Stem-calyx Axis Research Articles

Online soluble solids content (SSC) assessment of multi-variety tomatoes using Vis/NIRS diffuse transmission

This study investigates the potential of the online diffuse transmission Vis/NIRS technology for quantitative soluble solids content (SSC) assessment of multi-variety tomatoes. For every single-variety tomato, the stem-calyx axis horizontal with stem towards (T1 orientation) is verified to be the best detection orientation with the simpler propagation light path or shorter light path distance. Compared to the full wavelength after Savitzky-Golay smoothing (SGS) pretreatment, the partial least squares regression (PLSR) model performance can be further improved by the selected Competitive Adaptive Reweighted Sampling (CARS) key wavelengths. The best CARS-PLSR model performances are Tianci-595 (Rp = 0.85, RMSEp = 0.21), Xianke-No.8 (Rp = 0.87, RMSEp = 0.20), and Yuanwei-No.1 (Rp = 0.87, RMSEp = 0.35), respectively. For multi-variety tomatoes, it is difficult to find a universal SSC prediction method regardless of mutual prediction between different models or mixed models of different tomato varieties. Our results in the present study reveal the potential for online diffuse transmission Vis/NIRS technology as a valuable method for tomato SSC assessment. The potential of key wavelengths in multi-variety tomatoes' universal SSC prediction requires further experimental verification and optimization.

Effects of Orientations and Regions on Performance of Online Soluble Solids Content Prediction Models Based on Near-Infrared Spectroscopy for Peaches

Predicting the soluble solid content (SSC) of peaches based on visible/near infrared spectroscopy has attracted widespread attention. Due to the anisotropic structure of peach fruit, spectra collected from different orientations and regions of peach fruit will bring variations in the performance of SSC prediction models. In this study, the effects of spectra collection orientations and regions on online SSC prediction models for peaches were investigated. Full transmittance spectra were collected in two orientations: stem-calyx axis vertical (Orientation1) and stem-calyx axis horizontal (Orientation2). A partial least squares (PLS) method was used to evaluate the spectra collected in the two orientations. Then, each peach fruit was divided into three parts. PLS was used to evaluate the corresponding spectra of combinations of these three parts. Finally, effective wavelengths were selected using the successive projections algorithm (SPA) and competitive adaptive reweighted sampling (CARS). Both orientations were ideal for spectra acquisition. Regions without peach pit were ideal for modeling, and the effective wavelengths selected by the SPA led to better performance. The correlation coefficient and root mean square error of validation of the optimal models were 0.90 and 0.65%, respectively, indicating that the optimal model has potential for online prediction of peach SSC.

Online analysis of watercore apples by considering different speeds and orientations based on Vis/NIR full-transmittance spectroscopy

Watercore is a common internal disorder of ‘Fuji’ apples, which affects the quality and price of fruit. Moreover, the flesh of watercore apples is prone to browning during storage, resulting in a loss of commercial value. However, the online detection of watercore apples is very difficult in actual production due to the interference of many factors. In this study, visible and near infrared (Vis/NIR) full-transmittance spectroscopy (680-1000 nm) was used to online analyze watercore apples. Three different detection orientations (O1, O2 and O3) and speeds (S1, S2 and S3) were compared in detail. In order to determine the optimal detection speed and orientation, the partial least square discriminant analysis (PLS-DA) and least squares-support vector machine (LS-SVM) models were established based on the preprocessing spectra of Savitzky-Golay smoothing and standard normal variate (SGS-SNV). The results showed that S2 speed (0.5 m/s) and O3 orientation (apple stem-calyx axis horizontal and parallel to the moving direction of conveyor belt) were the most suitable for detection of watercore apples. A combination algorithm (MC-UVE-SPA) of Monte Carlo-uninformative variable elimination (MC-UVE) and successive projections algorithm (SPA) was used to select effective wavelengths for classification of watercore apples and quantitative prediction of watercore degree. MC-UVE-SPA-PLS-DA and MC-UVE-SPA-LS-SVM models established based on effective wavelengths obtained the same classification performance with the success rates of 100 % and 96.87 % for healthy and watercore apples, respectively. In order to predict the watercore degree of apples, the partial least squares (PLS), multiple linear regression (MLR) and LS-SVM models were established based on spectra obtained S2 speed and O3 orientation. MC-UVE-SPA-LS-SVM model coupled with eight effective wavelengths obtained the optimal prediction accuracy of watercore degree with 0.93 of RP and 2.12 % of RMSEP. The overall results indicated that online detection of watercore apples based on Vis/NIR full-transmittance spectroscopy was feasible, and the classification accuracy was related to the detection speed and the sample orientation. In addition, the results also showed that the LS-SVM model has good performance for classification of watercore apples and quantitative evaluation of watercore degree.

