Brassica carinata as an off-season crop in the southeastern USA: Determining optimum sowing dates based on climate risks and potential effects on summer crop yield

2022 ◽  
Vol 196 ◽  
pp. 103344
Author(s):  
Rogério de Souza Nóia Júnior ◽  
Clyde W. Fraisse ◽  
Mahesh Bashyal ◽  
Michael J. Mulvaney ◽  
Ramdeo Seepaul ◽  
...  
Keyword(s):  
Crop Yield ◽  
Brassica Carinata ◽  
Southeastern Usa ◽  
Climate Risks ◽  
Sowing Dates ◽  
Summer Crop

scholarly journals Relationships between primary production and crop yields in semi-arid and arid irrigated agro-ecosystems

2015 ◽  
Vol XL-7/W3 ◽  
pp. 27-30 ◽  
Author(s):  
H. H. Jaafar ◽  
F. A. Ahmad
Keyword(s):  
Primary Production ◽  
Crop Yield ◽  
Vegetation Index ◽  
Crop Yields ◽  
Gross Primary Production ◽  
Remotely Sensed ◽  
Early Assessment ◽  
Food Shortages ◽  
Semi Arid ◽  
Summer Crop

In semi-arid areas within the MENA region, food security problems are the main problematic imposed. Remote sensing can be a promising too early diagnose food shortages and further prevent the population from famine risks. This study is aimed at examining the possibility of forecasting yield before harvest from remotely sensed MODIS-derived Enhanced Vegetation Index (EVI), Net photosynthesis (net PSN), and Gross Primary Production (GPP) in semi-arid and arid irrigated agro-ecosystems within the conflict affected country of Syria. Relationships between summer yield and remotely sensed indices were derived and analyzed. Simple regression spatially-based models were developed to predict summer crop production. The validation of these models was tested during conflict years. A significant correlation (p<0.05) was found between summer crop yield and EVI, GPP and net PSN. Results indicate the efficiency of remotely sensed-based models in predicting summer yield, mostly for cotton yields and vegetables. Cumulative summer EVI-based model can predict summer crop yield during crisis period, with deviation less than 20% where vegetables are the major yield. This approach prompts to an early assessment of food shortages and lead to a real time management and decision making, especially in periods of crisis such as wars and drought.

Weed Community as an Indicator of Summer Crop Yield and Site Quality

2001 ◽  
Vol 93 (3) ◽  
pp. 524-530 ◽  
Author(s):  
Susana A. Suárez ◽  
Elba B. Fuente ◽  
Claudio M. Ghersa ◽  
Rolando J.C. León
Keyword(s):  
Crop Yield ◽  
Site Quality ◽  
Summer Crop

scholarly journals Intensification of an irrigated rice system in Senegal: Crop rotations, climate risks, sowing dates and varietal adaptation options

2016 ◽  
Vol 80 ◽  
pp. 168-181 ◽  
Author(s):  
P.A.J. van Oort ◽  
A. Balde ◽  
M. Diagne ◽  
M. Dingkuhn ◽  
B. Manneh ◽  
...  
Keyword(s):  
Crop Rotations ◽  
Irrigated Rice ◽  
Climate Risks ◽  
Sowing Dates ◽  
Adaptation Options

scholarly journals Application of DSSAT CERES-Maize to Identify the Optimum Irrigation Management and Sowing Dates on Improving Maize Yield in Northern China

Agronomy ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 674
Author(s):  
Patrick Rugira ◽  
Juanjuan Ma ◽  
Lijian Zheng ◽  
Chaobao Wu ◽  
Enke Liu
Keyword(s):  
Water Use ◽  
Crop Yield ◽  
Irrigation Water ◽  
Aboveground Biomass ◽  
Irrigation Management ◽  
Irrigation Treatment ◽  
Simulated Data ◽  
Northern China ◽  
Area Index ◽  
Sowing Dates

