Regression Analysis for Deploying UTC and the Resulting Energy Consumption in Pig Barns

( Mustafa Jaihuni ),( Fawad Khan ),( Jayanta Kumar Basak ),( Elanchezhian Arulmozhi ),( Ji-hoon Park ),( Hyeon-tae Kim ) 한국농업기계학회 2019 한국농업기계학회 학술발표논문집 Vol.24 No.1

There is high energy loss through ventilation in livestock barns as well as in electricity consumed by lamps. Using unglazed transpired collectors is a good solution to decrease such energy loss. Nevertheless, it is required to establish UTC control system and operating methods in order to provide comfortable room temperature for the pig barn. Hence, this paper aims to rise temperature of pig barns by UTC control system, evaluate the thermal performance of UTC, and analyze the resulting electricity usage. A UTC fan was operated for 7 hours per day and the UTC control system was applied. Therefore an average rise of 27.6°C in temperature, as compared to ambient temperature, was observed. Regression models, linear and non-linear, were established using indoor and outdoor temperature data values. Henceforth, a correlation analysis was done between solar radiation and collector surface temperature. This model’s R2 for linear and non-linear models were 0.93 and 0.92, respectively. The application of UTC control system had decreased the electricity consumption by 30.8%.

Designing a Power Data Logger with RaspberryPi and its Implementation in a Wind-Solar Hybrid System

( Mustafa Jaihuni ),( Jayanta Kumar Basak ),( Anil Bhujel ),( Na Eun Kim ),( Hyeon Tae Kim ) 한국농업기계학회 2020 한국농업기계학회 학술발표논문집 Vol.25 No.2

In this study, it was aimed to design and implement a data logger with RaspberryPi (DLR) that would record the power, current and voltage readings from a hybrid solar-wind renewable energy system. The data logger, DLR, was build over RaspberryPi 4 model along with corresponding sensors which measured the mentioned three readings and communicate to a central cloud storage via wireless transmitter every 50ms. The DLR was utilized for 10 days in the solar-wind hybrid system; the maximum power reading was 354.87 Watts and the correspoding total voltage and current readings of 21.68V and 16.37 Amps. The wireless transmitter worked successfully in sending the records in the mentioned intervals.

Forced Aerated Poultry Compost Effects on Soil Physicochemical Properties and Lettuce Plant Growth

Fawad Khan,Jayanta Kumar Basak,Mustafa Jaihuni,이덕현,이준현,김현태 한국농업기계학회 2020 바이오시스템공학 Vol.45 No.2

Purpose In previous studies, the stability and maturity of forced aerated composts were examined from the physicochemical analysis inside the reactors. The objective of this study is to check the maturity and effects of forced aerated composts after its addition to soil and plants. Methods The composts were prepared from fresh chicken manure and sawdust in cylindrical reactors and aerated at 0.75, 0.50, and 0.25 L min−1 kg−1 organic matter (OM) for 1 month. Afterward, it was mixed with soil and coded as treatment T1 (0.75 L min−1 kg−1 OM aeration rate + soil), T2 (0.50 L min−1 kg−1 OM aeration rate + soil), T3 (0.25 L min−1 kg−1 OM aeration rate + soil), and CS (only soil), respectively. The soil properties (pH, electrical conductivity (EC), organic matter content (OM), loss of organic matter content, bulk density (BD), water holding(WH)) and plant growth (shoot length (cm), leaves’ area (cm2), fresh and dry weight (g)) were checked for 4 months. Results The results showed a significant increase (at P < 0.05) in soil properties in T1, T2, and T3 as compared with CS. Among treatments T1, T2, and T3, the maximumpH (7.20 ± 0.07),OMdegradation (77.06%), loss of organic matter (6.32 ± 0.42%), and WH (32.17 ± 0.32%) were observed in T3. Additionally, the lowest EC (1.15 ± 0.02 mS/cm) and BD (1.06 ± 0.02%) were observed in T3. Further a significant increased difference (at P < 0.05) in shoot length (21.40 ± 1.01 cm), leaves’ area (293.20 ± 16.33 cm2), fresh weight (88.22 ± 7.30 g), and dry weight (12.10 ± 0.91 g) of the plant were observed in T3. Conclusion The poultry manure compost’s aerated rate (0.25 L min−1 kg−1 OM) in T3 was observed to be more mature and stable as compared with T1 and T2.