Optimization and compensation of models on tomato soluble solids content assessment with online Vis/NIRS diffuse transmission system

This study developed an efficient and compensable model for predicting soluble solids content (SSC) of tomato, based on the self-developed online Vis/NIRS diffuse transmission system. The fruit stem-calyx axis horizontal coupled with suitable light settings (path and intensity) was determined as the best measurement parameters, which significantly reduce the stray light and also optimize the light propagation inside tomato. The pretreatment method of Savitzky-Golay smoothing (SGS) combined with multiplicative scatter correction (MSC) could eliminate the spectral difference between samples and the inherent system noise in the raw spectral of tomato. The partial least squares regression (PLSR) model based on the 22 key wavelengths selected by competitive adaptive reweighted sampling (CARS) had better model performance than the full wavelength model. Finally, the CARS-PLSR model was further optimized by compensating physiological traits of height and weight with Rp of 0.91 and RMSEp of 0.17%. Our results in the present study demonstrated the potential of using online Vis/NIRS diffuse transmission spectra combined with model optimization and compensation as a valuable method for tomato SSC assessment.

Three-finger grasp planning and experimental analysis of picking patterns for robotic apple harvesting

Operational efficiency is an important bottleneck in the industrialization of apple picking robots. The action planning of grasping and picking is key to improving the operational efficiency of picking robots. In this study, first, from the perspective of grip stability, the grasping positions of a three-finger end-effector were planned in two cases to determine an optimal three-finger grip posture: one that is parallel to the apple stem–calyx axis and the other being centripetal to the apple equatorial plane. Second, based on the gripping posture parallel to the apple stem-calyx axis, four picking patterns were designed: vertical pull, horizontal pull, vertical rotation, and rotation–horizontal pull. With the horizontal displacement, vertical displacement, and rotation angle as the main factors influencing the picking process, it was found through ABAQUS simulation software and the response surface analysis method that the rotation–horizontal pull pattern with the combination of horizontal displacement and rotation angle yields the minimum separation force for apple piking. With the three-fingered hand in the optimal grasping posture parallel to the stem–calyx, the four picking patterns were tested on a dedicated apple picking experimental device equipped with a grip force acquisition sensor, and the test results showed that the average three-finger grip force required for rotary tug-pull picking was the lowest (10.33 N). The proposed rotation–horizontal pull pattern with the three-finger grip posture was proven to be the best pattern for apple picking. The results of this study provide a theoretical basis for further research on apple picking robots.

Multi-factor fusion models for soluble solid content detection in pear (Pyrus bretschneideri ‘Ya’) using Vis/NIR online half-transmittance technique

Development of the online and nondestructive technologies for inspecting and grading the quality of fruit in the postharvest period can improve industry competitiveness and profitability. The effect of fruit temperature, diameter and weight on online evaluation system of soluble solids content (SSC) of ‘Ya’ pears using visible/near infrared (Vis/NIR) spectroscopy was studied. To establish calibration models, partial least square (PLS) regression and least squares-support vector machine (LS-SVM) were employed in 630–900 nm and two fruit orientations (stem-calyx axis vertical with stem upward (T1), stem-calyx axis horizontal with stem towards belt moving direction (T2)), respectively. After pretreatments of Savitzky-Golay smoothing (SGS), multiplicative scattering correction (MSC), standard normal variate (SNV), and competitive adaptive reweighted sampling (CARS) for effective wavelength (EWs) selection, models were optimized and compared to evaluate calibration strategies. 36 EWs using PLS (rp = 0.89, RMSEP = 0.56) with the consideration of diameter (T1) and 34 EWs using LS-SVM (rp = 0.90, RMSEP = 0.57) with the consideration of temperature and diameter (T2) were finally selected, respectively. The fusion information of temperature and diameter showed beneficial effect and the best prediction results based on the designed online Vis/NIR half-transmittance system after MSC and 7-SGS for SSC evaluation of pears using LS-SVM, which would be effective to simplify models and promote computing efficiency and further make this proposed nondestructive detection technique have thepractical application.

