Agricultural Engineering International (E-Journal, CIGR - International Commission of Agricultural Engineering)
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A Kinetic analysis of changes in sweetness and acidity of sliced pineapples during ultrasonication: Sweetness and acidity changes in pineapple
No full textChanges in sweetness and acidity of sliced pineapples during ultrasonication was carried out by determining the rate of changes in total sugar content and pH. Half and fully ripe sliced pineapples were prepared and exposed to ultrasonic waves at the frequency of 40kHz for 0, 5, 10, 15, 20, 25, 30, 35, and 40 minutes. Total sugar content, pH, and order of reaction during ultrasonication were analyzed. Sonication of half-ripe pineapples for 40 minutes resulted in the lowest total sugar content (9.53% Brix), whereas the same treatment on fully ripe pineapples resulted in the highest pH (4.73). The reduction of total sugar content in half and fully ripe pineapples followed a first-order reaction with rate of constants (k) of -0.450 and -0.612 per hour, respectively. The kinetic changes in pH during ultrasonication showed that half and fully ripe of pineapples followed a first-order reaction with rate of constants (k) of 0.222 and 0.216 per hour, respectively
Effects of drying techniques on the sorption properties of dried Cassava chips from ‘‘Oko-Iyawo’’ Cassava local variety
No full textThe distinguishing attributes of preserved cassava chips depend on their moisture content, the periodic passage of moisture, and interactions with moisture during storage. The water activity level, which corresponds to the equilibrium moisture content range, was determined by the use of moisture isotherms. A local variety of Cassava tubers, “oko iyawo,” was obtained from the Ladoke Akintola University of Technology Teaching and Research Farm. The moisture sorption isotherms of the Cassava chips were determined at 27°C in the room temperature and 10-80% relative humidity range using the standard static gravimetric method, while the Cassava chips were subjected to sorption and measured periodically between 10-80% relative humidity until the equilibrium moisture content was reached. The modified Henderson sorption model was tested to fit the experimental data. A nonlinear regression analysis was used to evaluate the constants of the sorption GAB and MGAB models. The GAB and MGAB models were good fits for predicting the moisture sorption isotherms of sun-dried Cassava chips, while the MGAB model was a good fit for predicting the moisture sorption isotherms of solar and cabinet-dried Cassava chips. The GAB and MGAB models exhibited the best fit for predicting the moisture adsorption isotherms of sun-dried cassava chips at 27°C. Further studies should be conducted on the storage of the “oko iyawo” variety of cassava chips using appropriate packaging materials, and investigations of the isothermal attributes and other temperature characteristics of the Cassava chip product should be performed because it aligns with several sustainable development goals (SDGs)
Comparative evaluation of FAO56-PM ET0 estimates using meteorological parameters retrieved from MERRA-2 satellite and ground dataset for humid Dehradun region of India
No full textIn this study conducted with specific objective to compare ET0 estimates obtained at monthly and cropping (kharif, rabi and zaid) season timescales with climatic parameters retrieved from MERRA-2 satellite and ground meteorological dataset with standardized FAO56-PM model for humid Dehradun district of Uttarakhand, it was found that during 29 years study period, about 84.45% months resulted in very good correlation between FAO56-PM ET0 estimates obtained with MERRA-2 satellite parameters and ground meteorological dataset, while about 37.93% and 27.59% kharif seasons were observed under Very Strong Positive and Strong Positive levels, respectively. Similarly, about 93.10% and 6.90% rabi seasons were obtained with Very Strong Positive and Strong Positive correlation coefficient values. For zaid season, about 93.10% seasons showed Very Strong Positive correlation coefficient values. About 99.71% months during study period extended good agreement in terms of Agreement index. On cropping season basis, 55.17% kharif, 62.07%, rabi, and 7.31% zaid seasons respectively showed agreement index values with medium agreement
Modeling of emissions characteristics of a diesel engine fueled by Jatropha Diestrol
Full text linkThe global reliance on fossil fuels for energy production has become increasingly apparent. However, the numerous drawbacks and diminishing reserves of fossil fuels have compelled the world to explore and utilize alternative and renewable fuel sources. Biofuels have emerged as a prominent contender among renewable energy options. Derived from animal and plant sources, biofuels obtained from non-edible plant resources have gained precedence to avoid compromising human food supplies. Biodiesel offers several advantages, including clean combustion and energy generation comparable to fossil fuels. One such non-edible plant-based biofuel is Jatropha biodiesel. While a blend of biodiesel and diesel can be directly used in diesel engines, the addition of ethanol can enhance the properties of the fuel blend, resulting in an improved alternative fuel. This advanced fuel blend, known as Jatropha Diesterol, has been developed and patented for the first time in Iran. The Jatropha Diesterol fuel blends (consisting of Jatropha biodiesel-diesel-ethanol) comprised 3% ethanol and 10%, 20%, and 