scholarly journals Fundamental Studies on Yield-Forecast for Rice Plants : 15. Characters of rice yield-components in the order of culm length through the practical simplified survey method (5)

1967 ◽  
Vol 36 (2) ◽  
pp. 129-132
Author(s):  
Tetsujiro SUGAHARA ◽  
Yoji HAYASHI
Keyword(s):  
Yield Components ◽  
Rice Yield ◽  
Survey Method ◽  
Rice Plants ◽  
Culm Length ◽  
Yield Forecast

Development of gene-tagged markers for quantitative trait loci underlying rice yield components

Euphytica ◽  
2009 ◽  
Vol 169 (2) ◽  
pp. 215-226 ◽  
Author(s):  
Chang-Jie Yan ◽  
Song Yan ◽  
Ya-Chun Yang ◽  
Xiu-Hong Zeng ◽  
Yu-Wei Fang ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Yield Components ◽  
Rice Yield ◽  
Trait Loci

scholarly journals Effects of days to heading on culm length of rice plants.

1987 ◽  
Vol 37 (1) ◽  
pp. 88-97
Author(s):  
Yo-Ichiro SATO
Keyword(s):  
Rice Plants ◽  
Culm Length ◽  
Days To Heading

Rice yield forecast based on satellite and meteorological data

2010 ◽  
Vol 36 (6) ◽  
pp. 424-427 ◽  
Author(s):  
I. Yu. Savin ◽  
V. A. Isaev
Keyword(s):  
Rice Yield ◽  
Meteorological Data ◽  
Yield Forecast

Effect of uneven emergence on rice yield, milling yield, and yield components

1994 ◽  
Vol 34 (7) ◽  
pp. 949 ◽  
Author(s):  
KA Gravois ◽  
RS Helms
Keyword(s):  
Yield Components ◽  
Management Practices ◽  
Rice Yield ◽  
Oryza Sativa L ◽  
The United States ◽  
Growth Stages ◽  
Yield And Yield Components ◽  
Rice Yields ◽  
High Yields ◽  
Milling Yield

Establishing a uniform rice (Oryza sativa L.) stand is an important beginning to managing a rice crop and attaining high yields. Most rice management practices in the United States are timed according to rice growth stages. Non-uniform rice stands, and subsequently non-uniform growth stages, present problems for the timely application of management practices for attaining high yields. Our objective was the determination of the effects of uneven emergence on rice yield, milling yield, and yield components. Experiments were conducted in 1988 and 1989 on a Hebert silt loam (Vertic Hapludoll) at the Southeast Branch Experiment Station near Rohwer, Arkansas. Uneven emergence was simulated by delayed (18 days from emergence) interseeding of rice to achieve 0, 20, 40, 60, and 80% uneven emergence. Each experiment was planted with the cultivars Lemont (semi-dwarf) and Tebonnet (tall) and was replicated 4 times. Rice yields for the uneven emergence treatment levels were significantly less than the rice yields seeded exclusively at PD1 (planting date 1), except for the uneven emergence levels 80-20 (80% planted at PD1 and 20% planted at PD2) and 60-40 for Tebonnet, and 60-40 in 1988 for Lemont. In 1989, there was a trend for head rice yields to decrease as uneven emergence levels increased. Average panicle density and number of grains per panicle for both Lemont and Tebonnet decreased with increasing uneven emergence, indicating a failure in the typical compensatory relationship between panicle density and grain per panicle. Lemont exhibited reduced average grain weights due to uneven emergence, especially at 80-20, 60-40, and 40-60 uneven emergence levels. Harvest indices were higher for PD1 than for PD2, except at 20-80 uneven emergence level. Essentially, the later emerging rice from the second planting acted much like a weed by competing against rather than contributing to rice yields. Late interseeding to enhance poor rice stands is unlikely to produce an economic return that could be expected from an adequate initial plant stand.

scholarly journals Forecasting of Kharif Rice and Jute Yield in North Bengal through Statistical Model

2021 ◽  
pp. 60-65
Author(s):  
Kousik Nandi ◽  
Anwesh Rai ◽  
Soumen Mondal ◽  
Subhendu Bandyopadhyay ◽  
Deb Sankar Gupta
Keyword(s):  
Statistical Model ◽  
Crop Yield ◽  
Climate Change Scenario ◽  
Rice Yield ◽  
State Level ◽  
Change Scenario ◽  
Yield Prediction ◽  
Yield Forecast ◽  
Crop Yield Forecasting ◽  
North Bengal

Crop yield forecasting under the present climate change scenario needs an effective model and its parameter that how crop respond to the weather variable. A number of weather based models have been developed to estimate the crop yield for the various crops at block, district and state level. Among the different model statistical model is more popular and commonly used. The current study was undertaken to evaluate the performance of statistical model for rice and jute yield forecast of four different district viz. Cooch Behar, Jalpaiguri, Uttar Dinajpurand and Dakhin Dinajpur. Among the four districts Cooch Behar district found superior for kharif rice yield prediction (1.46% error with RMSE 177.68 kg/ha) whereas in case of jute crop its performance was the best in the Jalpaiguri district (-0.44% error with RMSE 217.50 kg/ha).

scholarly journals Trass Effect as a Source of Silicon on Soil, Hay, Husk and Growth of Rice Plants

2021 ◽  
Vol 232 ◽  
pp. 03022
Author(s):  
Mirawanty Amin ◽  
Rahadian Adi Prasetyo ◽  
Chandra Padang
Keyword(s):  
Rice Yield ◽  
Natural Materials ◽  
Rice Plants ◽  
Rice Growth ◽  
Two Factors ◽  
Main Plot ◽  
Accumulator Plant

Silicon (Si) is one of the important things for rice growth. The importance of Si relates to increased rice yield, increased resistance to disease and resistance to falling. The rice is an accumulator plant of Si which requires Si for its growth. However, the Si in soil is continually decreased therefore the additional Si is needed intothe soil. Trass is one of the natural materials containing Ca and Si, therefore it can be used as a Si fertilizer. This study aims to determine levels of soil Si, straw, husk, and growth in rice. This research consisted of three types of soil, Oxisol, Inceptisol and Vertisol as the main plot and 7 doses of burnt fuel namely 0 (D0); 1.25 (D1); 2.5 (D2); 3.75 (D3); 5 (D4); 7.5 (D5); 10 (D6) g kg-1 of soil as subplots. The treatment which is using in this research is a combination of the two factors and repeated 3 times 63 unit experiments were obtained. The results showed the Trass significant concerning to Si in the husk and Si of the soil. Vertisol gives the highest number of panicles of 27 and Si in the straw of 12.75 mg kg-1.

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