Agricultural production is highly dependent on the climatic variability of the specific regions. Differential climatic and soil conditions bring about changes in yield, quality of crops thus affecting the economy. This study evaluated the impact of variability in different climatic factors keeping the other factors constant on spring wheat production in North Dakota from 2007 to 2011. The spring wheat yield mainly depends on the climatic changes during growing periods April to September. Average maximum air temperature was significantly different from April to September except June from 2007 to 2011. High average minimum and maximum air temperatures during planting time increase yield and planting area for 2010. In 2011, low mean soil temperature, excess rainfall in April caused low yield of spring wheat. The unmitigated climate variability will result in declines in yields. So, adoption of sustainable agriculture practices helps the farmers to develop the different practices for their farms.
The impact of climate change and its changeability is a matter of concern in agriculture and is used to resolve food security issues. Climatic conditions all over the state are not same. It depends upon location to location. Crop production depends upon the climate and area. When climatic and soil conditions are normal or favorable for a crop, then there would be a high yield of crop with the best quality as well. If condition differs from normal, then it affects the yield and quality of the products. Sometimes it causes damage of crop. Besides, most of the farmers are not aware about the suitable agriculture practices like sowing time, irrigation and fertilizer application scheduling etc. with reference to climatic and soils conditions. Crop diseases or pest infestation are also depend upon the local weather and planting time. The climate variability and the area where crop is grown are very important for the crop production. So, it automatically affects the economic condition of producers, consumers and government agencies. If crop yield is less, then price for those commodities is high for the consumers and overall affects the economy. So it is very important to grow the crop according to favorable conditions. It is important for the farmers to follow the instruction given by the research scientist and extension specialist like sowing date, irrigation application time and quantity, fertilizers application recommendations etc. because they work on the model and study the possibility of benefits and damage. Most of the farmers are not aware of different technologies, techniques and model study which help them in gaining economic benefits from the crops in different locations and also at different time.
Economic distribution in any country varies with the regions, crop and their environment. Yield of crop changes with grower’s responses towards the crop like new varieties of the crop adoption, fertilizer and irrigation application changes, temperature and precipitation and are the major factors. Producers are more concern with the maximum benefits per acre. Cost of the product, quality, demand, procuring capacity is all depended upon the supply and the price changes. If prices are high then the consumer reduces their consumption or sometime stops it. So, it tends to less or no use of that commodity then comes to reduction in supply and overall affects the total welfare. So it is important to make the equilibrium between prices and quantities of the product. Product is from field by the grower and depends upon the climate and other factors for the production. Protect the crop from unavoidable changes from the climate from the longer term. At farms, the impact of climate change and its variability on crop production is calculated and helps the farmers to develop the different practices for their farms. It is used at a regional level at different spatial scales and determines the impact of climate change.
In North Dakota, blizzards, floods, droughts, tornadoes, hail storms, thunderstorms, high winds, severe cold spells, and extreme heat are common. Cyclical droughts with semi-arid conditions are common in the western half of the state. The eastern half receives most of the precipitation as rain in the spring and summer [
The project evaluated the impact of variability in climatic factors on spring wheat production in North Dakota from 2007 to 2011. The objectives of the study are:
・ Study the climate variability from 2007 to 2011.
・ Change in spring wheat yield from last five year of data from 2007 to 2011.
・ Study the impact of climate variability on spring wheat yield.
The aim of climate variability impacts assessment is to increase the understanding of the regional and global effects of climate change on agriculture. Climatic factors include change in temperature, precipitation, and higher atmospheric CO2 concentrations etc. Worldwide, scientists are working and modeling the effect of climate change on agriculture. This is very critical issue for society because people are fully dependent upon the climate for their survival.
Studies on the plant system and crop yield have shown that environmental factors like temperature and precipitation may play an important role either synergistically or antagonistically in yield determination [
Change in climate is having less effect on total food production globally but the impact of climate change is more variable on a regional basis [
USDA report on North Dakota spring wheat yield (
In North Dakota, climate plays an important role in wheat yield and production.