30% biodiesel. These fuel blends underwent testing in a single-cylinder air-cooled diesel engine, operating at full load and four engine speeds (1600, 2000, 2400, and 2800 rpm). The emitted pollutants, namely CO, CO2, HC, O2, and HC, were analyzed and recorded. Subsequently, the data was modeled using the support vector machine (SVM) method, incorporating genetic algorithm (GA) optimization. Eighty percent of the data was assigned for training purposes, while the remaining 20% was allocated for testing. The modeling results were evaluated using parameters such as R2, MSE, MAE, and RSME. The outcomes demonstrated that the SVM+GA method accurately predicted the data from this experiment, achieving high accuracy and, in some cases, 100% accuracy. Therefore, this modeling approach can be utilized for future research in this field, obviating the need for costly and time-consuming experiments and evaluations of advanced alternative fuel blen
Research paper Predicting the Effects of Agricultural Soil Tillage Operations on Fuel Use
No full textWastage and economic loss in agricultural productivity during tillage operations could be predicted and reduced at the design stages. This study used a factorial experimental design to optimize tractor hourly fuel consumption during ploughing and ridging operations. The research aimed to investigate tillage effect on fuel utilization efficiency for reduction of operational cost and increase agricultural productivity. A 4,480 m2 research plot split into three blocks of nine treatments with three replicates was adopted for the research. The plot varied from loamy sand to sandy loam, which are good for agricultural productivity. Field test parameters (ploughing depth (or ridging height), and tractor onward speed) and fuel use were measured. Using MINITAB 19 software, statistical analyses of the general full factorial design (GFFD) were carried out. These analyses included model fit adequacy, analysis of variance (ANOVA), main and interaction effects, multiple linear regression model, and response optimizer. Normal probability plots showed that the hourly fuel use during ploughing and ridging were approximately normally distributed, satisfying model fitness examination, and was confirmed by the model competence plot of frequency versus residual. The hourly fuel use during ploughing and ridging was shown to be randomly distributed with no discernible structure in the residual versus fitted value plots, supporting the residuals' constant variance requirement. Statistical analysis, and ANOVA in GFFD indicated that a significant difference exists with 95 and 99 % levels of significance on the influence of ploughing depth (or ridge height), tractor onward speed and their effects on tractor hourly fuel consumption during ploughing and ridging operations. Optimized tractor hourly fuel consumption during ploughing and ridging was attained at plough depth and ridge height of 0.10 m respectively, and tractor onward speed of 5Km/h. This study determined that the minimum fuel consumption per hour for tractor under optimised working circumstances were 2.93 L/h and 3.30 L/h for ploughing and ridging operations respectively
VARIABLE CONVOLUTION KERNEL WITH FEATURE FUSION AND TRANSFER LEARNING FOR LEAF DISEASE CLASSIFICATION
Full text linkThe advancement of automated frameworks for detecting and classifying leaf diseases is extensively explored in contemporary agricultural practices. The effectiveness of a classifier relies on the feature extraction process. A novel Variable Convolution Kernel (VCK) feature extraction algorithm with Feature Fusion (FF) and Transfer Learning (TL) based disease classification is proposed. Sparse representation is obtained in the training stage by fusing features obtained through different filters. TL offers the benefit of leveraging pre-trained models on large datasets, saving significant time and computational resources when building and training new models for specific tasks. Mobilenet_v2 pretrained using ImageNet dataset can improve model performance, especially when dealing with limited training data, by transferring weights and features. A novel framework has been developed by incorporating CNN, TL, FF and tuning the hyperparameters. The underlying algorithm is known as FF-TL-CNN algorithm. The empirical investigation utilized the Plant Village dataset. The leaf disease categories examined in this study encompass early blight, black rot, bacterial spot, apple scab, cercospora leaf spot, and the category of healthy leaves. FF-TL-CNN outperformed other classifiers by attaining 98.85% accuracy, 98.63% precision, 98.41% recall and 99.32% F1-score with Plant Village dataset. The research findings demonstrate that the suggested deep learning model and algorithm have practical applications in real-world computer vision contexts, particularly in the field of agriculture
A Laser Technique for Quality Evaluation of Sheep, Goat and Camel Milk
