Physiological Processes Associated with Winter Wheat Yield Potential Progress

2007 ◽  
pp. 591-597 ◽  
Author(s):  
M. J. Foulkes ◽  
J. W. Snape ◽  
V. J. Shearman ◽  
R. Sylvester-Bradley
Keyword(s):  
Winter Wheat ◽  
Wheat Yield ◽  
Yield Potential ◽  
Physiological Processes ◽  
Winter Wheat Yield

Increasing Hard Winter Wheat Yield Potential via Synthetic Wheat: I. Path-Coefficient Analysis of Yield and Its Components

Crop Science ◽  
2012 ◽  
Vol 52 (5) ◽  
pp. 2014-2022 ◽  
Author(s):  
Jessica K. Cooper ◽  
A.M.H. Ibrahim ◽  
J. Rudd ◽  
Subas Malla ◽  
Dirk B. Hays ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Wheat Yield ◽  
Yield Potential ◽  
Path Coefficient ◽  
Path Coefficient Analysis ◽  
Synthetic Wheat ◽  
Winter Wheat Yield

Comparing a random forest based prediction of winter wheat yield to historical production potential

2020 ◽  
Author(s):  
Yannik Roell ◽  
Amélie Beucher ◽  
Per Møller ◽  
Mette Greve ◽  
Mogens Greve
Keyword(s):  
Random Forest ◽  
Winter Wheat ◽  
Wheat Yield ◽  
Yield Potential ◽  
Production Potential ◽  
Yield Model ◽  
Spatiotemporal Trends ◽  
Winter Wheat Yield ◽  
Historical Production ◽  
Yield Map

<p>Predicting wheat yield is crucial due to the importance of wheat across the world. When modeling yield, the difference between potential and actual yield consistently changes because of technology. Considering historical yield potential would help determine spatiotemporal trends in agricultural development. Comparing current and historical production in Denmark is possible because production has been documented throughout history. However, the current winter wheat yield model is solely based on soil. The aim of this study was to generate a new Danish winter wheat yield map and compare the results to historical production potential. Utilizing random forest with soil, climate, and topography variables, a winter wheat yield map was generated from 876 field trials carried out from 1992 to 2018. The random forest model performed better than the model based only on soil. The updated national yield map was then compared to production potential maps from 1688 and 1844. While historical time periods are characterized by numerous low production potential areas and few highly productive areas, present-day production is evenly distributed between low and high production. Advances in technology and farm practices have exceeded historical yield predictions. Thus, modeling current yield could be unreliable in future years as technology progresses.</p>

The impact of variation in grain number and individual grain weight on winter wheat yield in the high yield potential environment of Ireland

2017 ◽  
Vol 87 ◽  
pp. 40-49 ◽  
Author(s):  
Joseph P. Lynch ◽  
Deirdre Doyle ◽  
Shauna McAuley ◽  
Fiona McHardy ◽  
Quentin Danneels ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Wheat Yield ◽  
Grain Weight ◽  
Yield Potential ◽  
High Yield ◽  
Grain Number ◽  
Winter Wheat Yield ◽  
The Impact ◽  
High Yield Potential

scholarly journals The Analysis of Wheat Yield Variability Based on Experimental Data from 2008–2018 to Understand the Yield Gap

Agriculture ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 32
Author(s):  
Elżbieta Wójcik-Gront ◽  
Marzena Iwańska ◽  
Agnieszka Wnuk ◽  
Tadeusz Oleksiak
Keyword(s):  
Winter Wheat ◽  
Plant Breeding ◽  
Management Practices ◽  
Wheat Yield ◽  
Yield Potential ◽  
Yield Variability ◽  
Mineral Fertilization ◽  
Yield Gap ◽  
Potential Yield ◽  
Winter Wheat Yield

Among European countries, Poland has the largest gap in the grain yield of winter wheat, and thus the greatest potential to reduce this yield gap. This paper aims to recognize the main reasons for winter wheat yield variability and shed the light on possible reasons for this gap. We used long-term datasets (2008–2018) from individual commercial farms obtained by the Laboratory of Economics of Seed and Plant Breeding of Plant Breeding and Acclimatization Institute (IHAR)-National Research Institute (Poland) and the experimental fields with high, close to potential yield, in the Polish Post-Registration Variety Testing System in multi-environmental trials. We took into account environment, management and genetic variables. Environment was considered through soil class representing soil fertility. For the crop management, the rates of mineral fertilization, the use of pesticides and the type of pre-crop were considered. Genotype was represented by the independent variable year of cultivar registration or year of starting its cultivation in Poland. The analysis was performed using the CART (Classification and Regression Trees). The winter wheat yield variability was mostly dependent on the amount of nitrogen fertilization applied, soil quality, and type of pre-crop. Genetic variable was also important, which means that plant breeding has successfully increased genetic yield potential especially during the last several years. In general, changes to management practices are needed to lower the variability of winter wheat yield and possibly to close the yield gap in Poland.

scholarly journals Assessment of water-limited winter wheat yield potential at spatially contrasting sites in Ireland using a simple growth and development model

2017 ◽  
Vol 56 (1) ◽  
pp. 65-76 ◽  
Author(s):  
J.P. Lynch ◽  
R. Fealy ◽  
D. Doyle ◽  
L. Black ◽  
J. Spink
Keyword(s):  
Winter Wheat ◽  
Growth And Development ◽  
Wheat Yield ◽  
Yield Potential ◽  
Weather Data ◽  
Minor Amount ◽  
Accurate Estimation ◽  
Area Index ◽  
Climatic Environment ◽  
Winter Wheat Yield

