semi-automatic soybean machine in nepal
- Usage: Soybean Oil, Cooking Oil
- Type: Soybean Oil Extraction Machine
- Production Capacity: 800KG/H
- Voltage: 380V/50HZ
- Dimension(L*W*H): 2670*1000*1726mm
- Weight: 1800kg
- Core Components: Gear, Bearing, Gearbox
- Oil type: Soybean Oil
- After Warranty Service: Video technical support, Online support, Spare parts, Field maintenance and repair service
- Local Service Location: Egypt, Turkey, Italy, Germany, Viet Nam, Brazil, Saudi Arabia, Indonesia, Pakistan, India, Mexico, Russia, Thailand, Malaysia, Australia, Kenya, Argentina, Chile, UAE, Colombia, Algeria, Sri Lanka, Bangladesh, South Africa, Kazakhstan, Ukraine, Kyrgyzstan, Nigeria, Uzbekistan, Tajikistan
- Certification: ISO
REVIEW ARTICLE ON STATUS OF SOYBEAN PRODUCTION IN NEPAL
The total world. production for soybeans is 348,712,311 metric tonnes (FAO,2018 ). In ca se. of Nepal, it is grown in 29282 ha with production and productivity of. 28270 Mt and 965 kg/ha
of this crop in Nepal is 2,93,173 hectare 28,318 metric tons and 0.96 tons/ha respectively (ABPSD, 2012). About 80% of total soybean area and productio n is occupied by mid-hills. However, soybean
Morphological characterization and evaluation of soybean genotypes
In Nepal, it is grown in 22507 ha with production and productivity of 28335 ton and 1.25 ton ha-1 respectively [4]. Soybean is becoming popular as a sole crop or on the rice bunds in terai and inner terai of Nepal due to the high demand of the soya meal in poultry industry.
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HOME - Machine Hub Nepal. We are a machine manufacturing company situated in Budhanilkantha, Kathmandu. We provide construction as well as agricultural machines and equipments. Contact us for any queries in either call or whatsapp in +9779851181127.
Agricultural mechanization in developing countries has taken at least two contested innovation pathways—the “incumbent trajectory” that promotes industrial agriculture, and an “alternative pathway” that supports small-scale mechanization for sustainable development of hillside farming systems. Although both pathways can potentially reduce human and animal drudgery, the body of
Semi‐automatic leaf disease detection and classification system
A similar study is performed for Soybean using leaf images. A rule based semi-automatic system using concepts of k-means is designed and implemented to distinguish healthy leaves from diseased leaves. In addition, a diseased leaf is classified into one of the three categories (downy mildew, frog eye, and Septoria leaf blight).
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