Three types of solutions (distilled water, aqueous ascorbic acid solution and aqueous citric acid solution) were sprayed periodically on the surface of fresh-cut Japanese pear during hot air drying at 40, 50 and 60 °C. The effects of solution spraying on the drying kinetics, the surface hardening, and the sample discoloration were investigated. The drying rates of the sprayed samples increased 58–63, 16–19 and 20–22% in comparison with those of the non-sprayed samples at 40, 50 and 60 °C, respectively. The hardness of the sprayed samples decreased 12–24% and 2–9% compared to that of the non-sprayed samples, and the total color difference (ΔE) was 27–44 and 20–33% less compared the non-sprayed samples at 40 and 50 °C, respectively.

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A robot tractor controlled by a human-driven tractor system was developed to solve the problem of agriculture labor shortage. In this type of system, a robot does farm work while a human-driven tractor is following and doing a different operation. An RTK-GPS and IMU were mounted on the robot for navigation. A remote control system was developed to assist the human's operation. The results of an experiment using this system showed that by following a robot, the range of lateral errors of the human- driven tractor improved from 0.2 m to 0.15 m. The experiment field is 5.3 ha, and it took 8.7 h to finish tillage and planting, 6.3 h less than that using a single tractor.

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In describing soil variability, information on the distribution of soil properties is required in both the horizontal and vertical directions. This study investigated the potential of a real-time soil sensor (RTSS) for mapping six soil properties at multiple soil depths of a paddy field. Soil spectra were acquired at three depths using RTSS. Three calibration models were developed. The first model (CM1) combined the dataset for depths of 10 and 15 cm, the second model (CM2) combined the dataset for depths of 15 and 20 cm, and the third model (CM3) combined all the three depths. CM3 was the best calibration model for all the soil properties. The generated maps exhibited variations in the distribution of all the soil properties at different depths.

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Method of manual removal of produce from the field has been a bottle-neck for lettuce production in Japan. In order to reduce the production cost of this fresh commodity, a prototype harvester has been developed for head lettuce production. The harvester consists of a cutting component to slice the lettuce head at the desired location and a lifting component that transports the harvested produce from the cutting site onto elevating conveyor and trimming station. A cutting component with reciprocating blade was proposed. Laboratory tests were performed to verify ability of reciprocating blade to slice lettuce stump at forward cutting speed of 0.1 m/s, reciprocating stroke of 18 mm, and different reciprocating frequencies of 2, 4 and 6 Hz. In addition, power requirement for reciprocating the cutting knife as slicing two lettuce stumps was measure. Tests in lettuce fields were also conducted at different working speed to investigation the cutting and lifting performances of the harvester mounted with the reciprocating-blade cutting component. The results of laboratory tests indicated that the cutting component could smoothly cut lettuce stumps and the maximum cutting torque and cutting power requirement were 0.73 Nm and 27.7 W, respectively at 6 Hz reciprocating frequency. Field test results showed that the harvester could cut and lift the lettuce heads without damaging and blemishing the produce at working speed of 0.04 m/s and the commercial head percentage was 94.5%. At higher working speed of 0.08 m/s, the head damage rate was 12.8% reducing the percent of commercially accepted heads to 87.2%.

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From production to market, most agricultural products are transported by truck. During distribution, fruits and vegetables are subjected to different vibration levels from transport vehicles that vary in frequency and acceleration. Vibration may have a significant effect on the rate of product damages. Vibration levels that occur during transportation depend on many factors, such as: suspension type, traveling speed, road conditions, and features of the packaging. The objective of this study was to determine and analyze the vibration that occurs during truck transport as a function of truck suspension system, vehicle speed and road surface conditions. In this research vibration levels were measured using two types of trucks that are used to transport agricultural produce (one with leaf-spring suspension and the other with air-ride suspension), in three different road surfaces (asphalted highway, secondary asphalt road, and dirt road). Data were analyzed using power spectral density (PSD). The results illustrated that vertical vibration intensity was higher compared with the lateral and longitudinal directions. Statistical analyses using ANOVA test represented the intended factors such as suspension system, traveling speed and road significantly affected PSD values (average PSD in the range of 0.1–5 Hz and peak PSD). In Iran, trucks with leaf-spring suspension generated higher vibration levels compared with the air-ride suspension one and the measurements of vertical vibration levels were severe in both two truck types compared with ASTM standard.

