WHEAT YIELDS FOR 50 YEARS AT SWIFT CURRENT, SASKATCHEWAN IN RELATION TO WEATHER

1974 ◽  
Vol 54 (4) ◽  
pp. 625-650 ◽  
Author(s):  
GEO. W. ROBERTSON
Keyword(s):  
Crop Production ◽  
Global Radiation ◽  
Wheat Yield ◽  
Triticum Aestivum L ◽  
Quadratic Functions ◽  
Weather Data ◽  
Temperature And Precipitation ◽  
Weather Model ◽  
Surveillance Programs ◽  
Crop Condition

Half a century of wheat yield and weather records at Swift Current in southwestern Saskatchewan were analyzed to determine the response of wheat (Triticum aestivum L.) to changing weather patterns. Weather at Swift Current has undergone subtle but significant changes over the past 50 yr. Earlier years had disturbed conditions: hot, dry periods alternating with cool, wet ones resulting in yield fluctuations ranging from crop failures to maximum values. More recently the weather has been quiet: dry and cool but less variable from year to year. The resulting conditions were more favorable for near-normal but less variable yields. Simple precipitation-based yield–weather models developed two decades ago no longer apply, because temperature and precipitation patterns are currently out of phase relative to earlier conditions. A factorial yield–weather model was used to explain the complex relationship. This involved the summation of the product of several quadratic functions of various weather elements. Those elements considered were precipitation, maximum and minimum temperatures, global radiation estimated from duration of bright sunshine, evaporation from a buried pan, and time as an indicator of advancing technology. One function contained a term for the antecedant crop condition. The most important elements were precipitation for the summer-fallow period and for May, June and August; maximum temperatures for June and July; and global radiation for May. Advances in technology would seem to have very little influence on wheat yield trends after weather trends were accounted for. The model accounted for 73% (r = 0.854) of the yield variability and provided realistic functions for explaining the curvilinear influence of individual weather elements on wheat yield. The model is of a form that is readily adaptable for assessing, at any time during the crop development period, the influence of past and current weather on future expected yield. This could be useful for interpreting weather data in terms of crop production in weather and crop condition surveillance programs.

scholarly journals Comparison of Lasso and stepwise regression technique for wheat yield prediction

2021 ◽  
Vol 21 (2) ◽  
pp. 188-192
Author(s):  
SUDHEER KUMAR ◽  
S.D. ATTRI ◽  
K.K. SINGH
Keyword(s):  
Crop Production ◽  
Stepwise Regression ◽  
Wheat Yield ◽  
Forecast Model ◽  
Regression Technique ◽  
Weather Data ◽  
Prediction Errors ◽  
Lasso Regression ◽  
Statistical Parameters ◽  
Forecast Models

Multiple regression approach has been used to forecast the crop production widely. This study has been undertaken to evaluate the performance of stepwise and Lasso (Least absolute shrinkage and selection operator) regression technique in variable selection and development of wheat forecast model for crop yield using weather data and wheat yield for the period of 1984-2015, collected from IARI, New Delhi. Statistical parameters viz. R2, RMSE, and MAPE were 0.81, 195.90 and 4.54 per cent respectively with stepwise regression and 0.95, 99.27, 2.7 percentage, respectively with Lasso regression. Forecast models were validated during 2013-14 and 2014-15. Prediction errors were -8.5 and 10.14 per cent with stepwise and 1.89 and 1.64 percent with the Lasso. This shows that performance of Lasso regression is better than stepwise regression to some extent.

scholarly journals Effect of warming temperatures on US wheat yields

2015 ◽  
Vol 112 (22) ◽  
pp. 6931-6936 ◽  
Author(s):  
Jesse Tack ◽  
Andrew Barkley ◽  
Lawton Lanier Nalley
Keyword(s):  
Crop Production ◽  
Wheat Variety ◽  
Wheat Yield ◽  
Predictive Performance ◽  
Extreme Heat ◽  
Weather Data ◽  
Effect Of Temperature ◽  
Data Set ◽  
Freezing Temperatures ◽  
Temperature Exposure