North Dakota summer rainfall was the 8th wettest on record out of 116 years. Excessive rainfall spoiled the North Dakota spring wheat harvest, 48% above normal in the summer growing season. The June-August rainfall was 299.7 mm and 44% above normal (NOAA―National Oceanic and Atmospheric Administration). Crop pro- duction depends upon climate and area. When growing conditions are normal or favorable to crop, then there would be a bumper crop. If conditions differ from normal, then it affects the yield and quality of the products. It can cause damage to crop. The risk cannot be eliminated but can be minimized with contact to timely management
that would permit farm managers to display crop condition to evaluate crop yields former to harvest. National Agricultural statistics service, USDA, North Dakota field office had made surveys completed by producers and dealers of the crops. This survey help the farmer in collecting past year information regarding crop, production, yield, area harvested etc. according to area wise.
Three location of North Dakota are selected for the study are Cavalier, Grand Fork, and McHenry randomly because these locations are very good for spring wheat growth and mostly grown in northern plains of the state.
Hard red spring (HRS) wheat has selected in this study. Wheat (Triticum spp.) [
Climate data for last five year from 2007 to 2011 were collected for Cavalier, Grand Fork and McHenry in North Dakota. It is collected from sowing time (April) to harvesting time (September) for spring wheat. It includes monthly average maximum and minimum temperature, average soil temperature, total solar radiation, total PET (potential evapo-transpiration) and rainfall. The data for each year and county is presented in Tables 4-18.
In the present study, data on yield was collected from the National Agricultural Statistics Service data (NASS, USDA) and climate data from NDAWN from 2007 to 2011. The tables of climate data from April to September for 5 years from 2007 to 2010 are attached in appendix. In this study, the statistical software SAS enterprise 4.3 was used for the analysis of the data and means separation was done using Fisher’s least significance difference (LSD) at 95% Significance level. Fisher LSD test is used for the comparison of two or more means. This test can only be used when significant result is attained after the analysis of variance (ANOVA). The Fishers LSD test is basically a set of individual t tests. The formula for the least significant difference is:
Cavalier | Area planted (ha) | Area harvested (ha) | Yield (MT/ha) | Production (MT) |
---|---|---|---|---|
2007 | 135,575 | 130,313 | 2.845 | 370,816 |
2008 | 149,739 | 148,525 | 3.329 | 496,144 |
2009 | 121,410 | 116,554 | 3.127 | 364,964 |
2010 | 129,504 | 127,885 | 3.302 | 421,845 |
2011 | 123,434 | 123,029 | 2.811 | 345,641 |
Grand Fork | Area planted (ha) | Area harvested (ha) | Yield (MT/ha) | Production (MT) |
---|---|---|---|---|
2007 | 80,940 | 79,726 | 3.302 | 263,177 |
2008 | 78,917 | 78,512 | 3.800 | 297,469 |
2009 | 76,893 | 74,870 | 3.732 | 278,418 |
2010 | 77,298 | 76,488 | 3.786 | 289,848 |
2011 | 76,488 | 75,679 | 2.663 | 201,397 |
Mchenry | Area planted (ha) | Area harvested (ha) | Yield (MT/ha) | Production (MT) |
---|---|---|---|---|
2007 | 62,324 | 61,514 | 2.118 | 130,500 |
2008 | 66,776 | 65,561 | 2.286 | 150,095 |
2009 | 62,729 | 61,514 | 2.757 | 170,371 |
2010 | 69,204 | 68,394 | 2.690 | 183,979 |
2011 | 45,326 | 44,112 | 1.715 | 75,660 |
Month/Cavalier | Av. max temp | Av. min temp | Av. soil temp | Total solar radiation | Total PET | Rainfall |
---|---|---|---|---|---|---|
Apr-07 | 11.3 | −2.6 | 6.1 | 450 | 128.8 | 12.4 |
May-07 | 19.2 | 6.2 | 15.3 | 425 | 154.4 | 160.8 |
Jun-07 | 24.5 | 12.1 | 22.7 | 519 | 168.4 | 137.7 |
Jul-07 | 28.6 | 14.8 | 26.4 | 579 | 199.4 | 165.4 |
Aug-07 | 24.7 | 10.9 | 22.6 | 408 | 142.2 | 14.2 |
Sep-07 | 21.1 | 5.8 | 16.8 | 310 | 117.3 | 17.5 |
where:
t = critical value from the t-distribution table with a df (degree of freedom) from the denominator of the f statistic.