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Flesh color of watermelon is often used as a major postharvest criterion by consumers to assess fruit quality. In this paper a non-destructive method was studied to determine watermelon (Crimson Sweet) internal color. Responses of samples to excitation vibrations were detected using laser Doppler vibrometry (LDV) technology. Phase shift between input and output vibrations were extracted overall frequency range. The frequencies of phase shifts which had the highest correlation with Hunter color values were selected. Regression models were developed to predict texture color using obtained results. The correlation coefficients of the calibration and cross validation models were 0.9 and 0.86 for a* respectively. Those of L* were 0.91 and 0.87. Meanwhile, cut watermelons were sensory evaluated by subjective scoring of color. Comparisons showed that correlations between objective measurements and consumer opinions were significant at the 0.01 level. This study demonstrated feasibility of laser vibrometery for predicting flesh color of watermelon.

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The aim of this study was to evaluate the physical and mechanical properties of particleboards manufactured from mixture of sycamore leaves and wood particles. Five panel types were made from mixtures of wood particles/sycamore leave (100/0, 90/10, 80/20, 70/30 and 60/40%, respectively). Some mechanical (modulus of rupture, modulus of elasticity and internal bonding strength) and physical properties (thickness swelling and water absorption) of the particleboards were determined. The results show that with incorporation of sycamore leaves up to 20%, the mechanical and physical properties of resulting particleboards improves. Nevertheless, the mechanical properties of all the panels exceed the minimum requirements of EN Standards for furniture manufacturing. Using renewable bio materials like sycamore leaves for manufacturing particleboards could contribute solution of raw material shortage for particleboard industry, decreasing the pressure on forest resources and diminishing environmental problems regarding their burning.

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This paper deals with the development and the implementation of an electronic nose based on Metal Oxide Semiconductor (MOS) as an innovative instrument to beer aroma recognition. Principal component analysis (PCA) results revealed a good discrimination, as two clearly separated groups (alcoholic and non-alcoholic brands). Linear discriminant analysis (LDA) was performed on the important variables which were detected based on PCA loadings. The results showed that 100% accuracy for both training and test sets was obtained using those variables. Soft independent modeling of class analogy (SIMCA) and partial least square discriminant analysis (PLS-DA) methods confirmed the PCA and LDA results of classification accuracy and their results were (100%, 100%) and (100%, 100%), for training and test sets, respectively. Finally, support vector machine (SVM) was considered and full accuracy (100%) for beer classification was again achieved for both training and test sets. The results showed that if simple methods perform well they may be preferred.

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Agricultural waste biomass has recently gained attention in the field of wastewater remediation because of their abundance and renewable nature. In the present study, agricultural waste cellulosic biomass has been modified through succinylation reaction and subsequently used as an adsorbent for the removal of Cu²⁺, Zn²⁺, Cd²⁺ and Pb²⁺ toxic metal ions from aqueous solution. The removal of metal ions from aqueous solution was investigated as a function of pH, contact time, temperature and metal ion con- centration. Pseudo-second-order kinetic model was used to study adsorption kinetics for all metal ions. Langmuir isotherm model was applied to describe the adsorption isotherm and maximum adsorption capacity qm calculated for Cu²⁺, Zn²⁺, Cd²⁺, Pb²⁺ metal ions were 72.72, 57.11, 121.51 and 273.97 mg/g respectively. The thermodynamic parameters ΔH° and ΔG° values for metals ion adsorption on the succinylated okra biomass adsorbent showed the process to be spontaneous and exothermic in nature.

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The feasibility of using visible transmission spectroscopy for the prediction of chick hatching time was investigated. An experiment was conducted with 100 chicken eggs in which transmission spectra were measured between incubation day 0 (non-incubated) and days 8 and subsequent hatching time was recorded. Spectral transmittance in the range of 500e750 nm was used in analysis. Spectral data were linked to hatching time using a partial least squares (PLS) regression method. Different pre-processing procedures were compared. The calibration model using incubation day 4 spectra with multiplicative scatter correction (MSC) resulted in the lowest root mean square error of prediction (RMSEP) 1⁄4 3.41 h. The result indicates that the use of visible transmission spectroscopy combined with multivariate analysis has potential to predict the chick hatching time.

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