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  • Author or Editor: G. G. Dull x
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Abstract

In addressing the subject of nondestructive evaluation of internal quality of horticultural crops, the establishment of an understanding of quality is needed at the outset. Dull (4) has defined nondestructive quality evaluation (NDQE) as “a gaining of meaningful information which can be used in making judgments, both positive and negative, about the degree of excellence of a food with out altering the physical and chemical properties of that food.” In order to make judgments about a specific quality situation, one must select specific physical and/or chemical properties to be measured. A list of those properties would include weight, diameter, titratable acidity, pH, total nitrogen and concentration of soluble solids, sucrose, glucose, fructose, malic acid, citric acid, chlorophyll, carotene, anthocyanins, dry matter, proteins, amino acids, fat, starch, cellulose, pectins, and hemicellulose.

Open Access

Abstract

The effect of N source ( NO 3 , NH 4 + ) and N concentration on amino acid patterns was determined for seeds of Vigna unguiculata (L.) Walp. (southernpea, cowpea) cv. Pinkeye Purple Hull. The lowest amino acid content was obtained when NO 3 supplied all of the N. At 75 ppm N, amino acids and proteins in seeds were increased as the ratio of NH 4 + to NO 3 was increased. N source, at 150 ppm N, had no effect on amino acid content. Increasing total N from 75 ppm to 150 ppm increased protein levels. Protein quality was unaffected by changing the NO 3 : NH 4 + ratios or by doubling the N concentration. The limiting amino acid was methionine.

Open Access

Abstract

High speed reflected light spectrophotometry was used to determine an optimum maturity distribution of mechanically harvested clingstone peaches (Prunus persica (L.) Batsch) for processing. Succinic acid-2,2-dimethylhydrazide (SADH) applied at pit-hardening, advanced the optimum harvest date from 3 to 5 days and increased the yield of processable fruit from 62% for the control trees to 80% for the treated trees.

Open Access

An instrument based on near infrared (NIR) reflectance techniques is described which is capable of determining nondestructively the percent soluble solids in whole honeydew, cantaloupe and watermelon samples. It utilizes a tilting interference filter technology for wavelength scanning and a silicon detector/amplifier for the detection of radiation which has penetrated through inner melon flesh. The standard error of prediction is of the order of 1.2 percent soluble solids for honeydew melons when compared with a standard refractometer analysis.

Free access

A near-infrared spectrophotometric method for estimating the soluble solids in honeydew melons is presented. The method is based on a body transmittance geometry in which the angle between the source incident beam and the detector is approximately 45°. The regression analysis of the spectral and chemical data utilizes a ratio of two second derivatives and resulted in a correlation coefficient of 0.85 and a standard error of calibration of 1.5. The numerator wavelength occurs in a carbohydrate absorption band, thus the method can be interpreted as a measurement of carbohydrates.

Free access

Spatial variation in soluble solids content (SSC) of fruits of apple (Malus ×domestica Borkh. cv. Red Delicious), cantaloupe (Cucumis melo L. Cantaloupensis group), grapefruit (Citrus paradisi Macf. cv. Indian River Ruby Red), honeydew melon (Cucumis melo L. Inodorus group), mango (Mangifera indica L. cv. Hayden), orange (Citrus sinensis L. Osbeck. cv. Valencia), peach (Prunus persica L. Batsch. cv. Windblow), pineapple (Ananas comosus L. Merr. cv. Kew) and tomato (Lycopersicon esculentum Mill.), and of bulbs of onion (Allium cepa L. Cepa group) and in dry-matter content (DMC) of potato (Solanum tuberosum L. cv. Russet Burbank) tubers was measured along three directional orientations (i.e., proximal to distal, circumferentially midway along the proximal to distal axis, and radially from the center of the interior to the outer surface). The pattern and magnitude of constituent variation depended on the type of product and the direction of measurement. Radial and proximal to distal variation was greater than circumferential variation in all the products tested. Honeydew had the highest radial variation with a SSC difference of 6.0 % and a cv of 22.8%, while tomato displayed lower radial variation with a cv of 1.0%. Pineapple had a proximal to distal SSC difference of 4.6% with a cv of 13.8%, while the difference in tomato was 0.6% with a cv of 5.1%. Circumferential variation of SSC in all products tested was <2% with cv ranging from 1.1% to 3.8%. The results confirm that considerable constituent variability exists within individual fruit and vegetable organs. This variability may affect the accuracy of calibration equations and their prediction capability. Therefore, within-unit constituent variability should be meticulously assessed when an NIR spectrometric method is being developed for the nondestructive quality evaluation and sorting of a product.