The increase in irrigated maize plantings in Northern China has increased the demand for irrigation water in the region, resulting in chronic water shortages in drier years. Efficient irrigation and water use are essential for the sustainable development and management of water resources in the area. This research applied DSSAT-maize in the Loess Plateau (Fenhe basin) to determine the suitable irrigation management and optimum sowing dates to ensure the stability of spring maize production. The model was calibrated using the full irrigation treatment of 2017–2019 growing seasons. Crop data, such as plant phenological phases, aboveground biomass, crop yield, and leaf area index, were used for model calibration. The calibration showed great consistency between the measured and simulated data, with nRMSE (normalized root mean square error) ranging from 0.77% to 21.6%. The field values of crop yield, aboveground biomass, LAI, soil water content, and water use efficiency were used to evaluate the calibrated model’s performance, the model evaluation was found to be satisfactory with acceptable nRMSE ranging from 1.9% to 25.3%. Optimum simulated sowing dates for increased productivity and water efficiency were between 15 and 25 May. The optimum irrigation timing and volume of irrigation water application were 85 mm at the tasseling phase and 85 mm at the grouting phase respectively. Therefore, the yield of maize can be increased by applying irrigation and altering the sowing date in case rainfall is insufficient to satisfy the water demand of the crops in the Fenhe basin.

Productivity of oilseed flax seeds at different sowing dates and seeding rates in the Leningrad region

2020 ◽  
Author(s):  
M.A. Nosevich ◽  
Keyword(s):  
Seed Germination ◽  
Crop Yield ◽  
Seed Yield ◽  
Seed Weight ◽  
Leningrad Region ◽  
Sowing Dates ◽  
Flax Seeds ◽  
Sowing Seed ◽  
Sowing Period ◽  
Sum Of Active Temperatures

Аn increase in the accumulation of the sum of active temperatures for each subsequent sowing period of oilseed flax contributes to an increase in field seed germination from 64-74 to 83-84%. At optimally early terms of flax sowing seed weight from each plant are higher by 20-50% than at later terms of sowing, which significantly affects the crop yield. The sowing oilseed flax of the LM 98 variety at the beginning of the first decade of May with rate of 8.0 million units/ha in the conditions of the Leningrad region, it is possible to form a crop seed yield of 3.5 t / ha, which is 3-35% higher compared to subsequent sowing periods.

ENSO classification indices and summer crop yields in the Southeastern USA

2011 ◽  
Vol 151 (7) ◽  
pp. 817-826 ◽  
Author(s):  
Frederick S. Royce ◽  
Clyde W. Fraisse ◽  
Guillermo A. Baigorria
Keyword(s):  
Crop Yields ◽  
Southeastern Usa ◽  
Summer Crop

scholarly journals New agroclimatic approach for soybean sowing dates recommendation: A case study

2014 ◽  
Vol 18 (11) ◽  
pp. 1149-1156 ◽  
Author(s):  
Rafael Battisti ◽  
Paulo C. Sentelhas
Keyword(s):  
Crop Yield ◽  
Air Temperature ◽  
Production Cost ◽  
Sowing Date ◽  
Climatic Conditions ◽  
Accurate Information ◽  
Zone Model ◽  
New Approach ◽  
Sowing Dates ◽  
Actual Yield

The objective of this study was to introduce a new approach to recommend sowing dates for soybean crop in Brazil, considering the climatic conditions and crop yield. The first step was to define the periods when air temperature is smaller than 40 °C and greater than 1 °C in at least 80% of the years, and with at least 60% of relative crop evapotranspiration during the establishment phase in more than 50% of the years. The actual yield of crop was estimated by FAO Agroecological zone model for the suitable sowing dates. Based on that, when actual yield overcome the production cost in more than 80% of years and mean air temperature along the cycle is between 20 and 30 °C, the sowing date is classified as suitable, but if actual yield overcome the production cost only between 60 and 80% of the years or mean air temperature is not between 20 and 30 °C, the date is classified as marginal. Sowing dates are considered as unsuitable if actual crop yield overcome the production cost in less than 60% of the years. The new approach was applied, as case studies, for Cruz Alta, RS, Jataí, GO, and Balsas, MA, in order to compare it with the agroclimatic zoning approach presently used in Brazil. The new procedures can generate more accurate information to support sowing dates recommendation for soybean, minimizing yield losses from climatic risk.

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