MSE = mean square error, obtained from the ANOVA test.
n = number of scores used to calculate the means.
In an attempt to improve the predictions, the coefficients of determination (R2) were also computed in model summary which shows how well the data fits in the statistical model that is being used. The R2 value ranges from 0 to 1 which then can be computed as percent to provide a better representation of the data. Higher R2 gives better the prediction of dependent variables indicating better model to be used for future outcomes.
Month/Grand Fork | Av. max temp | Av. min temp | Av. soil temp | Total solar radiation | Total PET | Rainfall |
---|---|---|---|---|---|---|
Apr-07 | 11.2 | −0.5 | 5.0 | 451 | 116.8 | 15.5 |
May-07 | 21.2 | 8.1 | 14.9 | 445 | 183.6 | 129.3 |
Jun-07 | 25.7 | 14.3 | 22.0 | 521 | 182.1 | 115.3 |
Jul-07 | 28.1 | 15.1 | 25.8 | 569 | 182.1 | 44.2 |
Aug-07 | 24.8 | 11.9 | 21.2 | 407 | 131.6 | 70.4 |
Sep-07 | 21.3 | 7.9 | 16.3 | 308 | 110.7 | 26.9 |
Month/McHenry | Av. max temp | Av. min temp | Av. soil temp | Total solar radiation | Total PET | Rainfall |
---|---|---|---|---|---|---|
Apr-07 | 11.2 | −1.2 | 5.5 | 463 | 157.0 | 13.5 |
May-07 | 18.8 | 6.8 | 13.9 | 450 | 176.0 | 143.8 |
Jun-07 | 24.0 | 12.7 | 19.9 | 538 | 187.7 | 66.0 |
Jul-07 | 28.0 | 15.8 | 24.6 | 601 | 235.0 | 89.7 |
Aug-07 | 23.1 | 12.1 | 19.8 | 412 | 156.0 | 78.2 |
Sep-07 | 20.3 | 7.9 | 15.8 | 349 | 144.5 | 34.5 |
Month/Cavalier | Av. max temp | Av. min temp | Av. soil temp | Total solar radiation | Total PET | Rainfall |
---|---|---|---|---|---|---|
Apr-08 | 10.6 | −3.7 | 4.7 | 437 | 127.5 | 22.4 |
May-08 | 17.4 | 1.4 | 13.1 | 514 | 181.1 | 20.1 |
Jun-08 | 23.3 | 8.7 | 19.6 | 527 | 170.4 | 119.1 |
Jul-08 | 25.9 | 12.2 | 23.8 | 536 | 173.0 | 65.5 |
Aug-08 | 27.0 | 12.0 | 23.1 | 477 | 169.7 | 72.6 |
Sep-08 | 20.3 | 6.7 | 16.0 | 317 | 96.0 | 143.5 |
Month/Grand Fork | Av. max temp | Av. min temp | Av. soil temp | Total solar radiation | Total PET | Rainfall |
---|---|---|---|---|---|---|
Apr-08 | 10.8 | −1.3 | 4.3 | 422 | 122.2 | 13.5 |
May-08 | 19.1 | 3.0 | 12.2 | 488 | 199.6 | 22.6 |
Jun-08 | 23.7 | 11.1 | 19.1 | 513 | 188.2 | 77.0 |
Jul-08 | 26.8 | 13.6 | 23.4 | 538 | 184.9 | 91.2 |
Aug-08 | 26.9 | 12.9 | 23.6 | 480 | 165.6 | 75.9 |
Sep-08 | 21.2 | 7.9 | 16.4 | 308 | 98.8 | 97.0 |
Climate is an essential component and varies from year to year. Crop productions are very much depends upon climate including temperature, precipitation change and other meteorological factors which varies through time.
