 660-670.36-. 41.30-. 32 780-820.30-.32 930-950 Stepise3 640,700,790, -50 of AOD 840,930 690,710,930, -- 940,950 660,690,730, -- 750,800 640,650,730, -- 760,920.34-.36.42.53.62 Golden Delicious OD 650-670.22-. 23 0, 930-940.22-.23 &OD 640-820.24-. 28 940-950.34 StepJise 870,880,920,.43 of AOD 930,940 - -- 5 790,800,810, 910,950 740,760,800, 910,950.46.52 1 Optical density (OD) of whole intact fruit at a single wavelength within stated ralqe. * OD at 720 nm subtracted from OD of each of other wavelergths. 3 Selection of 5 best waveleqths by stepdise regression analyses based on AOD (Wximum 72 improvement, P to enter and P to stay set a t 0.05).

224 ALLEY E. WATADA, DAVID R. MASSIE and JUDITH A. ABBOTT Table 3. Coefficients of determinations (R2) for sensory textural attributes versus optical density of apples. A range of R2 values presented for a range of wavelengths. Optical Wavelergth C r i y s Toughness Juiciness Chltivar value (nm) (R ) (R2) (R2) Golden Delicious OD1 650-680.28-. 34.34-. 38.27-. 30 0Dm2 650-680.28-.34.34-.37.25-.28 GOD^ 940-950 650-680.35-.38.34-. 38.31-. 35.38-. 41.30-.35.30-. 31 ~tepiise4 Of AOD 940-950 670,700,710, 920,940.37.53.37-.38-35-.37 670,690,930, 94 0,950.48 680,700,710, 730,950.47 York Imperial OD n. s ODADJ nod n.s n.s Stepiise n. s. n. s. 1 Optical density (OD) of whole fruit. 2 OD divided by cube-root of mass. 3 OD at 720 nm subtracted from OD of each other wavelength. 4 Selection of 5 best by steprlise regresssion analysis based on AOD. Texture Versus Optical Measurements The textural attributes of only Golden Delicious correlated with the optical data and the attributes were limited to crispness, toughness, and juiciness (Table 3). Correlations were significant with OD at wavelengths in the 650 to 680 nm range. The correlation was found to be significant also with measurements at 940 and 950 nm when fruit was adjusted on the basis of mass (ODADJ) or optically (AOD). The coefficients of determination were slightly greater when using AOD values than OD or ODADJ values.

APPLE QUALITY MEASURED OPTICALLY 225 The best 5-wavelength combination for estimating crispness, toughness, or juiciness were all similar. This similarity is not surprising because these attributes correlated very highly with each other (data not shown). The selected wavelengths were in the 670 to 730 nm and 920 to 950 nm regions and the question arises as to the identity of textural factors which absorb at these wavelengths. The absorbing components responsible for the correlation between optical and textural data may not be textural factors, but factors closely associated with textural changes. For example, chlorophyll and carbohydrates change with texture and they absorb at the 660 and 930 nm regions, respectively. These and other components which change with texture and have absorption properties may be responsible for the correlations. The lack of correlation between sweetness and optical measurements of Golden Delicious is puzzling. The average score for sweetness of Golden Delicious was higher than that of York Imperial and the widths of the range were similar for both cultivars. Carbohydrates absorb at the longer wavelengths of 910 to 950 nm (personal communication of Karl Norris, USDA, Beltsville, MD) so correlations were anticipated between sweetness and optical data at the longer wavelengths, providing absorption by other carbohydrates did not mask absorption by sugar. The lack of correlation probably was due to some factor such as acidity affecting the sensory response to sweetness. This is supported by the nonsignificant correlation between sweetness and soluble solids, the latter being an indicator of sugar content. Soluble solids did correlate with the optical data and in estimating the contents by multiple wavelengths, the coefficients of determination were 0.62 and 0.52, respectively, for York Imperial and Golden Delicious. The lack of correlation between textural and optical measurements found in our study with York Imperial was also noted by Aulenbach et al. (1972) with Delicious apples. The textural characteristics of these 2 cultivars are similar in terms of intensity and minimal change with storage as indicated by firmness measurements (Watada et al. 1980). In our study, the coefficients of determination for firmness versus crispness and toughness of York Imperial were 0.40 and 0.43, respectively. Since these attributes can be estimated by the physical measurements of either cultivar and by the optical measurement of Golden Delicious, the lack of correlation between the optical and textural data of York Imperial suggests that its OD values associated with the textural attributes were affected by other absorbing constituents. This needs to be examined in future studies. We conclude that the effectiveness of estimating the intensity of sensory attributes by the optical technique was improved by using multiple wavelengths. The selected wavelengths generally constituted a wide range of wavelengths and were not necessarily the same for a given attribute for the 2 cultivars. Only about 50% of the variations in sensory attributes can be accounted for by factors affecting optical density. This percentage needs to be increased substantially before the optical method can be used in commercial grading.

226 ALLEY E. WATADA, DAVID R. MASSIE and JUDITH A. ABBOTT REFERENCES AULENBACH, B. B., YEATMAN, J. N. and WORTHINGTON, J. T. 1972. Quality sorting of Red Delicious apples by light transmission. U.S.D.A. Marketing Research Report No. 936, pp. 21. MASSIE, D. R. and NORRIS, K. H. 1975. A high-intensity spectrophotometer interfaced with a computer for food quality measurement. Transactions ASAE 18(1), 173. NORRIS, K. H. 1956. Measurement of quality in foods and agricultural commodities by physical methods. In Proc. First Food Physics Symposium, Inst. Food Technol. pp. 113-124. NORRIS, K. H., BARNES, R. F., MOORE, J. E. and SHENK, J. S. 1976. Predicting forage quality by infrared reflectance spectroscopy. J. Animal Sci. 43(4), 889-897. OLSEN, K. L., SCHOMER, H. A. and BARTRAM, R. D. 1967. Segregation of Golden Delicious apples for quality by light transmission. Amer. SOC. Hort. Sci. Proc. 91, 821-828. WATADA, A. E., ABBOTT, J. A. and HARDENBURG, R. E. 1980. Sensory characteristics of apple fruit. J. Amer. SOC. Hort. Sci. 105(3), 371-375. YEATMAN, I. N. and NORRIS, K. H. 1965. Evaluating internal quality of apple with new automatic fruit sorter. Food Technol. 19(3), 123-125.