Free access

A nondestructive method for measuring the soluble solids (SS) content of peaches [Prunus persica (L.) Batsch] was developed using near-infrared (NIR) spectrometry. NIR transmittance in the 800 to 1050 nm region was measured for four cultivars of peaches (`Blake', `Encore', `Red Haven', and `Winblo'), over a period of three seasons (1993 through 1995). Each fruit was scanned on both halves keeping the suture away from the incident light beam. Soluble solids contents of flesh samples taken from corresponding scanned areas were determined using a refractometer. Multiple linear regression models using two wavelengths were developed with second derivative spectral data and laboratory measurements of SS content. Multiple correlation coefficients (R) for individual cultivar calibrations within a single season ranged from 0.76 to 0.98 with standard error of calibration (SEC) values from 0.35% to 1.22%. Selected spectra and corresponding SS data in individual cultivar calibration data sets were combined to create season and cultivar calibration data sets to cover the entire range of SS contents within the season or within the cultivar. These combined calibrations resulted in R values of 0.92 to 0.97 with SEC values ranging from 0.37% to 0.79%. Simple correlations of validations (r) ranged from 0.20 to 0.94 and the standard error of prediction (SEP) ranged from 0.49% to 1.63% while the bias varied from -0.01% to -2.62%. Lower r values and higher SEP and bias values resulted when individual cultivar calibrations were used to predict SS levels in other cultivar validation data sets. Cultivar calibrations, season calibrations and the overall calibration predicted SS content of all validation data sets with a smaller bias and SEP and with higher r values. These results indicate that NIR spectrometry is suitable for rapid nondestructive determination of SS in peaches. Feasible applications of the method include packinghouse sorting of peaches for sweetness and parent and progeny fruit quality assessment in peach breeding programs. Using this technique fruit may be sorted into two or three sweetness classes. The technique may also potentially be extended to other fruit.

Free access

A nondestructive method for measuring the soluble solids content (SSC) of individual processing tomatoes (Lycopersicon esculentum Mill.) was developed using NIR spectrometry. A diode array fiber optic spectrometer was used to measure NIR transmittance. Each fruit was scanned at two locations on opposite sides midway along the proximal-distal axis. After scanning, each fruit was processed and pureed, and SSC was determined using a refractometer. Multiple linear regression (MLR), partial least squares (PLS) regression, and neural network (NN) calibration models were developed using the second derivatives of averaged spectra from 780 to 980 nm. The validation results showed that NN calibration was better than MLR or PLS calibrations. The NN calibration could estimate the processed SSC of individual unprocessed tomatoes with a standard error of prediction of 0.52% and could classify >72% of fruit in an independent population within ±0.5% of SSC.

Free access

Abstract

The techniques used in near infrared spectrophotometry for nondestructive analysis of agricultural products were applied to determine the percentage of dry matter (% DM) of intact onions (Allium cepa L). Transmittance data were recorded for the 700 nm to 1000 nm spectral region. Second derivative data processing was used with a stepwise multiple regression analysis to develop an equation to predict the % DM of individual onions. The correlation between optical data and % DM was 0.996. In a 2nd and completely independent experiment, we obtained equivalent results demonstrating the repeatability of the method. This repeatability was demonstrated even further through the satisfactory field testing of a portable instrument.

Open Access

Abstract

The terminology used to describe developmental stages of fruits is often confusing or even misleading. “Mature” and “ripe” are often used synonymously. We find reference to “green” fruit, based on skin or peel color, used interchangeably with “unripe”, the latter without referring to pigmentation but rather to a state of non-palatability. We see in the literature such words used synonymously as “overripe” and “senescent” in describing a fruit in a very late stage of development. Such terms as “early maturity”, “optimum maturity”, or “full maturity” leave some doubt as to what stage is actually under consideration. At best, different authors are not always referring to the same stage, even when dealing with the same fruit.

Open Access