Climate change is expected to increase future temperatures, potentially resulting in reduced crop production in many key production regions. Research quantifying the complex relationship between weather variables and wheat yields is rapidly growing, and recent advances have used a variety of model specifications that differ in how temperature data are included in the statistical yield equation. A unique data set that combines Kansas wheat variety field trial outcomes for 1985–2013 with location-specific weather data is used to analyze the effect of weather on wheat yield using regression analysis. Our results indicate that the effect of temperature exposure varies across the September−May growing season. The largest drivers of yield loss are freezing temperatures in the Fall and extreme heat events in the Spring. We also find that the overall effect of warming on yields is negative, even after accounting for the benefits of reduced exposure to freezing temperatures. Our analysis indicates that there exists a tradeoff between average (mean) yield and ability to resist extreme heat across varieties. More-recently released varieties are less able to resist heat than older lines. Our results also indicate that warming effects would be partially offset by increased rainfall in the Spring. Finally, we find that the method used to construct measures of temperature exposure matters for both the predictive performance of the regression model and the forecasted warming impacts on yields.

Crop rotations compared with continuous canola and wheat for crop production and fertilizer use over 6 yr

2018 ◽  
Vol 98 (5) ◽  
pp. 1139-1149 ◽  
Author(s):  
Kabal S. Gill
Keyword(s):  
Crop Production ◽  
Wheat Yield ◽  
Weather Conditions ◽  
Triticum Aestivum L ◽  
Continuous Cropping ◽  
Hordeum Vulgare L ◽  
Brassica Napus L ◽  
Fertilizer Use ◽  
Linum Usitatissimum L ◽  
Pisum Sativum L

Local economic, logistic, soil, and weather conditions have made appropriate rotations vary from one area to another. Seed yield and fertilizer use in rotations were compared with continuous cropping for 6 yr in the southeast Peace region of Alberta, Canada. Canola (C) (Brassica napus L.), wheat (W) (Triticum aestivum L.), pea (P) (Pisum sativum L.), barley (B) (Hordeum vulgare L.), and flax (F) (Linum usitatissimum L.) were grown in 12 treatments [i.e., continuous canola (CC) and wheat (WW) and rotations of W–C, P–W–W, C–W–W, C–C–W, P–C–W, C–P–W, W–B–C, B–W–C, F–W–C, and F–C–W]. Canola yield increased with 1 or 2 yr breaks from canola. Within rotations, there was a trend to lower canola yield on canola stubble compared with other crop stubbles. Wheat yield was generally lower in WW than in rotations. Among rotations, wheat yield tended to be greater on pea stubble compared with canola, wheat, barley, and flax stubbles. Averaged over 2010–2015, the canola yield benefit from rotations was 0.632 Mg ha−1 (19.4%) over CC and the wheat yield benefit from rotations was 0.313 Mg ha−1 (7.2%) over WW. Nitrogen saving was observed when pea was included in rotation.

scholarly journals Seeding Rate Effects on Hybrid Spring Wheat Yield, Yield Components and Quality

Agronomy ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1240
Author(s):  
Peder K. Schmitz ◽  
Joel K. Ransom
Keyword(s):  
Spring Wheat ◽  
Yield Components ◽  
Wheat Yield ◽  
Triticum Aestivum L ◽  
Yield Component ◽  
Economic Feasibility ◽  
Protein Yield ◽  
Seeding Rate ◽  
Hard Red Spring Wheat ◽  
End Use