An optimal zone combination model for on-line nondestructive prediction of soluble solids content of apple based on full-transmittance spectroscopy

High accuracy on-line estimation for fruit internal quality is still a challenge due to varying geometric structures and orientations. In this study, multiple full-transmittance spectra were collected using short-integration-time mode for each apple. The signal-to-noise ratio of each collected spectrum changed with the measurement position of the fruit due to the heterogeneity of internal composition. To explore the distribution character of transmittance spectra across the apple structure to guide the development of an on-line fruit quality determination system, a methodology which we called ‘zone combination modelling’ was proposed for selecting the most effective spectra for SSC prediction. The orientation of stem–calyx axis vertical was selected as the preferred orientation for quality prediction of ‘Fuji’ apple based on the analysis of the variation and quality of full-transmittance spectra. The most ineffective and most effective zone combinations for SSC prediction were determined by investigating the effect of transmittance spectra within different zone combinations on SSC prediction ability. Ten effective wavelengths selected from the most efficient zone combination were used to develop an optimal prediction model. Results showed that the contribution of different spectral measurement zones to SSC prediction capability varied and that in particular, those collected from the apple core zone should be removed when building SSC prediction models. The coefficient of determination and root mean square errors of prediction and validation sets of SSC, respectively, were 0.733 and 0.61%, 0.721 and 0.71% for the optimal model, indicating that zone combinations model was promising for SSC prediction of apple.

Optimization and comparison of models for prediction of soluble solids content in apple by online Vis/NIR transmission coupled with diameter correction method

The online system can achieve high efficiency towards fruit quality determination in postharvest period. Thus, developing online and nondestructive technology for inspecting and grading fruit is meaningful and profitable in the existing robotic sorting systems. In this study, the effect of fruit diameter differences on online prediction of soluble solids content (SSC) of ‘Fuji’ apples based on visible and near-infrared (Vis/NIR) spectroscopy was studied. Partial least square (PLS) regression was employed to establish calibration models based on three wavelength regions (675–1025, 710–980, 750–1025 ​nm) and two fruit orientations (stem-calyx axis vertical with stem upward (T1) and stem-calyx axis horizontal with stem towards light source (T2)), respectively. A novel diameter correction method was proposed to reduce the effect of fruit diameter differences on original spectra. Combined with pretreatment and effective wavelength (EWs) selection methods, models were optimized and compared to determine the best calibration strategy. Diffuse transmission spectra in 710–980 ​nm and diameter correction method with calculated attenuation coefficient were testified much better than other corresponding regions and correction methods, respectively. Baseline offset correction (BOC) and 7-point Savitzky-Golay smoothing (SGS) of pretreatments and competitive adaptive reweighted sampling (CARS) of EWs selection methods were proved to be outstanding among other methods. 59 and 63 ​EWs achieved the best detection accuracies with correlation coefficient of prediction (rp) and root mean square error of prediction (RMSEP) of 0.92 and 0.50 °Brix, 0.89 and 0.56 °Brix for T1 and T2, respectively. The overall results indicated that online Vis/NIR transmission spectra after BOC and 7-SGS with proposed diameter correction method can make the variation of fruit diameters a small interference for SSC determination, and CARS-PLS would be effective to simplify models and promote computing efficiency to make this nondestructive detection technique promisingly applied.