Month/McHenry | Av. max temp | Av. min temp | Av. soil temp | Total solar radiation | Total PET | Rainfall |
---|---|---|---|---|---|---|
Apr-08 | 10.8 | −2.3 | 4.5 | 466 | 165.4 | 5.8 |
May-08 | 17.2 | 3.3 | 12.0 | 519 | 210.3 | 12.4 |
Jun-08 | 21.6 | 10.4 | 17.4 | 540 | 199.6 | 125.5 |
Jul-08 | 25.8 | 14.3 | 22.7 | 576 | 217.4 | 66.5 |
Aug-08 | 26.1 | 14.2 | 21.8 | 500 | 206.8 | 71.4 |
Sep-08 | 19.8 | 7.9 | 15.2 | 340 | 127.3 | 124.7 |
Month/Cavalier | Av. max temp | Av. min temp | Av. soil temp | Total solar radiation | Total PET | Rainfall |
---|---|---|---|---|---|---|
Apr-09 | 8.4 | −1.7 | 2.9 | 366 | 87.6 | 35.1 |
May-09 | 16.8 | 2.0 | 12.2 | 483 | 156.2 | 94.2 |
Jun-09 | 23.2 | 9.3 | 20.2 | 513 | 163.1 | 92.7 |
Jul-09 | 25.0 | 10.8 | 24.0 | 574 | 185.7 | 36.1 |
Aug-09 | 25.1 | 11.4 | 21.3 | 420 | 135.9 | 46.7 |
Sep-09 | 25.0 | 10.6 | 19.9 | 375 | 127.5 | 90.9 |
Month/Grand Fork | Av. max temp | Av. min temp | Av. soil temp | Total solar radiation | Total PET | Total rainfall |
---|---|---|---|---|---|---|
Apr-09 | 9.3 | 0.6 | 5.0 | 372 | 88.1 | 33.5 |
May-09 | 17.7 | 4.3 | 12.9 | 479 | 166.6 | 54.1 |
Jun-09 | 24.0 | 11.3 | 19.4 | 497 | 184.7 | 97.5 |
Jul-09 | 24.9 | 12.5 | 22.8 | 543 | 179.3 | 44.5 |
Aug-09 | 24.4 | 11.8 | 20.3 | 397 | 113.8 | 69.1 |
Sep-09 | 25.1 | 10.9 | 19.6 | 362 | 118.6 | 33.5 |
Month/Mchenry | Av. max temp | Av. min temp | Av. soil temp | Total solar radiation | Total PET | Rainfall |
---|---|---|---|---|---|---|
Apr-09 | 8.3 | −1.0 | 3.2 | 418 | 107.2 | 45.0 |
May-09 | 17.0 | 3.9 | 10.7 | 538 | 194.6 | 48.8 |
Jun-09 | 22.1 | 10.3 | 18.4 | 529 | 193.5 | 29.5 |
Jul-09 | 24.1 | 12.3 | 21.8 | 584 | 228.1 | 32.5 |
Aug-09 | 24.3 | 12.8 | 19.8 | 434 | 167.4 | 81.8 |
Sep-09 | 23.8 | 11.6 | 18.3 | 395 | 149.1 | 112.8 |
In this study, the impact of climate on spring wheat was discussed and other factors remain constant.
The study was done on the basis of planting to harvesting for 2007 to 2011 for average of three counties.
