The drying of fruits and vegetables is a complex operation that demands much energy and time. In practice, the drying of fruits and vegetables increases product shelf-life and reduces the bulk and weight of the product, thus simplifying transport. Occasionally, drying may lead to a great decrease in the volume of the product, leading to a decrease in storage space requirements. Studies have shown that dependence purely on experimental drying practices, without mathematical considerations of the drying kinetics, can significantly affect the efficiency of dryers, increase the cost of production, and reduce the quality of the dried product. Thus, the use of mathematical models in estimating the drying kinetics, the behavior, and the energy needed in the drying of agricultural and food products becomes indispensable. This paper presents a comprehensive review of modeling thin-layer drying of fruits and vegetables with particular focus on thin-layer theories, models, and applications since the year 2005. The thin-layer drying behavior of fruits and vegetables is also highlighted. The most frequently used of the newly developed mathematical models for thinlayer drying of fruits and vegetables in the last 10 years are shown. Subsequently, the equations and various conditions used in the estimation of the effective moisture diffusivity, shrinkage effects, and minimum energy requirement are displayed. The authors hope that this review will be of use for future research in terms of modeling, analysis, design, and the optimization of the drying process of fruits and vegetables.
Basal stem rot (BSR) is a prominent plant disease caused by Ganoderma boninense fungus, which infects oil palm plantations leading to large economic losses in palm oil production. There is need for novel disease detection techniques that can be used to reduce the oil palm losses due to BSR. Thus, this paper investigated the feasibility of utilizing electrical properties such as impedance, capacitance, dielectric constant, and dissipation factor in early detection of BSR disease in oil palm tree. Leaf samples from different oil palm trees (healthy, mild, moderate, and severely-infected) were collected and measured using a solid test fixture (16451B, Keysight Technologies, Japan) connected to an impedance analyzer (4294A, Agilent Technologies, Japan) at a frequency range of 100 kHz-30 MHz with 300 spectral interval. Genetic algorithm (GA), random forest (RF), and support vector machine-feature selection (SVM-FS) were used to analyze the electrical properties of the dataset and the most significant frequencies were selected. Following the selection of significant frequencies, the features were evaluated using two classifiers, support vector machine (SVM) and artificial neural networks (ANN) to determine the overall and individual class classification accuracies. The selection model comparative feature analysis demonstrated that the best statistical indicators with overall accuracy (88.64%), kappa (0.8480) and low mean absolute error (0.1652) were obtained using significant frequencies produced by SVM-FS model. The results indicated that the SVM classifier shows better performance as compared to ANN classifier. The results also showed that the classes, features selection models, and the electrical properties were found to be significantly different (p < .1). The impedance values were highly classified by Ganoderma disease at different levels of severity with overall accuracies of more than 80%. Impedance can be considered as the best electrical properties that can be used to estimate the severity of BSR disease in oil palm using spectroscopy technique. As such, this study demonstrates the potentials of utilizing electrical properties for detection of Ganoderma diseases in oil palm.
This study seeks to investigate the effects of temperature (50, 60, 70 and 80 °C) and material thickness (3, 5 and 7 mm), on the drying characteristics of pumpkin (Cucurbita moschata). Experimental data were used to estimate the effective moisture diffusivities and activation energy of pumpkin by using solutions of Fick’s second law of diffusion or its simplified form. The calculated value of moisture diffusivity with and without shrinkage effect varied from a minimum of 1.942 × 10–8 m2/s to a maximum of 9.196 × 10–8 m2/s, while that of activation energy varied from 5.02158 to 32.14542 kJ/mol with temperature ranging from 50 to 80 °C and slice thickness of 3 to 7 mm at constant air velocity of 1.16 m/s, respectively. The results indicated that with increasing temperature, and reduction of slice thickness, the drying time was reduced by more than 30 %. The effective moisture diffusivity increased with an increase in drying temperature with or without shrinkage effect. An increase in the activation energy was observed due to an increase in the slice thickness of the pumpkin samples.
