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The growing importance of rice globally over the past three decades is evident in its strategic place in many countries’ food security planning policies. Still, its cultivation emits substantial greenhouse gases (GHGs). The Indica and Japonica sub-species of Oryza sativa L. are mainly grown, with Indica holding the largest market share. The awareness, economics, and acceptability of Japonica rice in a food-insecure Indica rice-consuming population were surveyed. The impact of parboiling on Japonica rice was studied and the factors which most impacted stickiness were investigated through sensory and statistical analyses. A comparison of the growing climate and greenhouse gas emissions of Japonica and Indica rice was carried out by reviewing previous studies. Survey results indicated that non-adhesiveness and pleasant aroma were the most preferred properties. Parboiling treatment altered Japonica rice’s physical and chemical properties, introducing gelatinization of starch and reducing adhesiveness while retaining micronutrient concentrations. Regions with high food insecurity and high consumption of Indica rice were found to have suitable climatic conditions for growing Japonica rice. Adopting the higher-yielding, nutritious Japonica rice whose cultivation emits less GHG in these regions could help strengthen food security while reducing GHGs in global rice cultivation.
Daniel Dooyum Uyeh; Senorpe Asem-Hiablie; Tusan Park; Kyungmin Kim; Alexey Mikhaylov; Seungmin Woo; Yushin Ha. Could Japonica Rice Be an Alternative Variety for Increased Global Food Security and Climate Change Mitigation? Foods 2021, 10, 1869 .
AMA StyleDaniel Dooyum Uyeh, Senorpe Asem-Hiablie, Tusan Park, Kyungmin Kim, Alexey Mikhaylov, Seungmin Woo, Yushin Ha. Could Japonica Rice Be an Alternative Variety for Increased Global Food Security and Climate Change Mitigation? Foods. 2021; 10 (8):1869.
Chicago/Turabian StyleDaniel Dooyum Uyeh; Senorpe Asem-Hiablie; Tusan Park; Kyungmin Kim; Alexey Mikhaylov; Seungmin Woo; Yushin Ha. 2021. "Could Japonica Rice Be an Alternative Variety for Increased Global Food Security and Climate Change Mitigation?" Foods 10, no. 8: 1869.
Optimal placement of sensors in protected cultivation systems to maximize monitoring and control capabilities can guide effective decision-making toward achieving the highest levels of productivity and other desirable outcomes. Reinforcement learning, unlike conventional machine learning methods such as supervised learning does not require large, labeled datasets thereby providing opportunities for more efficient and unbiased design optimization. With the objective of determining the optimal locations of sensors in a greenhouse, a multi-arm bandit problem was formulated using the Beta distribution and solved by the Thompson sampling algorithm. A total of 56 two-in-one sensors designed to measure both internal air temperature and relative humidity were installed at a vertical distance of 1 m and a horizontal distance of 3m apart in a greenhouse used to cultivate strawberries. Data was collected over a period of seven months covering four major seasons, February (winter), March, April, and May (spring), June and July (summer), and October (autumn) and analyzed separately. Results showed unique patterns for sensor selection for temperature and relative humidity during the different months. Furthermore, temperature and relative humidity each had different optimal location selections suggesting that two-in-one sensors might not be ideal in these cases. The use of reinforcement learning to design optimal sensor placement in this study aided in identifying 10 optimal sensor locations for monitoring and controlling temperature and relative humidity.
Daniel Dooyum Uyeh; Blessing Itoro Bassey; Rammohan Mallipeddi; Senorpe Asem-Hiablie; Maryleen Amaizu; Seungmin Woo; Yushin Ha; Tusan Park. A Reinforcement Learning Approach for Optimal Placement of Sensors in Protected Cultivation Systems. IEEE Access 2021, 9, 100781 -100800.
AMA StyleDaniel Dooyum Uyeh, Blessing Itoro Bassey, Rammohan Mallipeddi, Senorpe Asem-Hiablie, Maryleen Amaizu, Seungmin Woo, Yushin Ha, Tusan Park. A Reinforcement Learning Approach for Optimal Placement of Sensors in Protected Cultivation Systems. IEEE Access. 2021; 9 ():100781-100800.
Chicago/Turabian StyleDaniel Dooyum Uyeh; Blessing Itoro Bassey; Rammohan Mallipeddi; Senorpe Asem-Hiablie; Maryleen Amaizu; Seungmin Woo; Yushin Ha; Tusan Park. 2021. "A Reinforcement Learning Approach for Optimal Placement of Sensors in Protected Cultivation Systems." IEEE Access 9, no. : 100781-100800.
