scholarly journals Average temperature of soil-strata in the paddy field, and its effects on the rice-crop

1953 ◽  
Vol 8 (1-2) ◽  
pp. 1-3
Author(s):  
S. SATO
Keyword(s):  
Paddy Field ◽  
Rice Crop ◽  
Average Temperature

Toxicity of biocides to native cyanobacteria at different rice crop stages in wetland paddy field

2017 ◽  
Vol 30 (1) ◽  
pp. 483-493 ◽  
Author(s):  
Nalinaxya Prasad Dash ◽  
Manish Singh Kaushik ◽  
Ajay Kumar ◽  
Gerard Abraham ◽  
Pawan Kumar Singh
Keyword(s):  
Paddy Field ◽  
Rice Crop

scholarly journals Nitrogen and phosphorus effluent loads from a paddy-field district adopting collective crop rotation

2012 ◽  
Vol 66 (5) ◽  
pp. 1074-1080 ◽  
Author(s):  
T. Hama ◽  
T. Aoki ◽  
K. Osuga ◽  
S. Sugiyama ◽  
D. Iwasaki
Keyword(s):  
Crop Rotation ◽  
Paddy Field ◽  
Surface Runoff ◽  
Paddy Rice ◽  
Rice Crop ◽  
Nutrient Load ◽  
Nitrogen And Phosphorus ◽  
Investigation Period ◽  
Rotation Crops

Japanese paddy rice systems commonly adopt the rotation of vegetables, wheat and soybeans with paddy rice. Crop rotation may, however, increase the nutrient load in effluent discharged from the district because more fertilizer is applied to the rotation crops than is applied to paddy crops. We investigated a paddy-field district subject to collective crop rotation and quantified the annual nutrient load of effluent from the district in three consecutive years. The total annual exports of nitrogen and phosphorus over the investigation period ranged from 30.3 to 40.6 kg N ha–1 and 2.62 to 3.13 kg P ha–1. The results suggest that rotation cropping increases the effluent nutrient load because applied fertilizer is converted to nitrate, and surface runoff is increased due to the absence of shuttering boards at the field outlets.

scholarly journals A Survey on Rice Crop Yield Prediction in India Using Improved Classification Technique

2019 ◽  
pp. 501-507
Author(s):  
Kolin Sukhadia ◽  
M. B. Chaudhari
Keyword(s):  
Crop Yield ◽  
Crop Production ◽  
Potential Evapotranspiration ◽  
Environmental Parameters ◽  
Rice Crop ◽  
Maximum Temperature ◽  
Support Vector ◽  
Pressure Potential ◽  
Average Temperature ◽  
Reference Crop

<p>India is an agricultural country. Agriculture is the important contributor to the Indian economy. There are many classification techniques like Support Vector Machine(SVM), LADTree, Natve Bayes, Bayesnet, K Nearest Neighbour(KNN), Locally Weighted Learning(LWL) on rice crop production datasets. They have some drawbacks like low accuracy and more errors. To achieve more significant result, To increase classification accuracy and reducing classification errors, our research uses classification method Bayesnet based adaboost will be proposed in work. Rice crop yield depend on environment's parameters like Rainfall, minimum temperature, average temperature, Maximum temperature, Vapour Pressure, potential evapotranspiration, reference crop evapotranspiration, cloud cover, wet day frequency for the kharif season. our dataset containing these environmental parameters for accurate prediction of Rice crop yield.</p>

scholarly journals Monitoring Rice Crop and Paddy Field Condition Using UAV RGB Imagery

2021 ◽  
Vol 5 (4) ◽  
pp. 469
Author(s):  
Mohd Yazid Abu Sari ◽  
Yana Mazwin Mohmad Hassim ◽  
Rahmat Hidayat ◽  
Asmala Ahmad
Keyword(s):  
Field Condition ◽  
Paddy Field ◽  
Crop Production ◽  
Industrial Revolution ◽  
Management Practice ◽  
Digital Camera ◽  
Crop Management ◽  
Rice Crop ◽  
Large Area ◽  
Crop Condition

An effective crop management practice is very important to the sustenance of crop production. With the emergence of Industrial Revolution 4.0 (IR 4.0), precision farming has become the key element in modern agriculture to help farmers in maintaining the sustainability of crop production. Unmanned aerial vehicle (UAV) also known as drone was widely used in agriculture as one of the potential technologies to collect the data and monitor the crop condition. Managing and monitoring the paddy field especially at the bigger scale is one of the biggest challenges for farmers. Traditionally, the paddy field and crop condition are only monitored and observed manually by the farmers which may sometimes lead to inaccurate observation of the plot due the large area. Therefore, this study proposes the application of unmanned aerial vehicles and RGB imagery for monitoring rice crop development and paddy field condition. The integration of UAV with RGB digital camera were used to collect the data in the paddy field. Result shows that the early monitoring of rice crops is important to identify the crop condition. Therefore, with the use of aerial imagery analysis from UAV, it can help to improve rice crop management and eventually is expected to increase rice crop production.

