Characterization of a 90° Transfer Point in a Fruit Packing Line.

Characteristics of the impacts suffered by the fruit on a transfer point of an experimental fruit packing line were analysed. The transfer is made up by two transporting belts at different heights forming an angle of 90°. These transfer points are very common in fruit packing lines, in which fruits receive two impacts: the first onto the belt base and the second into the lateral plate. Different tests were earned out to study the effect of transfer height, velocity, belt structure and padding on tire acceleration values recorded by an instrumental sphere (IS 100). Results showed that transfer height and belt structure affect mainly impact values on the belt base, and padding affects mainly impact values registered in lateral impact. The effect of belt velocity in both impacts is less important when compared to the rest of the variables. Additionally, two powered transfer decelerators were tested at the same point with the aim of decreasing impacts suffered by the fruit. Comparing impacts registered using these decelerators to those analysed in the first part of the study without decelerators a high reduction of the impact values was observed.

A procedure for testing padding materials in fruit packing lines.

Padding materials are commonly used in fruit packing lines with the objective of diminishing impact damage in postharvest handling. Two sensors, instrumented sphere IS 100 and impact tester, have been compared to analyze the performance of six different padding materials used in Spanish fruit packing lines. Padding materials tested have been classified according to their capability to decrease impact intensities inflicted to fruit in packing lines. A procedure to test padding materials has been developed for "Golden" apples. Its basis is a logistic regression to predict bruise probability in fruit. The model combines two kinds of parameters: padding material parameters measured with IS, and fruit properties.

Non-Destructive Identification of Woolly Peaches combining Mechanical Impact Response and NIR Spectroscopy.

Woolliness (mealiness in other fruits) is a negative attribute of peach sensory texture that is a physiological disorder associated with inadequate cold storage. It is characterised by lack of crispness and juiciness without variation in the tissue water content (Harker and Hallet, 1992). Many attempts have been made to develop destructive instrumental procedures to detect mealiness and woolliness. Non-destructive procedures attempted include using nuclear magnetic resonance (Sonego et al., 1995). However, this technique has economical limitations and is not practical at present. Non-destructive impact tests and NIR are non-destructive techniques which have been used to assess internal characteristics of fruits (Chen and Sun, 1991). The objective of this study was to develop a novel non-destructive procedure to identify woolly peaches by combining impact and NIR approaches.

Models for internal quality sorting of fruit, based on time-domain laser reflectance spectroscopy (TDRS).

Non-destructive measurement of fruit quality has been an important objective through recent years (Abbott, 1999). Near infrared spectroscopy (NIR) is applicable to the cuantification of chemicals in foods and NIK "laser spectroscopy" can be used to estimate the firmness of fruits. However, die main limitation of current optical techniques that measure light transmission is that they do not account for the coupling between absorption and scattering inside the tissue, when quantifying the intensity o f reemitted light. The solution o f this l i m i t a t i o n was the goal o f the present work.

Bruise Simulation in Peach Grading Lines as a tool for designing Improvement Strategies.

The Physical Properties Laboratory (LPF) has been working on the improvement of fruit and vegetable grading lines since 1992'. The experience shows that the improvement of grading lines for decreasing mechanical damages has to be approached from two viewpoints: 1) machinery aggressiveness, and 2) fruit susceptibility. Machinery aggressiveness can be characterized as impact probability for different impact intensities assessed by means of electronic fruits (IS-100) 2,5 . On the other hand, bruise susceptibility can be determined using different laboratory tests. A recent study from LPF4 shows that damage may arise differently in pome and in stone fruits, since: a) pome fruits are mainly stress-susceptible, while stone fruits appear to be more deformation-susceptible, and b) bruise size may be a good predictor for bruise susceptibility in pome fruits while for stone fruits bruise probability is the most relevant characteristic of bruise susceptibility. Also, this study indicates the feasibility of predicting bruise probability using several mechanical and load characterization parameters. Despite the efforts to establish damage thresholds in peachess, no simulation models are currently available for predicting bruise occurrence in grading lines.

Instrumental quality assessment of fresh peaches: Optical and mechanical parameters.

In developing instrumentation for the measurement of fruit quality, there is the need for fast and non-destructive devices, based on sensors, to be installed on-line. In the case of some fruits, like peaches, post-harvest ripeness, which is closely related to high quality for the consumer, is a priority. During ripening, external appearance (colour) and internal mechanical (firmness) and chemical (sugars and acids) quality are main features that evolve rapidly from and unripe to a ripe (high quality) stage. When considering the evolution of fruit quality in this scheme, external colour and firmness are shown to evolve in a parallel pattern, if monitored from the time of harvest to full consumer ripeness ( Rood, 1957; Crisosto et al, 1995; Kader, 1996). The visible (VIS) reflectance spectrum is a fast and easy reference that can be used to estimate quality of peaches, if we could show it to be reliably correlated with peach ripening rate during postharvest (Genard et al. 1994; Moras, 1995; Delwiche and Baumgartner, 1983; Delwiche et al. 1987; Slaughter, 1995; Lleo et al., 1998). Taste, described as an expert acceptance score, improves with ripeness (firmness and colour evolution), when considering the fruits on the tree, and also post-harvest.

New version of a laboratory impact device for firmness sensing of fruits.

Results of previous studies conducted by different researchers have shown that impact techniques can be used to evaluate firmness (Delwiche et al., 1989; Delwiche et al.;1996; Jaren et al., 1992; Ruiz Altisent et al., 1996). To impact the fruit with a small spherical impactor of known mass and radius of curvature and measure the acceleration of the impactor is a technique described by Chen et al. (1985) and used by several researchers for sensing fruit firmness (Jaren et al., 1992; Correa et al.; 1992). The advantages of this method vs. a force sensor that measures the force as a function of time is that the measured impact-acceleration response is independent of the fruit mass and is less sensitive to the variation in the radius of curvature of the fruit (Chen et al., 1996). Ruiz Altisent et al. (1993) developed and used a 50 g impactor with a 19 mm diameter spherical tip, dropping from different height for fruits (apples, pears, avocados, melons, peaches ...). Another impact device for firmness sensing of fruits was developed by Chen and Ruiz Altisent (1996). They designed and fabricated an experimental low-mass impact sensor for high-speed sensing of fruit firmness. The impactor consisted of a semi-spherical impacting tip attached to the end (near the centre of percussion) of a pivoting arm. Impact is done by swinging the impactor to collide with the fruit. It has been implemented for on-line use. In both devices a small accelerometer is mounted behind the impacting tip. Lateral impactor and vertical impactor have been used in laboratory and the results from non-destructive impact tests have contributed to standardise methods to measure fruit firmness: Barreiro (1992) compared impact parameters and results of Magness-Taylor penetration tests for apples, pears, apricots [and peaches; Agulheiro (1994) studied the behaviour of the impact parameters during seven weeks of cold storage of two melon varieties; Ortiz (1998) used low energy impact and NIR procedures to segregate non crispy, non firm and soft peaches. Steinmetz (1996) compared various non-destructive firmness sensors, based on sound, impact and micro-deformation.