Is Site‐Specific Yield Response Consistent over Time? Does It Pay?

2006 ◽  
Vol 88 (2) ◽  
pp. 471-483 ◽  
Author(s):  
Yanyan Liu ◽  
Scott M. Swinton ◽  
Neil R. Miller
Keyword(s):  
Specific Yield ◽  
Yield Response ◽  
Site Specific ◽  
Over Time

scholarly journals Adding value to spatially managed inputs by understanding site-specific yield response

2002 ◽  
Vol 27 (3) ◽  
pp. 233-245 ◽  
Author(s):  
David S. Bullock ◽  
Jess Lowenberg-DeBoer ◽  
Scott M. Swinton
Keyword(s):  
Specific Yield ◽  
Yield Response ◽  
Site Specific

Site-Specific Covariates Affecting Yield Response to Nitrogen of Late-Sown Maize in Central Argentina

2018 ◽  
Vol 110 (4) ◽  
pp. 1544-1553 ◽  
Author(s):  
Tomás Coyos ◽  
Lucas Borrás ◽  
Brenda L. Gambin
Keyword(s):  
Yield Response ◽  
Site Specific ◽  
Central Argentina

Site-specific yield for forages

1999 ◽  
Vol 21 (2) ◽  
pp. 120
Author(s):  
Jeffrey A. Behme ◽  
Jack L. Schinstock ◽  
Leonard L. Bashford ◽  
Louis I. Leviticus
Keyword(s):  
Specific Yield ◽  
Site Specific

Using yield maps and intensive soil sampling to improve nitrogen fertiliser recommendations from a deterministic model in the Western Australian wheatbelt

2000 ◽  
Vol 40 (7) ◽  
pp. 959 ◽  
Author(s):  
M. L. Adams ◽  
S. Cook ◽  
J. W. Bowden
Keyword(s):  
Prediction Accuracy ◽  
Deterministic Model ◽  
Yield Response ◽  
Specific Information ◽  
Sources Of Information ◽  
Site Specific ◽  
Nitrogen Fertiliser ◽  
Specific Variation ◽  
Scale Experiment ◽  
Western Australian

A field-scale experiment was conducted to determine the ability of a deterministic model developed for Western Australian wheat farmers to guide site-specific applications of nitrogen fertiliser. The results indicated that site-specific information of achievable yield improved the prediction accuracy much more than information about soil nitrogen — even though the latter was more costly to acquire. When applied together, these sources of information improved the prediction accuracy of the model markedly, explaining about half of the variation of yield response to nitrogen. However, the model failed to explain a substantial portion of site-specific variation, even with this intensity of information. This failure indicates the difficulty of representing complex biological systems with simple functional models.

scholarly journals Systematic analysis of site-specific yield distributions resulting from nitrogen management and climatic variability interactions

2014 ◽  
Vol 16 (4) ◽  
pp. 361-384 ◽  
Author(s):  
Benjamin Dumont ◽  
Bruno Basso ◽  
Vincent Leemans ◽  
Bernard Bodson ◽  
Jean-Pierre Destain ◽  
...  
Keyword(s):  
Climatic Variability ◽  
Nitrogen Management ◽  
Specific Yield ◽  
Systematic Analysis ◽  
Site Specific

scholarly journals Treatment complexity in cystic fibrosis: Trends over time and associations with site-specific outcomes

2013 ◽  
Vol 12 (5) ◽  
pp. 461-467 ◽  
Author(s):  
Gregory S. Sawicki ◽  
Clement L. Ren ◽  
Michael W. Konstan ◽  
Stefanie J. Millar ◽  
David J. Pasta ◽  
...  
Keyword(s):  
Cystic Fibrosis ◽  
Site Specific ◽  
Trends Over Time ◽  
Treatment Complexity ◽  
Over Time

STATISTICAL AND NEURAL METHODS FOR SITE–SPECIFIC YIELD PREDICTION

2003 ◽  
Vol 46 (1) ◽  
Author(s):  
S. T. Drummond ◽  
K. A. Sudduth ◽  
A. Joshi ◽  
S. J. Birrell ◽  
N. R. Kitchen
Keyword(s):  
Specific Yield ◽  
Yield Prediction ◽  
Site Specific

scholarly journals Farmers’ Participatory Site Specific Nutrient Management in Gangetic Tidal Floodplain Soil for High Yielding Boro Rice (Oryza Sativa L.)