The dry matter (DM) content of feed is vital in cattle nutrition and is inversely correlated with moisture content. The established ranges of moisture content serve as a marker for factors such as safe storage limit and DM intake. Rapid changes in moisture content necessitate rapid measurements. A rapid and non-destructive global model for the measurement of moisture content in total mixed ration feed and feed materials was developed. To achieve this, we varied and measured the moisture content in the feed and feed materials using standard methods and captured their images using a hyperspectral imaging (HSI) system in the spectral range of 1000–2500 nm. The spectral data from the samples were extracted and preprocessed using seven techniques and were used to develop a global model using partial least squares regression (PLSR) analysis. The range preprocessing technique had the best prediction accuracy (R2 = 0.98) and standard error of prediction (2.59%). Furthermore, the visual assessment of distribution in moisture content made possible by the generated PLSR-based moisture content mapped images could facilitate precise formulation. These applications of HSI, when used in commercial feed production, could help prevent feed spoilage and resultant health complications as well as underperformance of the animals from improper DM intake.
Daniel Uyeh; Juntae Kim; Santosh Lohumi; Tusan Park; Byoung-Kwan Cho; Seungmin Woo; Won Lee; Yushin Ha. Rapid and Non-Destructive Monitoring of Moisture Content in Livestock Feed Using a Global Hyperspectral Model. Animals 2021, 11, 1299 .
AMA StyleDaniel Uyeh, Juntae Kim, Santosh Lohumi, Tusan Park, Byoung-Kwan Cho, Seungmin Woo, Won Lee, Yushin Ha. Rapid and Non-Destructive Monitoring of Moisture Content in Livestock Feed Using a Global Hyperspectral Model. Animals. 2021; 11 (5):1299.
Chicago/Turabian StyleDaniel Uyeh; Juntae Kim; Santosh Lohumi; Tusan Park; Byoung-Kwan Cho; Seungmin Woo; Won Lee; Yushin Ha. 2021. "Rapid and Non-Destructive Monitoring of Moisture Content in Livestock Feed Using a Global Hyperspectral Model." Animals 11, no. 5: 1299.
Protected cultivation systems such as greenhouses are becoming increasingly popular globally and have been adopted because of unpredictable climatic conditions and their ability to easily control micro- and macroenvironments. However, limitations such as hazardous work environments and shortages in labor are major concerns for agricultural production using these structures. This has led to the development and adoption of robotic systems. For the efficient use of robots in protected cultivation systems, we formulate the work efficiency problem and model a three-dimensional standard strawberry greenhouse to analyze the effectiveness of a strawberry-harvesting robot compared to different levels of human workforce (experienced, average, and beginner). Simulations are conducted using Quest software to compare the efficiency of different scenarios of robotics to humans. Different methods of improvement from battery capacity and charge rate to harvesting speed are investigated and optimal conditions are recommended. The average hourly production of the robot is about five times lower than that of skilled workers. However, robots are more productive due to their ability to work around the clock. Comparative analyses show that a reduction in harvesting time per strawberry from 3 to 1 s would result in an increase in daily production from 347.93 to 1021.30 kg. This would lead to a five-fold increase in comparison to present daily production. A 10% improvement in battery charge time would result in the battery capacity gaining two extra hours from the current 10 h and would cut the current 2 h needed for charge to 1 h. This paper proposes an operation process and suggestions for changes needed for improving the work efficiency of robots in a greenhouse. This could be extended to other crops and greenhouses.
Seungmin Woo; Daniel Dooyum Uyeh; Junhee Kim; Yeongsu Kim; Seokho Kang; Kyoung Chul Kim; Si Young Lee; Yushin Ha; Won Suk Lee. Analyses of Work Efficiency of a Strawberry-Harvesting Robot in an Automated Greenhouse. Agronomy 2020, 10, 1751 .
AMA StyleSeungmin Woo, Daniel Dooyum Uyeh, Junhee Kim, Yeongsu Kim, Seokho Kang, Kyoung Chul Kim, Si Young Lee, Yushin Ha, Won Suk Lee. Analyses of Work Efficiency of a Strawberry-Harvesting Robot in an Automated Greenhouse. Agronomy. 2020; 10 (11):1751.
Chicago/Turabian StyleSeungmin Woo; Daniel Dooyum Uyeh; Junhee Kim; Yeongsu Kim; Seokho Kang; Kyoung Chul Kim; Si Young Lee; Yushin Ha; Won Suk Lee. 2020. "Analyses of Work Efficiency of a Strawberry-Harvesting Robot in an Automated Greenhouse." Agronomy 10, no. 11: 1751.
Journal of Animal Science and Technology (JAST) is a peer-reviewed, open access journal publishing original research, review articles and notes in all fields of animal science. Topics covered by the journal include: genetics and breeding, physiology, nutrition of monogastric animals, nutrition of ruminants, animal products (milk, meat, eggs and their by-products) and their processing, grasslands and roughages, livestock environment, animal biotechnology, animal behavior and welfare.