In paddy cultivation, harvesting is the most important operation, which needs suitable machinery. Thus, this study was carried out to compare field performances and energy and environmental effect between the conventional 5 m cutting width NEW HOLLAND CLAYSON 8080, 82 kW@2500 rpm combine harvester running on a total net area of 42.78 ha of plots for two rice (Oryza sativa L.) cultivation seasons and the new mid-size 2.7 m cutting width WORLD STAR WS7.0, 76 kW@2600 rpm combine harvester running on a total net area of 16.95 ha of plots for two rice cultivation seasons. The conventional combine as compared to mid-size combine showed 14.4% greater mean fuel consumptions (21.13 versus 18.46 l/ha), 31.1% greater mean effective field capacity (0.69 versus 0.53 ha/h), 5.23% greater cornering time (turning time) percentage of total time (8.28% versus 3.05%) and 1.41% greater reversing time percentage of total time (7.2% versus 5.79%) but 20.90% lesser mean operational speed (3.24 versus 4.10 km/h), 11.69% lesser effective time percentage of total time (60.0%versus 71.69%h/ha), 10.8% lesser mean field efficiency (64.3% versus 72.1%). In terms of total energy use the conventional combine showed 24.64% greater mean total energy use in the harvesting operation (1445.81 versus 1160.00 MJ/ha), 14.46% greater mean fuel energy (1010.014 versus 882.39 MJ/ha), 56.47% greater mean machinery energy (431.32 versus 275.65 MJ/ha) and 59.25% greater mean human energy (3.48 and 2.18 MJ/ha), this cause 26.12% greater mean total Green House Gas emission (GHG) than the mid-size combine. The results revealed that the mid-size combine is more suitable in conducting the harvest operation in rice field in Malaysia than the conventional combine.
The objective of this study is to determine the shopping drivers that influence consumers to choose the night market or wet market for fresh fruit and vegetable (FFV) purchases. The study also investigates whether any differences in behavior among generational cohorts exist while purchasing fresh fruits and vegetables between two retail formats. The cluster sampling technique was applied to the entire population of Klang Valley area in Malaysia, and 700 respondents were randomly selected for this research. Perceived freshness, perceived quality and perceived safety of the fresh fruits and vegetables are the most important shopping drivers in a consumer's decision to purchase FFV in night market and wet market retail formats. The findings show that members of different generational cohorts have different perceptions about freshness, quality and safety of fresh fruits and vegetables purchased in night market and wet market retail formats.
The study described the perceived importance of, and proficiency in core agricultural extension competencies among extension workers in Peninsular Malaysia; and evaluating the resultant deficits in the competencies. The Borich's Needs Assessment Model was used to achieve the objectives of the study. A sample of 298 respondents was randomly selected and interviewed using a pre-tested structured questionnaire. Thirty-three core competency items were assessed. Instrument validity and reliability were ensured. The cross-sectional data obtained was analysed using SPSS for descriptive statistics including mean weighted discrepancy score (MWDS). Results of the study showed that on a scale of 5, the most important core extension competency items according to respondents' perception were: "Making good use of information and communication technologies/access and use of web-based resources" (M=4.86, SD=0.23); "Conducting needs assessments" (M=4.84, SD=0.16); "organizing extension campaigns" (M=4.82, SD=0.47) and "Managing groups and teamwork" (M=4.81, SD=0.76). In terms of proficiency, the highest competency identified by the respondents was "Conducting farm and home visits (M=3.62, SD=0.82) followed by 'conducting meetings effectively' (M=3.19, SD=0.72); "Conducting focus group discussions" (M=3.16, SD=0.32) and "conducting community forums" (M=3.13, SD=0.64). The discrepancies implying competency deficits were widest in "Acquiring and allocating resources" (MWDS=12.67); use of information and communication technologies (ICTs) and web-based resources in agricultural extension (MWDS=12.59); and report writing and sharing the results and impacts (MWDS=11.92). It is recommended that any intervention aimed at developing the capacity of extension workers in Peninsular Malaysia should prioritize these core competency items in accordance with the deficits established in this study.
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