No full textMilk is an important source of all basic nutrients, which are needed for proper growth and body. The study was conducted to evaluate physiochemical quality of sheep, goat and camel milk samples in selected dairy plant of Egypt using Laser technique. Various physicochemical properties included fats; Protein, acidity, specific gravity; freezing point and colour were analyzed and compared. The qualification was done by laser technique with optical properties (reflection, absorption) with wavelength 632.8 nm. The conclusive can be summarized in the following points: (a) Total solids and pH in milk have been measured in terms of % of lactic acid, and order in different samples of milk is obtained as : Sheep milk < Goat milk < Camel milk, (b) Fat, protein, ash, and total carbohydrate content determined in various samples of milk have been reported, and order in different samples of milk is obtained as: Sheep milk > Goat milk > Camel milk, (c) There is direct proportion between Laser reflection percentage and pH value. While, there is inverse proportion between the Laser reflection percentage and the total solids percentages, (d) There is inverse proportion between Laser absorption percentage and pH value. While, there is direct proportion between the Laser absorption percentage and the total solids percentages, (e) There is inverse proportion between Laser reflection percentage and fat, protein, ash and carbohydrate percentage. While, there is direct proportion between Laser absorption percentage and fat, protein, ash and carbohydrate percentages, and (f) Laser techniques applied are available, fast, and easy used to detect milk quality
Effect of Tractor Noise on Operator and Bystander’s Health and its Attenuation using Noise Protection Devices
Full text linkThe study focused on assessing the impact of agricultural tractor noise hitched with disc plough, cultivator and rotavator on operators’ health. The tractor-hitched-implement’s noise level was measured at no load (0 cm tillage depth) and with load (10 cm and 14cm tillage depth) at operator’s ear level and bystander’s position at engine speed of 1000, 1500 and 2000 rpm. The response parameters were measured in terms of physiological parameters like heart rate, blood pressure and sound pressure level (SPL). The experimentation and analysis revealed that the noise level at operator’s ear level exceeds beyond the allowable 85 dB level. In order to reduce noise, the attenuation characteristics of ear muff, ear plug and moist cotton were also tested. The results revealed 24.65% noise attenuation with ear muff, 19.04% ear plug and 13.94% moist cotton. The drop in the heart rate 37.38%, 26.26% and 24.50 % and blood pressure 7.8%, 1.07% and 1.05% with ear muff, ear plug and moist cotton, respectively. The study leverages towards the intervention to reduce the intensity of noise, protect the operators from occupational health syndromes (OHS) and improve the working efficiency
Toward mechanized saffron farms by a full-hydraulically mounted saffron corm sorter
Full text linkIn this research, a saffron corm sorter was designed and manufactured. Inside the drum screen, a rubber blade impeller with three vanes was installed. The speed and direction of rotation of this impeller is the same as the drum screen. The saffron corms are poured into the sorter through inlet by the worker, and while moving forward, the different size of corms are separated from each other. Therefore, the lumpy soil and small corms fall to the ground from the distance between the bars of the drum screen. Also, large corms are also discharged from the end of the drum screen. The excess peel of saffron corms is discharged from the end of the drum with the help of fan air flow. In order to evaluate the sorter, the effect of feeding rate at three levels (300, 400 and 500 ), drum rotation speed at three levels (5, 8 and 12 rpm) and the speed of rubber impeller in two level (50 and 75 rpm) was studied. Therefore, the amount of damaged corms and grading accuracy were evaluated. The optimum performance of corm sorter was obtained in the feeding rate of 400 and the rotational speed of 8 rpm. In this condition the maximum grading accuracy and minimum level of damage can be reached. The rubber blade impeller has a better performance at the rotational speed of 50 rpm than the rotational speed of 75 rpm
Design Conceptual Design of a Multi-Crop Inter-Row Cultivator including Development and Performance Evaluation of Prototype: Design, Development, testing, and performance Evaluation of the cultivator
No full textThe emergence of herbicide-resistant weeds, environmental impact and increasing demand for chemical-free foods made chemical method of weed control less attractive and hence gave rise to the importance of mechanical weeding method. The main objective of this study was to design, develop and test a two wheel tractor (2WT) drawn multi-crops inter-row cultivator. While designing and in material selection, premium was given to crop parameters such as row to row spacing, plant height and branching pattern; soil parameters such as soil penetration resistance, soil bulk density and soil moisture content, and machine-soil parameters. Consideration was given to strength, durability, portability, simplicity and techno-economic status of the smallholder farmers and artisans who are the intended users and mass producers respectively. The design computations and graphic of the functional units and components of the machine were achieved using the CATIA software package and Solid Work 2013. The machine was constructed and tested at Melkassa Agricultural Research Center (MARC) fabrication workshop and tested at the center’s experimental farm using a 15 hp 2WT. Results revealed that the average weeding indexes were 84.27 %, 92.12% and 88.31% for maize, soybean and sorghum respectively while the average mechanical damage were 4.27%, 3.65% and 4.25% for maize, soybean and sorghum respectively. The results of the test showed that the machine performed satisfactorily. With a production cost of ETB 11,196.80 (USD 279.92), the machine can be easily afforded by the smallholder and low income farmers who are the intended users