Month/Cavalier | Av. max temp | Av. min temp | Av. soil temp | Total solar radiation | Total PET | Rainfall |
---|---|---|---|---|---|---|
Apr-10 | 16.7 | 1.7 | 10.6 | 435 | 146.6 | 52.8 |
May-10 | 19.2 | 6.2 | 14.9 | 437 | 148.8 | 115.3 |
Jun-10 | 23.1 | 10.6 | 21.1 | 486 | 139.4 | 93.0 |
Jul-10 | 29.1 | 13.7 | 26.4 | 583 | 196.1 | 79.8 |
Aug-10 | 28.1 | 12.8 | 24.2 | 460 | 162.6 | 107.7 |
Sep-10 | 18.3 | 6.2 | 14.3 | 304 | 87.1 | 107.2 |
Month/Grand Fork | Av. max temp | Av. min temp | Av. soil temp | Total solar radiation | Total PET | Rainfall |
---|---|---|---|---|---|---|
Apr-10 | 17.2 | 3.3 | 9.5 | 408 | 145.0 | 24.6 |
May-10 | 19.3 | 7.9 | 13.7 | 429 | 154.2 | 121.2 |
Jun-10 | 23.2 | 12.2 | 18.9 | 467 | 133.1 | 87.9 |
Jul-10 | 28.1 | 14.5 | 23.9 | 542 | 174.5 | 53.1 |
Aug-10 | 28.8 | 14.2 | 24.4 | 457 | 180.8 | 43.7 |
Sep-10 | 18.5 | 7.4 | 14.3 | 290 | 99.1 | 143.5 |
Month/Mchenry | Av. max temp | Av. min temp | Av. soil temp | Total solar radiation | Total PET | Rainfall |
---|---|---|---|---|---|---|
Apr-10 | 15.5 | 3.2 | 8.1 | 434 | 166.4 | 35.6 |
May-10 | 17.6 | 6.8 | 12.1 | 459 | 179.1 | 77.7 |
Jun-10 | 22.4 | 12.3 | 18.9 | 534 | 175.5 | 116.3 |
Jul-10 | 26.5 | 14.7 | 23.3 | 577 | 211.3 | 53.1 |
Aug-10 | 26.6 | 14.1 | 22.7 | 492 | 195.6 | 43.7 |
Sep-10 | 17.7 | 7.4 | 13.7 | 320 | 116.6 | 110.2 |
Month/Cavalier | Av. max temp | Av. min temp | Av. soil temp | Total solar radiation | Total PET | Rainfall |
---|---|---|---|---|---|---|
Apr-11 | 10.6 | −1.3 | 4.6 | 372 | 86.4 | 49.5 |
May-11 | 17.1 | 4.6 | 13.1 | 418 | 132.6 | 88.6 |
Jun-11 | 23.4 | 10.2 | 20.7 | 486 | 152.7 | 106.9 |
Jul-11 | 29.4 | 13.6 | 26.4 | 555 | 183.6 | 71.9 |
Aug-11 | 29.0 | 12.7 | 25.0 | 485 | 173.0 | 19.1 |
Sep-11 | 22.7 | 6.7 | 17.2 | 373 | 124.5 | 103.6 |
The highest value for particular parameters like average air maximum temperature, average air minimum temperature, average soil temperature, total solar radiation, total PET and rainfall along with the year of observation
Month/Grand Fork | Av. max temp | Av. min temp | Av. soil temp | Total solar radiation | Total PET | Rainfall |
---|---|---|---|---|---|---|
Apr-11 | 10.1 | 0.8 | 5.0 | 377 | 85.9 | 72.6 |
May-11 | 17.3 | 6.1 | 11.7 | 408 | 135.6 | 75.4 |
Jun-11 | 23.4 | 12.9 | 17.6 | 468 | 166.9 | 73.4 |
Jul-11 | 27.9 | 15.7 | 22.4 | 538 | 177.0 | 93.0 |
Aug-11 | 26.7 | 13.4 | 21.7 | 460 | 156.7 | 55.6 |
Sep-11 | 22.0 | 6.7 | 16.7 | 369 | 123.7 | 31.2 |
Month/Mchenry | Av. max temp | Av. min temp | Av. soil temp | Total solar radiation | Total PET | Rainfall |
---|---|---|---|---|---|---|
Apr-11 | 8.1 | −1.3 | 3.2 | 407 | 96.5 | 35.8 |
May-11 | 15.8 | 5.3 | 10.5 | 427 | 154.4 | 40.6 |
Jun-11 | 21.8 | 11.9 | 17.7 | 494 | 165.9 | 150.4 |
Jul-11 | 26.6 | 16.1 | 23.5 | 556 | 200.9 | 142.0 |
Aug-11 | 25.3 | 14.3 | 21.9 | 493 | 183.1 | 98.6 |
Sep-11 | 20.4 | 7.9 | 16.2 | 389 | 147.1 | 56.1 |
