How Profitable and Energy-Efficient Is Nepal’s Crop Production? A Case Study of Spring Rice Production in Jhapa District

2021 ◽  
Author(s):  
Padam Prasad Paudel ◽  
Dharma Raj Pokhrel ◽  
Sajan Koirala ◽  
Lalan Baitha ◽  
Dae Hyun Kim ◽  
...  
Keyword(s):  
Energy Efficient ◽  
Crop Production ◽  
Rice Production

scholarly journals Farmers’ Awareness of the Low Yield of Conventional Rice Production in Ayeyarwady Region, Myanmar: A Case Study of Myaungmya District

Agriculture ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 26 ◽  
Author(s):  
Soe Paing Oo
Keyword(s):  
Crop Production ◽  
Field Survey ◽  
Agricultural Practices ◽  
Rice Production ◽  
Adoption Process ◽  
Total Income ◽  
Conventional Production ◽  
Binary Logit ◽  
Farmer Management

The Ministry of Agriculture and Irrigation introduced the Good Agricultural Practices (GAPs) of rice in 2008. The adoption rate of GAPs is still low. As the first step of the adoption process, this study investigates farmers’ awareness of the low yield of conventional rice production. Based on the data of 315 farmers collected from a field survey conducted from July to August 2018 in Myaungmya District, Myanmar, and by applying the cluster analysis and binary logit model, the study found that farmers’ awareness was low for the aspects of farmer management and Ministry management. The finding of most interest is that farmers with more experience, higher income level, larger farmland size, and receiving agricultural information were associated with low awareness. Farmers with more farming experience were satisfied with the return of rice from conventional production. Some farmers received a higher total income from crop production because of a larger farmland size, and they are less aware of the low yield of conventional rice production. Even though farmers received agricultural information, they could not apply the information to rice production. Farmers’ awareness of the low yield can be increased through developing extension services programs to distribute useful information on rice production effectively.

Water Management in Relation to Crop Production: Case Study on Rice

1992 ◽  
Vol 21 (4) ◽  
pp. 293-299 ◽  
Author(s):  
Sadiq I. Bhuiyan
Keyword(s):  
Water Management ◽  
Water Resources ◽  
Irrigation Water ◽  
Crop Production ◽  
Rice Production ◽  
Staple Food ◽  
Foreseeable Future ◽  
Production Growth

Rice is the staple food of nearly half of the world's population, most of whom live in Asia. For intensive, high-yielding rice production, access to irrigation water and drainage facilities is crucial. Provision of irrigation facilities expanded rapidly in the 1970's and early 1980's in the major rice-producing countries of Asia, but the management of water has remained inefficient. Investments in new irrigation have declined as the rice supply improved and the development of new water resources became increasingly costly. This trend is not likely to be reversed in the foreseeable future. Consequently, improved efficiency in the use of water is needed to maintain rice production growth.

scholarly journals On the Investigation of Energy Efficient Torque Distribution Strategies through a Comprehensive Powertrain Model

2021 ◽  
Vol 13 (8) ◽  
pp. 4549
Author(s):  
Sara Salamone ◽  
Basilio Lenzo ◽  
Giovanni Lutzemberger ◽  
Francesco Bucchi ◽  
Luca Sani
Keyword(s):  
Energy Storage ◽  
Electric Vehicles ◽  
Energy Efficient ◽  
Storage System ◽  
Energy Storage System ◽  
Torque Distribution ◽  
Driving Cycles ◽  
Energy Models ◽  
Battery State Of Charge

In electric vehicles with multiple motors, the torque at each wheel can be controlled independently, offering significant opportunities for enhancing vehicle dynamics behaviour and system efficiency. This paper investigates energy efficient torque distribution strategies for improving the operational efficiency of electric vehicles with multiple motors. The proposed strategies are based on the minimisation of power losses, considering the powertrain efficiency characteristics, and are easily implementable in real-time. A longitudinal dynamics vehicle model is developed in Simulink/Simscape environment, including energy models for the electrical machines, the converter, and the energy storage system. The energy efficient torque distribution strategies are compared with simple distribution schemes under different standardised driving cycles. The effect of the different strategies on the powertrain elements, such as the electric machine and the energy storage system, are analysed. Simulation results show that the optimal torque distribution strategies provide a reduction in energy consumption of up to 5.5% for the case-study vehicle compared to simple distribution strategies, also benefiting the battery state of charge.

scholarly journals Assessment of water footprint for crop production: a case study in North China

2021 ◽  
Vol 831 (1) ◽  
pp. 012047
Author(s):  
Chunxiao Wang ◽  
Jing Zhao ◽  
Baochuan Tian
Keyword(s):  
Crop Production ◽  
North China ◽  
Water Footprint

A new framework to select energy-efficient retrofit schemes of external walls: A case study