AbstractAlthough Irish winter wheat yields are among the highest globally, increases in the profitability of this crop are required to maintain its economic viability. However, in order to determine if efforts to further increase Irish wheat yields are likely to be successful, an accurate estimation of the yield potential is required for different regions within Ireland. A winter wheat yield potential model (WWYPM) was developed, which estimates the maximum water-limited yield achievable, within the confines of current genetic resources and technologies, using parameters for winter wheat growth and development observed recently in Ireland and a minor amount of daily meteorological input (maximum and minimum daily temperature, total daily rainfall and total daily incident radiation). The WWYPM is composed of three processes: (i) an estimation of potential green area index, (ii) an estimation of light interception and biomass accumulation and (iii) an estimation of biomass partitioning to grain yield. Model validation indicated that WWYPM estimations of water-limited yield potential (YPw) were significantly related to maximum yields recorded in variety evaluation trials as well as regional average and maximum farm yields, reflecting the model’s sensitivity to alterations in the climatic environment with spatial and seasonal variations. Simulations of YPw for long-term average weather data at 12 sites located at spatially contrasting regions of Ireland indicated that the typical YPw varied between 15.6 and 17.9 t/ha, with a mean of 16.7 t/ha at 15% moisture content. These results indicate that the majority of sites in Ireland have the potential to grow high-yielding crops of winter wheat when the effects of very high rainfall and other stresses such as disease incidence and nutrient deficits are not considered.

Increasing Hard Winter Wheat Yield Potential via Synthetic Hexaploid Wheat: II. Heritability and Combining Ability of Yield and its Components

Crop Science ◽  
2013 ◽  
Vol 53 (1) ◽  
pp. 67-73 ◽  
Author(s):  
Jessica K. Cooper ◽  
Amir M. H. Ibrahim ◽  
Jackie Rudd ◽  
Dirk Hays ◽  
Subas Malla ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Hexaploid Wheat ◽  
Combining Ability ◽  
Wheat Yield ◽  
Yield Potential ◽  
Synthetic Hexaploid Wheat ◽  
Winter Wheat Yield ◽  
Synthetic Hexaploid

scholarly journals Comparing a Random Forest Based Prediction of Winter Wheat Yield to Historical Yield Potential

Agronomy ◽  
2020 ◽  
Vol 10 (3) ◽  
pp. 395 ◽  
Author(s):  
Yannik E. Roell ◽  
Amélie Beucher ◽  
Per G. Møller ◽  
Mette B. Greve ◽  
Mogens H. Greve
Keyword(s):  
Random Forest ◽  
Winter Wheat ◽  
Agricultural Development ◽  
Wheat Yield ◽  
Field Trials ◽  
Yield Potential ◽  
Spatiotemporal Trends ◽  
Winter Wheat Yield ◽  
High Yields ◽  
Yield Map

Predicting wheat yield is crucial due to the importance of wheat across the world. When modeling yield, the difference between potential and actual yield consistently changes because of advances in technology. Considering historical yield potential would help determine spatiotemporal trends in agricultural development. Comparing current and historical yields in Denmark is possible because yield potential has been documented throughout history. However, the current national winter wheat yield map solely uses soil properties within the model. The aim of this study was to generate a new Danish winter wheat yield map and compare the results to historical yield potential. Utilizing random forest with soil, climate, and topography variables, a winter wheat yield map was generated from 876 field trials carried out from 1992 to 2018. The random forest model performed better than the model based only on soil. The updated national yield map was then compared to yield potential maps from 1688 and 1844. While historical time periods are characterized by numerous low yield potential areas and few highly productive areas, current yield is evenly distributed between low and high yields. Advances in technology and farm practices have exceeded historical yield predictions, mainly due to the use of fertilizer, irrigation, and drainage. Thus, modeling yield projections could be unreliable in the future as technology progresses.

scholarly journals Development of the methodology of estimating of agricultural crop yield potential with consideration of climate and agrophytotechnology impact

2017 ◽  
pp. 52-60
Author(s):  
V. P. Dmytrenko ◽  
L. P. Odnolyetok ◽  
О. О. Kryvoshein ◽  
A. V. Krukivska
Keyword(s):  
Winter Wheat ◽  
Crop Yield ◽  
Crop Yields ◽  
Wheat Yield ◽  
Yield Potential ◽  
Agricultural Crop ◽  
Yield Level ◽  
Winter Wheat Yield ◽  
The Mathematical Model

In the paper it is outlined the main methodological positions and the results of the approbation of new approaches to the integrated assessment of the potential of crop yields. There are considered the theoretical foundations of a joint assessment of the biological, ecological and anthropogenic components of the yield potential of agricultural crops which are based on the ecosystem concept and the mathematical model "Weather-Crop Yield" developed by V. P. Dmytrenko. In the considered approaches the peculiarities of the influence of various environmental factors on the formation of crop yields are determined by indicators of various potential yields -  general, climatic and trend (agrotechnological). Each type of yield potential can be used for evaluation of the effectiveness of the conditions of field crop growing for each factor taken into account, as well as the optimality criterion in the agrometeorological adaptation strategies and also as a criterion for the degree of sensitivity of the yield level to the conditions of crops cultivating. The developed approaches are tested on the example of estimation of long-term dynamics of winter wheat yield potential in Ukraine. According to the results of the evaluation of different factors of the potential of the productivity of winter wheat for the periods 1961-1990 and 1991-2010 the dominant importance of organizational and technological processes in comparison with the contribution of changes of agroclimatic conditions has been determined in both periods.

Effect of nitrogen top-dressing on winter wheat yield, quantity and quality

2005 ◽  
Vol 34 (2) ◽  
pp. 177-185 ◽  
Author(s):  
Zs. Szentpétery ◽  
Cs. Kleinheincz ◽  
G. Szöllősi ◽  
M. Jolánkai
Keyword(s):  
Winter Wheat ◽  
Wheat Yield ◽  
Winter Wheat Yield
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