during the study period is given in Tables 19-25. It also includes the coefficient of determination (R2) value which helps us to indicate the quality prediction of dependent variable. Analysis shows that in most cases the average air maximum temperature, average minimum temperature, average soil temperature, total solar radiation, total PET and rainfall significantly different in each month from the year 2007 to 2011. However, there are some exceptions and data analysis revealed that there were no significance difference in June for average maximum temperature from 2007 to 2011 and June, August for average minimum temperature. The mean average soil temperature in May, July, August, and September for year 2007 to 2011 are not significantly different. In case of total solar radiation as well, there are months of May, June, August and September which did not show any significant difference. The mean total PET in April, June, August and September for 2007 to 2011 were not found significantly different. Similar observation is made for the mean rainfall in July for year 2011, 2007, 2008 and 2010 which are not all significant to each other.
North Dakota’s major industry is agriculture. Planting and yield progress for three counties (Cavalier, Grand Fork and McHenry) was taken as average from 2007 to 2011 (
From
There are number of factors which affect the decrease in planting area like high water table, climate, soil condition, variety of spring wheat, some agronomic factor, weeds, pest, and diseases etc.
In this study, climatic factors are used and other factors are keeping constant. The impact of climate variation on spring wheat yield in North Dakota depends on the actual patterns of climatic factors change during growing
Month | Highest maximum temperature (˚C) | Observed year | Coefficient of determination (%) |
---|---|---|---|
April | 16.4 | 2010 | 95.15 |
May | 19.7 | 2007 | 66.62 |
June | 24.7 | 2007 | 45.59 |
July | 28.2 | 2007 | 76.19 |
August | 27.8 | 2010 | 71.55 |
September | 24.6 | 2009 | 81.59 |
Month | Highest mean temperature (˚C) | Observed year | Coefficient of determination (%) |
---|---|---|---|
April | 2.7 | 2010 | 78.17 |
May | 7 | 2007 | 83.84 |
June | 13 | 2007 | 56.96 |
July | 15.3 | 2007 | 72.99 |
August | 13.7 | 2010 | 59.88 |
September | 11.1 | 2009 | 84.65 |
Month | Highest mean temperature (˚C) | Observed year | Coefficient of determination (%) |
---|---|---|---|
April | 9.4 | 2010 | 88.5 |
May | 14.7 | 2007 | 60.85 |
June | 21.5 | 2007 | 47.75 |
July | 25.6 | 2007 | 42.73 |
August | 23.7 | 2010 | 58.75 |
September | 19.3 | 2009 | 92.33 |
Month | Highest mean solar radiation (Lys) | Observed year | Coefficient of determination (%) |
---|---|---|---|
April | 454.67 | 2007 | 75.87 |
May | 507 | 2008 | 83.54 |
June | 526.67 | 2008 | 53.8 |
July | 583 | 2007 | 39.08 |
August | 485.67 | 2007 | 86.96 |
September | 377.33 | 2009 | 83.1 |
periods from April to September. Average minimum and maximum temperature can affect yield by accelerating the plant development and the functioning of the photosynthetic apparatus in 2010. Average maximum temperature was significantly different from April to September except June from 2007 to 2011. There was no significant difference in June and August for average minimum temperature. Temperature determines duration and timing of growing season for spring wheat.