Detection of internal defect of apples by a multichannel Vis/NIR spectroscopic system

Abstract This paper reports on nondestructive detection of internal defect in apples by using a new noncontact multichannel spectroscopic system in semi-transmittance mode for the visible and near-infrared (Vis/NIR) range of 550-1,650 nm. The specially designed multichannel system consists of six optical fibers arranged in a 360-degree configuration for improved evaluation of each fruit. Spectra were acquired for 430 ‘Honeycrisp’ apples, 243 of which were good (defect free) and 187 internally defective. To assess the effect of fruit orientation on defect detection, each apple was measured in three orientations (i.e., the stem-end facing the light source (A), the calyx end facing the light source (B) and the stem-calyx axis being perpendicular to the light source(C)). Classification models based on partial least squares discriminant analysis (PLSDA) were established for spectra of each detection fiber and mean spectra of the six detection fibers, to compare their performance for internal defect detection. Results showed that classification results varied with detection fiber and fruit orientation. Mean spectra for each fruit orientation gave consistently better classifications, with the overall accuracies of 91.5%, 89.2% and 93.1% for orientations A, B and C, respectively. Moreover, the best PLSDA models had lower misclassification rates for good apples (4.3%) than for defective apples (10.0%). Furthermore, significantly better classification results for mildly defective apples were obtained when using mean spectra than using spectra of each detection fiber. The multichannel Vis/NIR spectroscopic system is thus advantageous for detection of internal defects, especially those localized ones, in apples.

Effect of spectral measurement orientation on online prediction of soluble solids content of apple using Vis/NIR diffuse reflectance

The effect of variation of fruit orientation on online prediction of soluble solids content (SSC) of ‘Fuji’ apples based on visible and near-infrared (Vis/NIR) spectroscopy was studied. The diffuse reflectance spectra in 550–950 nm were collected with a designed online system in six orientations: stem-calyx axis vertical with stem upward (T1) and stem downward (T5), 45° between stem-calyx axis and horizontal with stem slope upward (T2) and stem slope downward (T4), stem-calyx axis horizontal with stem towards computer side lights (T3), stem-calyx axis horizontal with stem towards belt movement direction (T6). The 180 samples with SSC range of 8.00–13.60°Brix were divided into 135 of calibration set with 1.09 standard deviation (S.D.) and 45 of prediction set with 0.85 S.D. The signal-to-noise ratio (SNR) and area change rate (ACR) were used to evaluate the stability of collected spectra. After the comparison of different preprocessing methods, partial least squares (PLS) and least squares-support vector machine (LS-SVM) were used to develop compensation models of SSC for each orientation separately (local models) and all orientations (global model), respectively. Finally, competitive adaptive reweighted sampling (CARS), successive projection algorithm (SPA), and their combination were used to select the effective wavelengths (EWs), respectively. Results showed that T1 performed better for our system and influence of measurement orientation on spectra greatly affected SSC prediction accuracy. Comparatively, global model was insensitive to fruit orientation variation. 37 EWs selected by CARS-SPA-PLS model after Savitzky-Golay smoothing in all orientations achieved better results with rp and RMSEP of 0.815, 0.818, 0.837, 0.731, 0.807, 0.842 and 0.487, 0.484, 0.460, 0.573, 0.497, 0.453°Brix, respectively. Generally, global model with EWs could be promisingly used for online SSC prediction of apple.

Minimally destructive assessment of mangosteen translucency based on electrical impedance measurements

Electrical impedance spectroscopy in a frequency range of 1 kHz–200 kHz was studied to develop a classifying model for translucent mangosteen. The optimal configuration of the measurement was investigated. Transverse alignment of two measuring needles with the stem–calyx axis and with the measured position on the part of the pericarp pertinent to the largest flesh segment proved to be the optimal configuration. The optimal electrical parameters were selected at frequencies of 1, 4, 7, 8, 14, 47, 73, and 81 kHz as the classifying variables based on the student t-test analysis for a significant difference between the normal and translucent mangosteen and the largest difference of the average values of the electrical parameters. The differences in the electrical parameters and their reciprocals were the optimal classifying variables. The model constructed from the samples from two seasons was robust in terms of seasonality, providing a classification accuracy of 82.7%. The difference in the initial moisture content of the pericarp was justifiably compensated by the differences in the electrical parameters. The EIS technique was suitable for measurement of mangosteen samples at the maturity color stage in which the sample contained no yellow latex in the pericarp.