2021 ◽  
Vol 289 ◽  
pp. 125718
Author(s):  
Fan Zhang ◽  
Yanbing Ju ◽  
Ernesto D.R. Santibanez Gonzalez ◽  
Aihua Wang ◽  
Peiwu Dong ◽  
...  
Keyword(s):  
Energy Efficient ◽  
New Framework

scholarly journals Predicting Shifts in Land Suitability for Maize Cultivation Worldwide Due to Climate Change: A Modeling Approach

Land ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 295
Author(s):  
Yuan Gao ◽  
Anyu Zhang ◽  
Yaojie Yue ◽  
Jing’ai Wang ◽  
Peng Su
Keyword(s):  
Climate Change ◽  
Crop Production ◽  
Large Scale ◽  
Land Suitability ◽  
Large Scale Assessment ◽  
Scale Assessment ◽  
Maize Cultivation ◽  
Large Scale Screening ◽  
Selection Of

Suitable land is an important prerequisite for crop cultivation and, given the prospect of climate change, it is essential to assess such suitability to minimize crop production risks and to ensure food security. Although a variety of methods to assess the suitability are available, a comprehensive, objective, and large-scale screening of environmental variables that influence the results—and therefore their accuracy—of these methods has rarely been explored. An approach to the selection of such variables is proposed and the criteria established for large-scale assessment of land, based on big data, for its suitability to maize (Zea mays L.) cultivation as a case study. The predicted suitability matched the past distribution of maize with an overall accuracy of 79% and a Kappa coefficient of 0.72. The land suitability for maize is likely to decrease markedly at low latitudes and even at mid latitudes. The total area suitable for maize globally and in most major maize-producing countries will decrease, the decrease being particularly steep in those regions optimally suited for maize at present. Compared with earlier research, the method proposed in the present paper is simple yet objective, comprehensive, and reliable for large-scale assessment. The findings of the study highlight the necessity of adopting relevant strategies to cope with the adverse impacts of climate change.

scholarly journals Towards DC Energy Efficient Homes

2021 ◽  
Vol 11 (13) ◽  
pp. 6005
Author(s):  
Daniel Villanueva ◽  
Moisés Cordeiro-Costas ◽  
Andrés E. Feijóo-Lorenzo ◽  
Antonio Fernández-Otero ◽  
Edelmiro Miguez-García
Keyword(s):  
Energy Efficiency ◽  
Electric Vehicles ◽  
Energy Efficient ◽  
Electricity Consumption ◽  
Real Data ◽  
Mean Values ◽  
Led Lighting ◽  
Shed Light

The aim of this paper is to shed light on the question regarding whether the integration of an electric battery as a part of a domestic installation may increase its energy efficiency in comparison with a conventional case. When a battery is included in such an installation, two types of electrical conversion must be considered, i.e., AC/DC and DC/AC, and hence the corresponding losses due to these converters must not be forgotten when performing the analysis. The efficiency of the whole system can be increased if one of the mentioned converters is avoided or simply when its dimensioning is reduced. Possible ways to achieve this goal can be: to use electric vehicles as DC suppliers, the use of as many DC home devices as possible, and LED lighting or charging devices based on renewables. With all this in mind, several scenarios are proposed here in order to have a look at all possibilities concerning AC and DC powering. With the aim of checking these scenarios using real data, a case study is analyzed by operating with electricity consumption mean values.

scholarly journals Augmenting Crop Detection for Precision Agriculture with Deep Visual Transfer Learning—A Case Study of Bale Detection

2020 ◽  
Vol 13 (1) ◽  
pp. 23
Author(s):  
Wei Zhao ◽  
William Yamada ◽  
Tianxin Li ◽  
Matthew Digman ◽  
Troy Runge
Keyword(s):  
Object Detection ◽  
Transfer Learning ◽  
Precision Agriculture ◽  
Crop Production ◽  
Domain Adaptation ◽  
Training Data ◽  
Detection Accuracy ◽  
Detection Model ◽  
Agriculture Products

In recent years, precision agriculture has been researched to increase crop production with less inputs, as a promising means to meet the growing demand of agriculture products. Computer vision-based crop detection with unmanned aerial vehicle (UAV)-acquired images is a critical tool for precision agriculture. However, object detection using deep learning algorithms rely on a significant amount of manually prelabeled training datasets as ground truths. Field object detection, such as bales, is especially difficult because of (1) long-period image acquisitions under different illumination conditions and seasons; (2) limited existing prelabeled data; and (3) few pretrained models and research as references. This work increases the bale detection accuracy based on limited data collection and labeling, by building an innovative algorithms pipeline. First, an object detection model is trained using 243 images captured with good illimitation conditions in fall from the crop lands. In addition, domain adaptation (DA), a kind of transfer learning, is applied for synthesizing the training data under diverse environmental conditions with automatic labels. Finally, the object detection model is optimized with the synthesized datasets. The case study shows the proposed method improves the bale detecting performance, including the recall, mean average precision (mAP), and F measure (F1 score), from averages of 0.59, 0.7, and 0.7 (the object detection) to averages of 0.93, 0.94, and 0.89 (the object detection + DA), respectively. This approach could be easily scaled to many other crop field objects and will significantly contribute to precision agriculture.

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