Minimize the Level of NPK and Enhance the Growth and Nutritional Quality of Strawberry Plants by Trichoderma-enriched Biofertilizer

( Fawad Khan ),( Jayanta Kumar Basak ),( Mustafa Jaihuni ),( Na Eun Kim ),( Deog Hyun Lee ),( Hyeon Tae Kim ) 한국농업기계학회 2020 한국농업기계학회 학술발표논문집 Vol.25 No.1

Effective biofertilizers not only decrease the level of chemical fertilizers in agricultural production but also improve the vegetative growth, fruit quality of the plant as well as reduce the risk of pollution. In this study, the impact of Trichoderma-enriched biofertilizer (poultry manure and sawdust compost with Trichoderma harzianum YC459 (TEB)), standard chemical fertilizer (SCF), and the combination of both (TEB+SEF), was utilized to evaluate the growth, yield, and nutritional quality of strawberry plants (Fragaria × ananassa). Four treatments were applied, including T1 (control soil (CS)), T2 (SEF); T3 (TEB); and T4 (50% TEB + 50% SEF). The standard statistical method (one-way ANOVA) was used to determine the encouraging responses in all respects. Four treatments were applied, including T1 (control soil), T2 (standard NPK); T3 (Trichoderma-enriched biofertilizer); and T4 (50% of Trichoderma enriched biofertilizer + 50% of NPK). The standard statistical method (one-way ANOVA) was used to determine the encouraging responses in all respects. The significant increase in plant growth and fruit yield (at P<0.05) was observed over control by T4, followed by T2. Also, total soluble soil, ascorbic acid, total sugar content, was observed higher when fertilizer with a combination (50% TEB + 50% SEF) in T4. Trichoderma enriched biofertilizer with reduce the level of chemical fertilizer can be considered for improvement in growth, yield, and quality of strawberry plant cultivation.

Assessment of Combined Trichoderma-Enriched Biofertilizer and Nutrients Solutions on the Growth and Yield of Strawberry Plants

Khan Fawad,김나은,Bhujel Anil,Jaihuni Mustafa,이덕현,Basak Jayanta Kumar,김현태 한국농업기계학회 2021 바이오시스템공학 Vol.46 No.3

Purpose The use of biofertilizers not only decreases the level of a nutrient solution but also improves the growth of plants and reduces the risk of environmental pollution. In this study, the impact of Trichoderma-enriched biofertilizer (poultry manure composted and Trichoderma harzianum YC459 (TEB), standard nutrient solution (SNS), and the combination of both (TEB + SNS) were utilized to evaluate the growth, yield, and nutritional quality of strawberry plants (Fragaria × ananassa Duch.). Method The strawberry plants were planted in four treatments—control soil (CS, without TEB and SNS), T1 (SNS), T2 (TEB), and T3 (50% SNS + 50% TEB) — in a controlled greenhouse. Several scientific instruments such as a ubiquitous broadcast network (UBN) farm link control management system, sensor nodes, nutrient controller, composting reactor, digital refractor meter, dry oven, digital balance, and different chemical techniques were used for a particular purpose. Results Consequently, analysis of variance was performed, and a significant increase in yield values (123.07–145.83% and 88.46–100.00%) was recorded over control by T3 and T1, respectively. Also, the vegetative growth parameters, total soluble solids, ascorbic acid, and total sugar content were observed higher in T3. Conclusion It was observed that the combined use of Trichoderma-enriched biofertilizer with the standard nutrient solution could improve the growth, yield, and quality of the strawberry plant.

Sensor Systems for Greenhouse Microclimate Monitoring and Control: a Review

Bhujel Anil,Basak Jayanta Kumar,Khan Fawad,Arulmozhi Elanchezhian,Jaihuni Mustafa,Sihalath Thavisack,이덕현,박재성,김현태 한국농업기계학회 2020 바이오시스템공학 Vol.45 No.4