Using Vis/NIR Diffuse Transmittance Spectroscopy and Multivariate Analysis to Predicate Soluble Solids Content of Apple

The objectives of this research were to compare the effect of different fruit orientations on the quality of acquired spectra and to provide a suitable calibration model for further online determination of soluble solids content (SSC) of “Fuji” apples using visible and near-infrared (Vis/NIR) diffuse transmittance. The diffuse transmittance spectra between 650 and 910 nm were collected with the designed spectrum measurement system in two fruit orientations: stem-calyx axis horizontal (T1) and stem-calyx axis vertical (T2). Area change rate (ACR) was used to evaluate the stability of spectra collected in two fruit orientations. Results showed that the fruit orientation T1 was better for our designed spectrum measurement system. Then, the performance of partial least squares (PLS) models based on spectral data after the pretreatment of several preprocessing methods was analyzed and compared. Finally, the modified competitive adaptive reweighted sampling (MCARS), successive projection algorithm (SPA), and their combination were investigated to select the effective variables for the determination of SSC. It concluded that the MCARS-SPA-PLS model based on the spectra after preprocessing of Savitzky-Golay (SG) smoothing achieved better results for SSC prediction. The correlation coefficients between measured and predicted SSC were 0.962 and 0.946, and the root mean square errors were 0.510 and 0.527°Brix for calibration and prediction set, respectively. Moreover, the physicochemical properties of 27 variables selected by MCARS-SPA were discussed to obtain a better interpretation of the calibration model. The overall results indicated that the designed diffuse transmittance spectrum measurement system together with the PLS calibration model with 27 effective variables selected by MCARS-SPA method had a potential application for online SSC detection of apple.

Determination of soluble solids and firmness of apples by Vis/NIR transmittance

Firmness and soluble solids content (SSC) of Red Fuji apples were examined by Vis/NIR transmittance to find out factors to be considered in online detection. Four arrangements of light source and fruit-orientation were investigated. The wavelength range of 650–920 nm was selected and two types of data pre-processing were used to enhance the precision of calibration models based on partial least square (PLS). The results show the precision of determination can be improved by using second derivate. The best fruit-orientation was the stem–calyx axis was vertical and the fruit surface was illuminated from the upper side. The precision of determination was enhanced by using multi lamps. According to the high grade of apple to export (SSC ⩾ 14 °Brix, firmness ⩾ 8.0 kg/cm 2), the classifying correctness was 86%. Validation models for SSC and firmness had a r 2 of 0.9532 and 0.8136, as well as, SEP of 0.3838 and 0.5344, respectively.

Comparison of diffuse reflectance and transmission mode of visible-near infrared spectroscopy for detecting brown heart of pear

The objective of this research was to compare transmission and reflectance modes of visible (VIS)/near infrared (NIR) spectroscopy for detecting brown heart in pears. Transmission spectra were collected by a fiber spectrometer in the range of 400–1028 nm with two fruit-orientations: stem-calyx axis vertical (T1) and stem-calyx axis horizontal (T2). Diffuse reflectance spectra were acquired using a FT–NIR spectrometer with two detectors (Si: 670–1110 nm; InGaAs: 800–2630 nm). Discriminant analysis (DA) method was employed to classify the pears with brown heart and without brown heart. Better results were obtained based on transmission spectra than those on reflectance spectra. The classifying correctness was 91.2% by using transmission spectra acquired in fruit-orientation T2. Three defective pears and one sound pear were misclassified during calibration process and for validation, no defective pear was predicted incorrectly and only one sound pear was predicted as defect. The results indicate that VIS–NIR spectroscopy is feasible for detecting brown heart in pear and transmission mode is better than reflectance mode for internal disorder detection.