Agronomic practices, such as planting date, seeding rate, and genotype, commonly influence hard red spring wheat (HRSW, Triticum aestivum L. emend. Thell.) production. Determining the agronomic optimum seeding rate (AOSR) of newly developed hybrids is needed as they respond to seeding rates differently from inbred cultivars. The objectives of this research were to determine the AOSR of new HRSW hybrids, how seeding rate alters their various yield components, and whether hybrids offer increased end-use quality, compared to conventional cultivars. The performance of two cultivars (inbreds) and five hybrids was evaluated in nine North Dakota environments at five seeding rates in 2019−2020. Responses to seeding rate for yield and protein yield differed among the genotypes. The AOSR ranged from 3.60 to 5.19 million seeds ha−1 and 2.22 to 3.89 million seeds ha−1 for yield and protein yield, respectively. The average AOSR for yield for the hybrids was similar to that of conventional cultivars. However, the maximum protein yield of the hybrids was achieved at 0.50 million seeds ha−1 less than that of the cultivars tested. The yield component that explained the greatest proportion of differences in yield as seeding rates varied was kernels spike−1 (r = 0.17 to 0.43). The end-use quality of the hybrids tested was not superior to that of the conventional cultivars, indicating that yield will likely be the determinant of the economic feasibility of any future released hybrids.

scholarly journals Fungicide Application Affects Nitrogen Utilization Efficiency, Grain Yield, and Quality of Winter Wheat

Agronomy ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1295
Author(s):  
Ahossi Patrice Koua ◽  
Mirza Majid Baig ◽  
Benedict Chijioke Oyiga ◽  
Jens Léon ◽  
Agim Ballvora
Keyword(s):  
Synergistic Effect ◽  
Grain Yield ◽  
Crop Production ◽  
Agronomic Traits ◽  
Yellow Rust ◽  
Wheat Yield ◽  
Utilization Efficiency ◽  
High Nitrogen ◽  
Available N ◽  
Fungicide Application

Nitrogen (N) is a vital component of crop production. Wheat yield varies significantly under different soil available N. Knowing how wheat responds to or interacts with N to produce grains is essential in the selection of N use efficient cultivars. We assessed in this study variations among wheat genotypes for productivity-related traits under three cropping systems (CS), high-nitrogen with fungicide (HN-WF), high-nitrogen without fungicide (HN-NF) and low-nitrogen without fungicide (LN-NF) in the 2015, 2016 and 2017 seasons. ANOVA results showed genotypes, CS, and their interactions significantly affected agronomic traits. Grain yield (GY) increased with higher leaf chlorophyll content, importantly under CS without N and fungicide supply. Yellow rust disease reduced the GY by 20% and 28% in 2015 and 2016, respectively. Moreover, averaged over growing seasons, GY was increased by 23.78% under CS with N supply, while it was greatly increased, by 52.84%, under CS with both N and fungicide application, indicating a synergistic effect of N and fungicide on GY. Fungicide supply greatly improved the crop ability to accumulate N during grain filling, and hence the grain protein content. Recently released cultivars outperformed the older ones in most agronomic traits including GY. Genotype performance and stability analysis for GY production showed differences in their stability levels under the three CS. The synergistic effect of nitrogen and fungicide on grain yield (GY) and the differences in yield stability levels of recently released wheat cultivars across three CS found in this study suggest that resource use efficiency can be improved via cultivar selection for targeted CS.

Participatory soil quality assessment: The case of smallholder farmers in Ethiopian highlands

Soil Research ◽  
2004 ◽  
Vol 42 (7) ◽  
pp. 793 ◽  
Author(s):  
Teklu Erkossa ◽  
Karl Stahr ◽  
Thomas Gaiser
Keyword(s):  
Quality Assessment ◽  
Soil Quality ◽  
Crop Production ◽  
Smallholder Farmers ◽  
Soil Management ◽  
Triticum Aestivum L ◽  
Soil Functions ◽  
Yield Data ◽  
Management Interventions ◽  
Soil Quality Assessment

