Evaluating maize yield response to fertilizer and soil in Mexico using ground and satellite approaches

2022 ◽  
Vol 276 ◽  
pp. 108393
Author(s):  
Jake Campolo ◽  
Ivan Ortiz-Monasterio ◽  
David Guerena ◽  
David B. Lobell
Keyword(s):  
2018 ◽  
Vol 256-257 ◽  
pp. 242-252 ◽  
Author(s):  
Elizabeth K. Carter ◽  
Jeff Melkonian ◽  
Scott Steinschneider ◽  
Susan J. Riha

2019 ◽  
Vol 7 (2) ◽  
pp. 11
Author(s):  
Ebrima Sonko ◽  
Sampson K. Agodzo ◽  
Philip Antwi-Agyei

Climate change and variability impact on staple food crops present a daunting challenge in the 21st century. The study assesses future climate variability on maize and rice yield over a 30-year period by comparing the outcomes under two GCM models, namely, CSIRO_RCP4.5 and NOAA_RCP4.5 of Australia’s Commonwealth Scientific and National Oceanic and Atmospheric Administration respectively. Historical climate data and yield data were used to establish correlations and then subsequently used to project future yields between 2021 and 2050. Using the average yield data for the period 1987-2016 as baseline yield data, future yield predictions for 2021-2030, 2031-2040 and 2041-2050 were then compared with the baseline data. The results showed that the future maize and rice yield would be vulnerable to climate variability with CSIRO_RCP4.5 showing increase in maize yield whilst CSIRO_RCP4.5 gives a better projection for rice yield. Furthermore, the results estimated the percentage mean yield gain for maize under CSIRO_RCP4.5 and NOAA_ RCP4.5 by about 17 %, 31 % and 48 % for the period 2021-2030, 2031-2040 and 2041-2050 respectively. Mean rice yield lossess of -23 %, -19 % and -23 % were expected for the same period respectively. The study recommended the use of improved rice and maize cultivars to offset the negative effects of climate variability in future.


2019 ◽  
Vol 09 (01) ◽  
Author(s):  
Waqar Ali ◽  
Mukhtiar Ali ◽  
Abid Kamal ◽  
Muhammad Uzair ◽  
Nasr Ullah ◽  
...  

2018 ◽  
Vol 223 ◽  
pp. 113-124 ◽  
Author(s):  
Onesmus M. Kitonyo ◽  
Victor O. Sadras ◽  
Yi Zhou ◽  
Matthew D. Denton

2020 ◽  
Vol 51 (6) ◽  
pp. 923-940 ◽  
Author(s):  
William J. Burke ◽  
Sieglinde S. Snapp ◽  
Thom S. Jayne
Keyword(s):  

2012 ◽  
Vol 49 (1) ◽  
pp. 3-18 ◽  
Author(s):  
E. RUTTO ◽  
J. P. VOSSENKEMPER ◽  
J. KELLY ◽  
B. K. CHIM ◽  
W. R. RAUN

SUMMARYCorrect placement of side dress nitrogen (N) fertilizer could increase nitrogen use efficiency (NUE) and maize yield production. Field studies were established to evaluate application of midseason (V8 to V10), variable liquid urea ammonia nitrate (28%), N rates (0, 45, 90 and 134 kg N ha−1) and different application distances (0, 10, 20 and 30 cm) away from the maize row on grain yield and NUE at Haskell and Hennessey in 2009, Efaw in 2010 and Lake Carl Blackwell, Oklahoma in 2009 and 2010. A randomized complete block design with three replications was used throughout the study. Results indicated that maize grain yield in sites with adequate rainfall increased significantly (p < 0.05) with N rate, and poor N response was recorded in sites with low rainfall. Across sites and seasons, varying side dress N application distance away from the maize row did not significantly (p < 0.05) influence maize grain yield and NUE even with no prep-plant applied. Environments with adequate rainfall distribution had better maize grain yields when high side dress N rates (90 and 134 kg N ha−1) were applied 0 to 10 cm, and a higher NUE when 45 kg N ha−1 was applied 0 to 20 cm away from the maize row. For low N rates (45 kg N ha−1), increased maize grain yield and NUE were achieved when side dress N was applied 0 to 20 cm away from the maize row at locations with low rainfall distribution. Across sites and seasons, increasing side dress N to 134 kg N ha−1 contributed to a general decline in mean NUE to as low as 4%, 35%, 10%, 51% at Hennessey, Efaw, LCB (2009) and LCB (2010) respectively.


Food Security ◽  
2017 ◽  
Vol 9 (3) ◽  
pp. 577-593 ◽  
Author(s):  
Bashir Jama ◽  
David Kimani ◽  
Rebbie Harawa ◽  
Abednego Kiwia Mavuthu ◽  
Gudeta W. Sileshi

2015 ◽  
Vol 54 (4) ◽  
pp. 785-794 ◽  
Author(s):  
Yi Zhang ◽  
Yanxia Zhao ◽  
Sining Chen ◽  
Jianping Guo ◽  
Enli Wang

AbstractProjections of climate change impacts on crop yields are subject to uncertainties, and quantification of such uncertainty is essential for the effective use of the projection results for adaptation and mitigation purposes. This work analyzes the uncertainties in maize yield predictions using two crop models together with three climate projections downscaled with one regional climate model nested with three global climate models under the A1B emission scenario in northeast China (NEC). Projections were evaluated for the Zhuanghe agrometeorological station in NEC for the 2021–50 period, taking 1971–2000 as the baseline period. The results indicated a yield reduction of 13% during 2021–50, with 95% probability intervals of (−41%, +12%) relative to 1971–2000. Variance decomposition of the yield projections showed that uncertainty in the projections caused by climate and crop models is likely to change with prediction period, and climate change uncertainty generally had a larger impact on projections than did crop model uncertainty during the 2021–50 period. In addition, downscaled climate projections had significant bias that can introduce significant uncertainties in yield projections. Therefore, they have to be bias corrected before use.


Sign in / Sign up

Export Citation Format

Share Document