2013 ◽  
Vol 11 (1) ◽  
pp. 8-14 ◽  
Author(s):  
DK Nath ◽  
F Haque ◽  
F Amin ◽  
M Sh Islam ◽  
MA Saleque
Keyword(s):  
Oryza Sativa ◽  
Nutrient Management ◽  
Oryza Sativa L ◽  
Block Design ◽  
Yield Response ◽  
Management Approach ◽  
Nitrogen And Phosphorus ◽  
Floodplain Soil ◽  
Site Specific ◽  
A Site

Site Specific Nutrient Management (SSNM) trials were conducted for irrigated, transplanted and high yielding rice (Oryza sativa L.) during Boro season 2012. Four treatments (NPK, PK, NK, and NP) were applied in a randomized complete block design to assess the effects of indigenous nutrient elements on rice yield and yield components. The trials were conducted so as to develop a site specific nutrient management approach for the farmers of Gangtic Tidal Floodplain ecosystem. The highest grain-yield of 5.64 t ha-1 was observed in NPK treatment, which gave 9.0, 34.4 and 50.7% higher yields than those of NP, NK and PK, respectively. The response to indigenous K was remarkable and it gave the second highest yield (5.13 t ha-1). The yield response to indigenous N was very poor and the lowest yield was found in N omission treatment (2.78 t ha-1). The response to indigenous P was also poor (3.7 t ha-1). This result shows that nitrogen and phosphorus are the most vibrant factors to increase yield since omission of N and P had significant impact on yield during Boro season. Use of N, P and K at 128.7, 8.08 and 12.78 kg, respectively could be recommended for growing BRRI dhan47 in Boro season. It could save P and K nutrient by 55.11 and 75.89 % compared to that of NPK treatment, respectively. DOI: http://dx.doi.org/10.3329/agric.v11i1.15236 The Agriculturists 2013; 11(1) 8-14

scholarly journals Impacts of Spatial Zonation Schemes on Yield Potential Estimates at the Regional Scale

Agronomy ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 631 ◽  
Author(s):  
Hao Xu ◽  
Fen Huang ◽  
Wenjun Zuo ◽  
Yongchao Tian ◽  
Yan Zhu ◽  
...  
Keyword(s):  
Growth Models ◽  
Sunshine Duration ◽  
Regional Scale ◽  
Crop Growth ◽  
Yield Potential ◽  
Specific Yield ◽  
Site Specific ◽  
Spatial Zonation ◽  
Simulation Results ◽  
Crop Growth Models

Simulations based on site-specific crop growth models have been widely used to obtain regional yield potential estimates for food security assessments at the regional scale. By dividing a region into nonoverlapping basic spatial units using appropriate zonation schemes, the data required to run a crop growth model can be reduced, thereby improving the simulation efficiency. In this study, we explored the impacts of different zonation schemes on estimating the regional yield potential of the Chinese winter wheat area to obtain the most appropriate spatial zonation scheme of weather sites therein. Our simulated results suggest that the upscaled site-specific yield potential is affected by the zonation scheme and by the spatial distribution of sites. As such, the distribution of a small number of sites significantly affected the simulated regional yield potential under different zonation schemes, and the zonation scheme based on sunshine duration clustering zones could effectively guarantee the simulation accuracy at the regional scale. Using the most influential environmental variable of crop growth models for clustering can get the better zonation scheme to upscale the site-specific simulation results. In contrast, a large number of sites had little effect on the regional yield potential simulation results under the different zonation schemes.

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