The study was conducted at Caffee Doonsa (08°88′N, 39°08′E; 2400 m asl), a small watershed in the central highlands of Ethiopia, in order to identify farmers’ goals of soil management and the indicators they use in selecting soils for a certain function, and to categorise the soils in different quality groups with respect to the major functions. Thirty-six male farmers of different age and wealth groups participated in a Participatory Rural Appraisal technique. They listed and prioritised 12 soil functions in the area and itemised the soil quality indicators (characteristics). Based on the indicators, the soils in the watershed were classified into 3 soil quality (SQ) groups (Abolse, Kooticha, and Carii). The SQ groups have been evaluated and ranked for the major soil functions. For crop production, Abolse was graded best, followed by Kooticha and Carii, respectively. The grain and straw yield data of wheat (Triticum aestivum L.) taken from the SQ groups confirmed the farmers claim, in that Abolse gave the highest grain yield (4573 kg/ha), followed by 4411 and 3657 kg/ha for Kooticha and Carii, respectively. Local insights should be included in systematic soil quality assessment, and in planning and implementation of various soil management interventions.

Nitrogen form, time and rate of application, and nitrification inhibitor effects on crop production

2014 ◽  
Vol 94 (2) ◽  
pp. 425-432 ◽  
Author(s):  
R. E. Karamanos ◽  
K. Hanson ◽  
F. C. Stevenson
Keyword(s):  
Crop Production ◽  
Protein Concentration ◽  
Wheat Yield ◽  
Nitrification Inhibitor ◽  
N Fertilizer ◽  
Nitrogen Form ◽  
Anhydrous Ammonia ◽  
N Concentration ◽  
Fertilizer Rates ◽  
Better Than

Karamanos, R., Hanson, K. and Stevenson, F. C. 2014. Nitrogen form, time and rate of application, and nitrification inhibitor effects on crop production. Can. J. Plant Sci. 94: 425–432. Nitrogen management options for anhydrous ammonia (NH3) and urea were compared in a barley–wheat–canola–wheat cropping sequence (2007–2010) at Watrous and Lake Lenore, SK. The treatment design included a factorial arrangement of N fertilizer form (NH3versus urea), nitrification inhibitor application, time of N application (mid-September, mid- to late October, and spring) and four N fertilizer rates (0, 40, 80 and 120 kg ha−1). Anhydrous ammonia applications at 40 kg N ha−1in 2008 (fall) and in 2010 (all times of application) resulted in wheat yield reductions relative to the same applications for urea. For wheat years, yield was reduced for both fall versus spring N fertilizer applications, when no nitrification inhibitor was applied and the inclusion of nitrification inhibitor maintained wheat yield at similar levels across all times of N fertilizer applications, regardless of form. Protein concentration was approximately 2 g kg−1greater with urea compared with NH3at both sites in 2008 and only at Watrous in 2010. Also, early versus late fall N fertilizer applications consistently increased N concentration of grain only for the 40 and/or 80 kg N ha−1rates. Effects of nitrification inhibitor on N concentration were not frequent and appeared to be minimal. Urea had greater agronomic efficiency (AE) than NH3at the lower N fertilizer rates. The nitrification inhibitor had a positive effect on wheat AE only for early fall N fertilizer applications. It can be concluded that for maximum yields NH3or urea will be suitable if applied at rates of 80 kg N ha−1and greater. If N fertilizer is applied at 40 kg N ha−1, especially in fall without inhibitor, urea is better. In terms of protein concentration for wheat, urea seemed to better than NH3and fall was better than spring application.

scholarly journals Classifying multi-model wheat yield impact response surfaces showing sensitivity to temperature and precipitation change

2018 ◽  
Vol 159 ◽  
pp. 209-224 ◽  
Author(s):  
Stefan Fronzek ◽  
Nina Pirttioja ◽  
Timothy R. Carter ◽  
Marco Bindi ◽  
Holger Hoffmann ◽  
...  
Keyword(s):  
Wheat Yield ◽  
Response Surfaces ◽  
Precipitation Change ◽  
Impact Response ◽  
Temperature And Precipitation

scholarly journals Impact of Climate Change on Water Availability and Food Security of Nepal

2012 ◽  
pp. 59-63
Author(s):  
Roshan Kumar Mehta ◽  
Shree Chandra Shah
Keyword(s):  
Climate Change ◽  
Crop Production ◽  
Climatic Factors ◽  
Monsoon Season ◽  
Groundwater Table ◽  
Maximum Temperature ◽  
Aquatic Life ◽  
Temperature And Precipitation ◽  
Average Maximum ◽  
Water Scarce