Siam Suffers from Poor Rice Crop

1938 ◽  
Vol 7 (1) ◽  
pp. 10-11
Author(s):  
E. O. H.
Keyword(s):  
Rice Crop

The concept of local explosion in freshwater ecosystems

2013 ◽  
Vol 25 (1-2) ◽  
pp. 136-148
Author(s):  
I. V. Gryb
Keyword(s):  
Species Composition ◽  
Aquatic Environment ◽  
Arid Zone ◽  
Fish Fauna ◽  
River Basins ◽  
Freshwater Ecosystems ◽  
Human Society ◽  
Living Matter ◽  
Ecosystem Recovery ◽  
Average Temperature

The concept of an explosion in freshwater ecosystems as a result of the release of accumulated energy, accompanied by the destruction of the steady climax successions of hydrocenoses is presented. The typification of local explosions as well as methods for assessing their risk during the development of river basins are shown. The change in atmospheric circulation, impaired phases of the hydrological regime of rivers, increasing the average temperature of the planet, including in Polesie to 0,6 ºC, deforestation leads to concentration and release of huge amounts of unmanaged terrestrial energy, which manifests itself in the form of disasters and emergencies. Hydroecological explosion is formed as a result of multifactorial external influence (natural and anthropogenic) on the water body in a certain period of time. Moreover, its level at wastewater discharge depends on the mass of recycled impurities and behaved processing capacity of the reservoir, and the mass of dumped on biocides and the possibility of the water flow to their dilution and to the utilization of non-toxic concentrations. In all these cases the preservation of "centers of life" in the tributaries of the first order – local fish reproduction areas contributed to ecosystem recovery, and the entire ecosystem has evolved from equilibrium to non-equilibrium with further restructuring after the explosion and environmental transition to a new trophic level. It means that hydroecological explosion can be researched as the logical course of development of living matter in abiotic environmental conditions, ending abruptly with the formation of new species composition cenoses and new bio-productivity. The buffer capacity of the water environment is reduced due to re-development and anthropic transformation of geobiocenoses of river basins, which leads to a weakening of life resistance. This applies particularly to the southern industrial regions of Ukraine, located in the arid zone that is even more relevant in the context of increased average temperature due to the greenhouse effect, as well as to Polesie (Western, Central and Chernihiv), had been exposed to large-scale drainage of 60-80th years, which contributed to the degradation of peatlands and fitostroma. Imposing the western trace of emissions from the Chernobyl accident to these areas had created the conditions of prolonged hydroecological explosion in an intense process of aging water bodies, especially lakes, change in species composition of fish fauna and the occurrence of neoplasms at the organismal level. Under these conditions, for the existence of man and the environment the vitaukta should be strengthened, i.e. buffer resistance and capacitance the aquatic environment, bioefficiency on the one hand and balanced using the energy deposited - on the other. This will restore the functioning of ecosystems "channel-floodplain", "riverbed-lake", reducing the energy load on the aquatic environment. Hydroecological explosions of natural origin can not be considered a pathology – it is a jump process of natural selection of species of biota. Another thing, if they are of anthropogenic origin and if the magnitude of such an impact is on the power of geological factors. Hydroecological explosions can be regarded as a manifestation of environmental wars that consciously or unconsciously, human society is waging against themselves and their kind in the river basins, so prevention of entropy increase in the aquatic environment and the prevention of hydroecological explosions is a matter of human survival. While the man - is not the final link in the development of living matter, it can develop without him, as matter is eternal, and the forms of its existence are different.

The Diffusion of Agricultural Exterminators in the Paddy Field and its Influence on Silkworms

1976 ◽  
Vol 32 (1) ◽  
pp. 11-17 ◽  
Author(s):  
Seiji HAYAKAWA ◽  
Tsutomu SAKANOUE ◽  
Yushiro MOTODA ◽  
Shoichiro NISHI
Keyword(s):  
Paddy Field

County-level USA: No Robust Relationship between Geoclimatic Variables and Cognitive Ability

2020 ◽  
Author(s):  
Bryan J Pesta ◽  
John Fuerst ◽  
Emil O. W. Kirkegaard
Keyword(s):  
Cognitive Ability ◽  
Climate Models ◽  
Cold Weather ◽  
Regression Equations ◽  
County Level ◽  
Spatial Lag ◽  
Average Temperature ◽  
Wrong Direction ◽  
Race Ethnicity ◽  
Demographic Covariates

Using a sample of ~3,100 U.S. counties, we tested geoclimatic explanations for why cognitive ability varies across geography. These models posit that geoclimatic factors will strongly predict cognitive ability across geography, even when a variety of common controls appear in the regression equations. Our results generally do not support UV radiation (UVR) based or other geoclimatic models. Specifically, although UVR alone predicted cognitive ability at the U.S. county-level (β = -.33), its validity was markedly reduced in the presence of climatic and demographic covariates (β = -.16), and was reduced even further with a spatial lag (β = -.10). For climate models, average temperature remained a significant predictor in the regression equation containing a spatial lag (β = .35). However, the effect was in the wrong direction relative to typical cold weather hypotheses. Moreover, when we ran the analyses separately by race/ethnicity, no consistent pattern appeared in the models containing the spatial lag. Analyses of gap sizes across counties were also generally inconsistent with predictions from the UVR model. Instead, results seemed to provide support for compositional models.

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