Seungmin Woo; Sooah Kim; Suji Ye; Soo Rin Kim; Jeongman Seol; Uyeh Daniel Dooyum; Junhee Kim; Dong Hyuck Hong; Jong Nam Kim; Yushin Ha. Effect of temperature on single- and mixed-strain fermentation of ruminant feeds. Journal of Animal Science and Technology 2020, 62, 227 -238.
AMA StyleSeungmin Woo, Sooah Kim, Suji Ye, Soo Rin Kim, Jeongman Seol, Uyeh Daniel Dooyum, Junhee Kim, Dong Hyuck Hong, Jong Nam Kim, Yushin Ha. Effect of temperature on single- and mixed-strain fermentation of ruminant feeds. Journal of Animal Science and Technology. 2020; 62 (2):227-238.
Chicago/Turabian StyleSeungmin Woo; Sooah Kim; Suji Ye; Soo Rin Kim; Jeongman Seol; Uyeh Daniel Dooyum; Junhee Kim; Dong Hyuck Hong; Jong Nam Kim; Yushin Ha. 2020. "Effect of temperature on single- and mixed-strain fermentation of ruminant feeds." Journal of Animal Science and Technology 62, no. 2: 227-238.
There has been rapid increase in demand for premium and safe agricultural products. Protected systems such as greenhouses have been adopted to meet demand. Ease in environmental regulation required for optimal plant growth is one of the advantages of protected systems. However, drawbacks such as poor ventilation in greenhouses can be fatal to the human workforce. This has led to the development of robots for hazardous tasks. Considering mobile robots are required to navigate down every aisle to perform a task in a greenhouse, it is difficult to predict at which point the robot will need to return to the start point; to offload or refill for transportation and spraying schedules respectively or charge the battery for all category of robots. It will be commercially constraining to manufacture robots for every greenhouse specification. Efficient navigation can be done through path planning or layout design. In this study, the greenhouse layout optimization problem was formulated to find optimal points on each bed to create an access path that would enable reduction in travel time from any point in the greenhouse to the base point. The optimization problem was solved using Differential Evolution (DE), an evolutionary algorithm. Furthermore, we considered: a) required space for inter-bed and rotary robot navigation b) standard bed specification, c) area of the greenhouse, and d) base point for robot starting and termination. The applicability of the proposed method was demonstrated by carrying out experimental simulations on several greenhouse sizes.
Daniel Dooyum Uyeh; Fitria Wulandari Ramlan; Rammohan Mallipeddi; Tusan Park; Seungmin Woo; Junhee Kim; Yeongsu Kim; Yushin Ha. Evolutionary Greenhouse Layout Optimization for Rapid and Safe Robot Navigation. IEEE Access 2019, 7, 88472 -88480.
AMA StyleDaniel Dooyum Uyeh, Fitria Wulandari Ramlan, Rammohan Mallipeddi, Tusan Park, Seungmin Woo, Junhee Kim, Yeongsu Kim, Yushin Ha. Evolutionary Greenhouse Layout Optimization for Rapid and Safe Robot Navigation. IEEE Access. 2019; 7 (99):88472-88480.
Chicago/Turabian StyleDaniel Dooyum Uyeh; Fitria Wulandari Ramlan; Rammohan Mallipeddi; Tusan Park; Seungmin Woo; Junhee Kim; Yeongsu Kim; Yushin Ha. 2019. "Evolutionary Greenhouse Layout Optimization for Rapid and Safe Robot Navigation." IEEE Access 7, no. 99: 88472-88480.
A. It is better to skip the parboiling process than to perform the process improperly. Unfortunately, improper parboiling of rice is a custom in most of the developing countries where there is heavy dependence on rice. b. Variety of rice plays vital role in the degree to which the factors should be combined during the parboiling process. Research should always be carried out on new developed varieties before commercial parboiling commences. c. Parboiling process has impact on rice in diverse ways. It affects the color intensity, lightness, impacts hardness, increase milling yield, etc. d. Different lots of paddy with different initial moisture contents can be mixed safely for parboiling without any loss in quality or quantity. e. Proper parboiling of rice will have significant impact on human health especially in rice consuming nations.Key words: Milling, Optimization, Parboiling, Post-Harvest, Rice
Daniel Uyeh; Seung Woo; Dong Hong; Yu Ha. Optimization of parboiling conditions for enhanced Japonica rice milling. Emirates Journal of Food and Agriculture 2016, 28, 1 .
AMA StyleDaniel Uyeh, Seung Woo, Dong Hong, Yu Ha. Optimization of parboiling conditions for enhanced Japonica rice milling. Emirates Journal of Food and Agriculture. 2016; 28 (11):1.
Chicago/Turabian StyleDaniel Uyeh; Seung Woo; Dong Hong; Yu Ha. 2016. "Optimization of parboiling conditions for enhanced Japonica rice milling." Emirates Journal of Food and Agriculture 28, no. 11: 1.