APPLE SHAPE AND ROLLING ORIENTATION

The ability to orient fruit is needed to fully utilize the capabilities of many commercial sorters for defect and shape detection and general quality sensing. Five apple cultivars, representing a range of shape and size, were observed for their ability to orient (stem-calyx axis horizontal and perpendicular to the direction of travel) or remain oriented, depending on their starting position, as they were rolled by a mechanically driven flat paddle up a flat, padded incline between two fixed parallel rails. Apples did not orient particularly well on the apparatus, on average rolled 66.0 cm before orienting and rolled only 70.5 cm before becoming unoriented. Various size and shape parameters were measured and correlated with the distance apples rolled to orient and the distance that the apples remained oriented. Generally, elongation parameters were better than taper or symmetry parameters as predictors of an apple's ability to orient or remain oriented. Elongated cultivars of apples, Red Delicious and Fuji (Washington), Braeburn (New Zealand), and Granny Smith (South Africa), oriented or remained oriented better than Rome and Red Delicious (West Virginia).

Post-harvest physico-mechanical properties of orange peel and fruit

The post-harvest physico-mechanical properties data of fruits and vegetables are important in adoption and design of various handling, packaging, storage and transportation systems. Physico-mechanical properties namely, orange peel tensile strength and cutting energy and fruit color, weight loss, bioyield point, firmness, puncture force and cutting energy were determined with respect to storage period under ambient and refrigerated conditions. Peel tensile strength, modulus of elasticity and cutting energy decreased with storage period in both ambient and refrigerated conditions. The color index of orange followed a fourth-order polynomial equation during storage. At the end of 17 days storage, the fruit cumulative weight losses in ambient and refrigerated conditions were 19.4% and 7.3%, respectively. Bioyield point, firmness, puncture force and cutting energy of orange fruits decreased with respect to number of days of storage. The firmness of orange fruit was significantly higher in stem-calyx axis in vertical position than that in horizontal position.

Detection of Brownheart in ‘Braeburn’ apple by transmission NIR spectroscopy

Abstract ‘Braeburn’ apples containing the internal browning disorder, Brownheart, were examined by transmission NIR spectroscopy to determine whether sample orientation and degree of browning were significant factors requiring consideration in the design of online detection systems. Two hundred and forty fruit were preselected using a clinical MRI system to have a uniform range of the disorder from 0 to 100%. This was later checked by dissecting fruit and calculating the degree of browning in transverse equatorial slices. Four arrangements of light source, fruit-orientation and detector were investigated. Pronounced spectral changes were observed in the range 700–900 nm as the percentage of browned tissue increased. Regression-based Ratio, MLR and PLS calibration models applied to independent prediction sets gave correlations (R2p) of between 0.69 and 0.91 for the different geometries across the full range of affected fruit. Corresponding root mean square error of prediction (RMSEP) statistics of area affected were between 7.9 and 15.4%, and were elevated, in part, because of the asymmetric distribution of browning in individual fruits. PLS models tended to produce lower error and better goodness-of-fit statistics than the simpler two- or three-wavelength Ratio or MLR models. The best individual model was obtained by averaging spectra from opposite sides of the fruit where the stem–calyx axis was horizontal and the light source and detector were located at right-angles to one another at the equator. Our results suggest that single NIR transmission measurements using the models above could lead to a worthwhile reduction in the incidence of Brownheart in commercial lines containing affected fruit. However, to produce an optimal grading system, techniques to reduce the prediction error that overcome the asymmetric distribution of affected flesh, such as averaging multiple views, are still required.

