Study Life in Niigata University
Bio-Production and Machinery Laboratory at Niigata University, Japan, offers innovative solutions for production, machinery, engineering, research, and development. With cutting-edge technology, we carry out research and development activities to improve agricultural practices, develop new agricultural technologies and enhance the quality of agricultural products. Our Laboratory brings together students from around the world who share a passion for utilizing the latest technology in agriculture.
Welcome to Bio-Production and Machinery Laboratory
Meet our Team
Our range of research covers but is not limited to Remote Sensing, Climate Smart Agriculture, Bio-Production and Machinery, Soil and Crop Properties, Data Management, and Analysis.
Research Activities
Development of deep placement fertilizer applicator for soybean production in the Amur region
Investigates the specific soil properties that contribute to the optimal growth of soybean crops and explore new pre-sowing and fertilizing techniques to maximize yields. Additionally, simulates the implementation of the fertilizing machine to assess its effectiveness in improving crop yields.
Evaluation of different fertilizer application technologies: deep placement of slow-release lime nitrogen a pathway for nutrient management to enhance yields of soybean in Mozambique
Assessing Soybean yield under various fertilizer technologies. Evaluating soybean performance, examining deep slow-release fertilizer technology and its efficiency in reducing nitrogen losses
Assessing the Relationship between Soil Characteristics, Vegetation Indices, and Soybean Yield Using Multi-Temporal Remote Sensing Data"
Aim to investigate the relationship
between soil characteristics, vegetation
indices, and soybean yield using multitemporal remote sensing data
History, current situation, and prospectives of soybean breeding, soybean variety in Russia
Using QGIS to visualize the number of soybean varieties registered in Russia and its federal subjects can be created. Additionally, an analysis of the structure of soybean originators in the far east can be conducted which could help in predicting potential future scenarios.
Predictive Model for Automated Chamber Measurement of Agricultural GHG Emissions using Machine Learning Approach
An emission prediction model based on combining data-driven ML and biophysical-based approaches, hybrid models including soil physiochemical processes, crop rotation data, and seasonal vegetation fluctuations.
Multispectral Analysis and soil mapping usimg remote sensing technoogy
Enhanced soil mapping accuracy for precision agricultural improved decision-making for soil management and fertilization, and increased crop yield through optimized resource allocation.
Publications
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Quality Evaluation of Kohaku Koi (Cyprinus rubrofuscus) Using Image Analysis
Mikhail A. Domasevich, Hideo Hasegawa, Tatsuya Yamazaki
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Effects of Tillage Systems on Grain Production in the Republic of Buryatia, Russia
Tsyden Sandakov, Hideo Hasegawa, Daba Radnaev, Nadezhda Sandakova, Anna Lyude
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Agricultural Machinery Cluster Formation Model under Import Substitution in Russia
Nadezhda Sandakova, Hideo Hasegawa, Anna Lyude, Tsyden Sandakov, Elizaveta Kolesnikova
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Current Status and Perspectives on Agricultural Engineering in Central Asian Countries
Abdukarim Usmanov, Vladimir Golikov, Askar Rzaliev, Marat Kaliaskarov, Hideo Hasegawa
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Current Status and Perspectives of Agricultural Mechanization in Primorsky Krai, Russian Federation
Iaroslav Patuk, Hideo Hasegawa, Piotr F. Borowski -
Simulation for Design and Material Selection of a Deep Placement Fertilizer Applicator for Soybean Cultivation
Iaroslav Patuk, Hideo Hasegawa, Igor Borodin, Andrew C. Whitaker, Piotr F. Borowski
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Comparison of NDVI and NDRE Indices to Detect Differences in Vegetation and Chlorophyll Content
Boris Boiarskii, Hideo Hasegawa
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Application of UAV-derived digital elevation model in agricultural field to determine waterlogged soil areas in Amur region, Russia
Boris Boiarskii, Hideo Hasegawa, Aleksei Muratov, Vladimir Sudeykin
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Application of UAV and multispectral camera for field survey in the Amur Region, Russia
Boris Boiarskii, Hideo Hasegawa, Mikhail Sinegovskii, Anastasiia Boiarskaia
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Optimum design of a chisel plow for grain production in the Republic of Buryatia, Russian Federation
Tsyden Sandakov, Hideo Hasegawa, Nadezhda Sandakova, Lin Chang, Daba Radnaev
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An Overview of the Seed Sector in the Republic of Mozambique
Missels Quécio Carlos Monjane, António Machava Júnior, Mauro Estevão Machipane, Hideo Hasegawa
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The Current Situation and Perspectives Regarding Agricultural Mechanization in the Republic of Mozambique
Missels Quécio Carlos Monjane, António Jacinto, Paulo da Graça, Hideo Hasegawa
Research Equipment
UAV
In the laboratory, we have three types of UAV; Matrice 100, Mavic 2 pro and Matrice 300RTK drones. These are used for survey purposes. Attached to the drone is a multispectral camera Mcasense rededge P.
Veris on-the-go soil sensor
This is a newly acquired equipment which is on of the first in Japan. This is used to precisely map the properties of the soil such as soil tecture, PH and organic matter.
Agricultural Machinery/equipment
In this laboratory, we have various machinery such as kubota Agri-robo tractor, harvester, Rice reaper, boom sprayer, potatoe harvester, offset shredder, Twin rake, subsoiler amongst many others.
SPAD meter
The SPAD chlorophyll meter is a tool for estimating "greenness" of leaves, an indicator of relative nitrogen (N) content (Spectrum Technologies)
SPAD is used to assess nitrogen (N) needs, research shows a strong correlation between SPAD measurements and leaf nitrogen (N) content.
JICA Alumni
Monjane Missels Quecio Carlos (Mozambique) Msc class of 2019
Missels Monjane from Mozambique is a beneficiary of the JICA ABE initiative and SDG program. He obtained his masters degree from the graduate school of science and technology Niigata University batch 3 in 2019.He applied again for the doctoral scholarship of JICA SDGs golbal leadership program and started his Ph.D from the same graduate school. He is currently enrolled in the 3rd year.
Guei Mahe Frank (Cote D' Ivoire) Msc class of 2023
Mahe Guei Frank was a masters student from Cote D' Ivoire who was a beneficiary of the JICA ABE initiative 2020 7th batch. His research during his masters program was focused on "Study on perfprmance on cage wheels and its improvement for Cote D' Ivoire". He is currently back top to his home town and applying the knowledge gained from his studies.
Mavia Edson Dario (Mozambique) Msc class of 2023
Mavia Edson Dario from the rebublic of Mozambique was a beneficiary of the JICA ABE initiative program 2020 7th batch. During his study at Niigata University; his research focused on "weed control in maize production and comparative effects of organic and inorganic fertilizers in soybean production. He is currently back in his home country and applying the knowledge he gained from his study.
Ajayi Ayomikun David (Nigeria) Msc class of 2023
David Ayomikun Ajayi is a first year doctoral student at Niigata University. He was a beneficiary of the JICA ABE initiative program 2020 7th batch. His research during his masters program was focused on "Automated mapping and assesment of agricultural fields for digital transformation in Nigeria". As part of JICA's objectives to support developing countries to transorfm their economies through digitalization; his research addresses these issues and optimize the agriculture value chain by implementing innovative digital technologies.