Month | Highest mean total PET (mm) | Observed year | Coefficient of determination (%) |
---|---|---|---|
April | 152.7 | 2010 | 78.8 |
May | 197.1 | 2008 | 66.73 |
June | 186.2 | 2008 | 55.13 |
July | 205.5 | 2007 | 10.37 |
August | 180.6 | 2008 | 56.87 |
September | 131.8 | 2011 | 49.19 |
Month | Maximum mean rainfall (mm) | Observed year | Coefficient of determination (%) |
---|---|---|---|
April | 52.6 | 2011 | 72.38 |
May | 144.5 | 2007 | 86.63 |
June | 110.2 | 2011 | 20.8 |
July | 102.4 | 2011 | 44.21 |
August | 73.4 | 2011 | 6.91 |
September | 121.7 | 2008 | 70.6 |
Year | Area planted (ha) | Area harvested (ha) | Yield (MT/ha) | Production (MT) |
---|---|---|---|---|
2007 | 92,946 | 90,518 | 2.757 | 254,831 |
2008 | 98,477 | 97,533 | 3.141 | 314,570 |
2009 | 87,011 | 84,312 | 3.208 | 271,251 |
2010 | 92,002 | 90,923 | 3.262 | 298,558 |
2011 | 81,749 | 80,940 | 2.394 | 207,566 |
In 2007 and 2008, timely rains and moderate temperatures helped spring wheat to grow very well. A favorable weather condition increases the spring wheat planting area and it also increase the yield. In 2009, the planting days for spring wheat were dry across the State with snow in the northeast regions. The middle of the month had more rain showers across the State. In 2010, Warm, dry weather at the time of planting allowed producers to begin planting, temperatures and precipitation was above normal. Harvest was in progress and aided spring wheat development in end of August.
Crop establishment was a problem when soil temperatures are low. Plant emergence and its establishment for crop growth are affected. Yield was limited by amount of water received and stored in the soil during April 2011. In 2011, Temperatures was below normal during planting of spring wheat and precipitation was above normal. Freezing rain and snow added moisture to the already wet fields. Flooding remained a problem across the state. So, planting of spring wheat was pushed back again due to saturated fields and low soil temperatures. Late planting season and more acres were planted to other crop. Transpiration is a heat avoidance mechanism. A crop that maintains transpiration cooling may be a good heat avoider. The temperature of spring wheat standing in the field may be different from air temperature by some degrees. Transpiration rate is affected by these differences in air and soil temperature. Air temperature increases with increase in leaf temperature, when stoma of leaves closes due to water shortage. During planting time, solar radiation (385.33 Lys) and potential-evapotranspiration (89.7 mm) for 2011 was less. Solar radiation affects photosynthesis, transpiration, and also used to make plant biomass. Excess of rainfall in field affect the yield by flooding. There was also the stress prior to harvest of spring wheat in these locations.
Average minimum and maximum air temperatures affect yield of 2010 by accelerating the plant development and the functioning of the photosynthetic apparatus. Average maximum air temperature was significantly different from April to September except June from 2007 to 2011. There was no significant difference in June and August for average minimum air temperature. High average minimum and maximum air temperatures during planting time increase yield and planting area for 2010. In 2011, the mean average soil temperature was found low and represented low yield of spring wheat. During planting time, solar radiation and potential-evapotrans- piration for 2011 was less i.e. 385.33 Lys and 89.7 mm respectively. This can affect the low yield because the amount of the dry matter of spring wheat produces is comparative to the amount of water that it transpires. In April, excess of rainfall in 2011 was 52.6 mm in field and caused flooding in the field. This gives in low yield.
The unmitigated climate variability will result in declines in yields. So, adoption of sustainable agriculture practices helps the farmers to develop the different practices for their farms.