The increase in the concentration of greenhouse gases (GHGs) in the atmosphere is widely believed to be causing climate change. It affects agriculture, forestry, human health, biodiversity, and snow cover and aquatic life. Changes in climatic factors like temperature, solar radiation and precipitation have potential to influence agrobiodiversity and its production. An average of 0.04°C/ year and 0.82 mm/year rise in annual average maximum temperature and precipitation respectively from 1975 to 2006 has been recorded in Nepal. Frequent droughts, rise in temperature, shortening of the monsoon season with high intensity rainfall, severe floods, landslides and mixed effects on agricultural biodiversity have been experienced in Nepal due to climatic changes. A survey done in the Chitwan District reveals that lowering of the groundwater table decreases production and that farmers are attracted to grow less water consuming crops during water scarce season. The groundwater table in the study area has lowered nearly one meter from that of 15 years ago as experienced by the farmers. Traditional varieties of rice have been replaced in the last 10 years by modern varieties, and by agricultural crops which demand more water for cultivation. The application of groundwater for irrigation has increased the cost of production and caused severe negative impacts on marginal crop production and agro-biodiversity. It is timely that suitable adaptive measures are identified in order to make Nepalese agriculture more resistant to the adverse impacts of climate change, especially those caused by erratic weather patterns such as the ones experienced recently.DOI: http://dx.doi.org/10.3126/hn.v11i1.7206 Hydro Nepal Special Issue: Conference Proceedings 2012 pp.59-63

scholarly journals Comparison of Herbicides for Control of Diclofop-Resistant Italian Ryegrass in Wheat

Agriculture ◽  
2018 ◽  
Vol 8 (9) ◽  
pp. 135 ◽  
Author(s):  
Taghi Bararpour ◽  
Ralph Hale ◽  
Gurpreet Kaur ◽  
Jason Bond ◽  
Nilda Burgos ◽  
...  
Keyword(s):  
Triticum Aestivum ◽  
Winter Wheat ◽  
Lolium Perenne ◽  
Wheat Yield ◽  
Field Studies ◽  
Triticum Aestivum L ◽  
Italian Ryegrass ◽  
Lolium Perenne L

Diclofop-resistant Italian ryegrass (Lolium perenne L. ssp. Multiflorum (Lam.) Husnot) is a dominant weed problem in non-irrigated winter wheat (Triticum aestivum L.) in mid-south USA. Field studies were conducted from 2001 to 2007 to evaluate the efficacy of herbicides for diclofop-resistant ryegrass control and effect on wheat yield. In 2001 through 2004, chlorsulfuron/metsulfuron at 0.026 kg ha−1 preemergence (PRE) followed by (fb) mesosulfuron at 0.048 kg ha−1 at 4-leaf to 2-tiller ryegrass provided 89% control of diclofop-resistant Italian ryegrass, resulting in the highest wheat yield (3201 kg ha−1). Flufenacet/metribuzin at 0.476 kg ha−1 applied at 1- to 2-leaf wheat had equivalent Italian ryegrass control (87%), but lesser yield (3013 kg ha−1). In 2005–2006, best treatments for Italian ryegrass control were chlorsulfuron/metsulfuron, 0.013 kg ha−1 PRE fb mesosulfuron 0.015 kg ha−1 at 3- to 4-leaf ryegrass (92%); metribuzin, 0.280 kg ha−1 at 2- to 3- leaf wheat fb metribuzin at 2- to 3-tiller ryegrass (94%); chlorsulfuron/metsulfuron (0.026 kg ha−1) (89%); and flufenacet/metribuzin at 1- to 2-leaf wheat (89%). Chlorsulfuron/metsulfuron fb mesosulfuron provided higher yield (3515 kg ha−1) than all other treatments, except metribuzin fb metribuzin.

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