Purpose Sensors are the primary component of a monitoring and control system. Effective monitoring and control of the microclimatic environment in a greenhouse is the key necessity for protecting crops from adverse environments. Moreover,the greenhouse microclimate is influenced by various factors. In the large-scale greenhouse facilities, several sensors and actuators are needed to control the system. Manual monitoring and control of such a large and complex system is labor-intensive and impractical. Therefore, an automatic monitoring and control system in the greenhouse becomes indispensable. In addition, microclimatic parameters such as temperature, humidity, and solar irradiance in the greenhouse are non-linearly interlinked, thereby forming a non-linear multivariate system. Thus, an appropriately designed sensor system is needed for monitoring and controlling the greenhouse microclimate. Methods Research articles on greenhouse microclimate monitoring and control published in the last 6 years were considered. The sensor devices and technologies applied to control particular environmental parameters in the greenhouse and their key achievements were systematically reviewed. In addition, different approaches to determine the optimum number of sensors and their placement inside the greenhouse were investigated. Results It was found that spatially installed sensor devices above the plant height reflect the actual information of the environment getting by plant. Furthermore, both hardware and software-based sensing techniques control the greenhouse microclimate optimally. The proper positioning of sensors and their protection from harsh environmental factors is also essential. Conclusions It can be concluded that modern sensor devices and systems are driving the greenhouse monitoring and control system toward an intelligent, real-time, remotely accessible, and fully automatic system.

Assessments of different types of biodegradable pots strength and its effects on plant growth

( Fawad Khan ),( Gyeong Mun Choi ),( Na Eun Kim ),( Jayanta Kumar Basak ),( Mustafa Jaihuni ),( Anil Bhujel ),( Deog Hyun Lee ),( Hyeon Tae Kim ) 한국농업기계학회 2020 한국농업기계학회 학술발표논문집 Vol.25 No.2

This work is to increase the positive footprint of paper waste products by designing ‘‘eco-effective’’ solutions according to the regenerative design framework. Reutilization of five kinds of pots(waste of newspaper) is proposed here to close the loop at the end of the product life cycle. The aim was to design, manufacture and examine the strength of biodegradable pots were evaluated after the cultivation of paper plants. It is expected that by understanding the degradation rate of the investigated products and to support plant growth, it will be possible to optimize paper pots manufacturing to assure sufficient mechanical resistance and the desired rate of degradation. Five kinds (S0, S1, S1-1, S2, and S2-1) of biodegradable pots were made from old newspaper, and chilly plants were planted in the control greenhouse. Consequently, analysis of variance was performed, and a significant increase in holding moisture content was observed in S1 (73.75±1.92 %). The plant height (15.60±0.99 cm), stem diameter (1.60±0.20 cm), leaves length (3.51±0.0.20 cm) was higher in the S1 pots. However, the regression analysis values in the case of tension (R²=0.63) and compression (R²=0.99) with moisture content was shown by S0. It was concluded that S1 positively improve the growth of plants and hold optimum moisture content.

Semantic Segmentation of Strawberry Gray Mold Disease using Deep UNet

( Anil Bhujel ),( Jayanta Kumar Basak ),( Elanchezhian Arulmozhi ),( Thavisack Sihalath ),( Fawad Khan ),( Byeong Eun Moon ),( Mustafa Jaihuni ),( Deog Hyun Lee ),( Hyeon Tae Kim ) 한국농업기계학회 2020 한국농업기계학회 학술발표논문집 Vol.25 No.1

Gray mold is a common disease in strawberry, causing a devastating loss. Therefore, it is very important to identify the gray mold disease as early as possible and check the severity of the disease. The gray mold disease on strawberry plants was produced experimentally in a greenhouse located at Gyeongsang National University. The fungus “Botrytis cinerea” is the causal agent of gray mold disease, which was inoculated in the strawberry plants with three different concentrations (103, 105, and 107 MPN per 50 ml). The images of strawberry leaves infected by the disease were captured by the smartphone and pre-processed. In image pre-processing, removed the background of the image, created a mask of the lesion area of each image, and labeled them. A pair of the original image and its annotated mask were manually prepared and split into training and testing sets. A deep learning convolutional neural network-based UNet model was designed and trained by 45 sets of original and annotated pairs of images using heavy data augmentation. The model was trained for 10 epochs with 1000 steps per epoch, and the training accuracy achieved was 98.92%. Then the model was tested by 10 sets of original and annotated images, which gave the highest pixel accuracy of 98.21%. It was also tested by other segmentation metrics like the intersection of union (iu) and dice accuracy. The model provided the highest iu of 87.91% and dice accuracy of 92.91%. From the results, it can be concluded that the deep learning UNet can successfully segment the gray mold disease that occurred in strawberry, helping to identify the disease severity.