Effect of postharvest water loss on ‘Hayward’ kiwifruit water status

To investigate the effect of postharvest water loss on ‘Hayward’ kiwifruit (Actinidia deliciosa C.F. Liang and A.R. Ferguson var. deliciosa) water status, fruit were observed over 14 days after harvest while being subjected to dehydrating conditions in chambers ventilated at 1 l min−1 with dry air (∼10% relative humidity, 20°C). Techniques for monitoring the change in internal aqueous characteristics involved serial magnetic resonance (MR) imaging and traditional measures of fruit water status: water content, relative water content (RWC), tissue water potential, and juice osmotic potential. Fruit fresh weight decreased by 8–10% of the initial weight over the trial period. This was accompanied by decreased water content, RWC and water potential. The rate of decrease in fresh weight, water content and RWC slowed with time. Measurements from serial MR images revealed fruit volume also decreased. This was attributable to shrinkage along the stem–calyx axis (6–9% reduction) rather than across the fruit diameter (1–3% reduction). Relaxation measurements (spin–lattice (T1) and spin–spin (T2)) indicated that there were significant differences between the localised aqueous environments of the core, inner pericarp and outer pericarp, and that the water content (proton density) differed across the fruit. However, despite the marked changes in the fruit's tissue water content, RWC, water potential and juice osmotic potential during dehydration, no significant change was observed in any of the MR measurements during the course of this study. Comparison of the relaxation measurements with those from other imaging studies suggested this observation was not unusual.

Quantitative evaluation of apple (Malus × domestica Borkh.) fruit shape by principal component analysis of Fourier descriptors

Apples from 1253 genotypes representing 82 open pollinated families planted at three sites were cut along the stem-calyx axis at the widest point to analyse fruit shape. An image analysis program was used to extract calliper measurements of the fruit outline and calculated Fourier descriptors for each fruit outline. Five independent shape traits were identified from a principal component analysis of the Fourier descriptors. The shape traits and the proportion of the total phenotypic variation they accounted for were: fruit aspect (76.8%), asymmetric-crown (7.8%), fruit conicity (6.0%), asymmetric-sides (4.3%), and fruit squareness (2.0%). Genetic and residual variance components were estimated with data from two sites using restricted maximum-likelihood techniques to select genetically-inherited apple shape traits. Combined sites heritability was estimated to be 0.79 for aspect, 0.38 for conicity and 0.35 for squareness. Multiple regression between calliper measurements and aspect, conicity, and squareness traits showed firstly that aspect was best predicted by fruit length/width ratio (R2 = 0.97), secondly conicity could be described by both the distance of the maximum width from the base of the fruit/fruit length ratio and the calyx basin width/fruit width ratio (R2 =0.44), and finally squareness was best described by ratio of the product of calyx basin width and distance of the maximum width from the calyx end of the fruit by the product of fruit length and fruit width(R2 = 0.19). A chart based on the aspect, conicity and squareness principal component values was drawn to allow visual assessment of shape.

FACTORS INFLUENCING DYNAMIC MECHANICAL PROPERTIES OF RED ‘DELICIOUS’APPLE TISSUE

This research measured tissue failure stress, failure strain, and shock wave speed in dynamic axial compression tests to assess, with respect to these properties: (1) the homogeneity of Red ‘Delicious’ apple tissue samples (10 mm dia., 15.2 mm long) taken around the apple equator; (2) the isotropy between tissue samples taken radially and parallel to the stem-calyx axis; and (3) the effects of strain rate and fruit size on dynamic (impact) properties. Results were compared with Magness-Taylor penetrometer measurements. At strain rates from 20 to 150 s –1 (equivalent to drop heights of 5 to 265 mm, respectively), the measured tissue properties were homogeneous around the periphery of the apple, but not isotropic for radial versus parallel sample orientation. Radial samples had lower failure strain but slightly higher failure stress than parallel samples. Smaller apple tissue had lower failure strain, higher failure stress, higher elastic modulus, and higher shock wave speed than that of larger apples. Failure stress and strain both increased as strain rate increased from 20 to 150 s –1 . However, the failure strain was largest at the quasi-static strain rate (0.027 s –1 ), likely due to a bio-yield occurring at the quasi-static strain rate, but not at dynamic strain rates. As expected, very poor linear correlations occurred between the Magness-Taylor penetrometer force and dynamic failure properties. Generally, correlations were better at the lower than at the higher strain rates, which is logical considering the viscoelastic nature of apples and the quasi-static loading rates used in Magness-Taylor measurements. Important conclusions are that measurement of dynamic failure properties must take into consideration fruit size and strain rate, and that Magness -Taylor tests cannot predict such properties, at least in the apples we measured.