seyed javad rasooli; Mohammad Taghi Naseri Yazdi; reza ghorbani
Abstract
Introduction: Environmental factors whichaffect crop yield areone of the most important factors in increasing yield.Accurate prediction of crop yield for economic management and farming systems is of particular importance.
Materials and Methods: This research was done in order to statistically model ...
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Introduction: Environmental factors whichaffect crop yield areone of the most important factors in increasing yield.Accurate prediction of crop yield for economic management and farming systems is of particular importance.
Materials and Methods: This research was done in order to statistically model and predict the canola growth and yield in Mashhad region based on 5 agricultural meteorology indicesand 12 climatic parameters during 1999 - 2014period. The date of planting determined with regard to the optimum temperature at planting with probability of 75% based on Weibull formula. Beginning and the end of the phenological stages of canola (germination, emergence, Single leaf, rosette, stemming, flower, poddingand ripening) were calculated on the basis of growing degree days (GDD) for each set. Calculation and statistical equations was done usingMinitab Ver. 13.0, 16.Ver SPSS and Excelsoftwares. Correlation analysis,statistical models andmultivariate models were used to determine the relationship between the annual yield of canolaand independent variables, includingclimaticparameters and agricultural meteorologyindices during the growing season between 1999- 2000 and2009-2010for each phenological stage (8stages).The bestmodel was selected with respect to the values of the coefficient of determination (R2) and root mean square error (RMSE).If the predictive power is estimated of the model RMSE values of less than 10% excellent, between 10 and 20% good, 20 to 30% average, and higher than 30% weak. The model tested by estimating the yield of canola for the 2010 to2014 years and the correction factor was calculated and the effect.
Results and Discussion: Canola planting date wascalculated for 23 September in Mashhad region. The phenology of canola was calculated based on growing degree days (GDD) above 5 ° C.Germination calculatedfor25 September, emergence in 3 October, appearance single leaf in 7 October, rosette in 6 March, stemming in 4 April, floweringin 21 April, podding in 15 May and ripening in 4 Jun. The time of the phenological stages of cereals is virtually the same time. Therefore, due to the water scarcity in the studied region -canola can be used in crop rotation. Average, the highest and the lowest yield of canola were1329.5, 2159 and 835.5 kg per hectare,respectively.Canola crop yield showed a rising trend during 1999 – 2014period due toimprovingfarming techniques and mechanization. All models are significant regression coefficients were tested normal, alignment and line.Each model in the absence of proof of any of these hypotheses was removed and the 9remaining models were compared.Model 1 predicted canola crop yield in the single leaf stagewith an average yield of canola evapotranspiration ((Mpet, absolute maximum wind speed (FFabsmax) and the sum of the vapor pressure deficit (VPD).Model 5 predicted canola yield in the floweringstage based on the absolute lowest temperature (Tabsmin), average daily wind speed (FF) and total sunshine hours (SH). Model 3 predicted canola yield in the rosette stage based on the average of daily minimum temperature (Tmin), the number of days with precipitation greater than 1 mm R (day) and total pressure loss water vapor (VPD). Model 7 predicted canola yield during the whole growing season based on the average of daily maximum temperature (Tmax) and total precipitation (R).After R2 models with higher coefficient of 1, 5, 7 and 3, respectively, with coefficients of determination 0.902, 0.902, 0.868 and 0.866 respectively.Then F and RMSE were evaluated forecasting models 1 and 7 excellent, 5 good model and version 3 was average. Model 7due to lower RMSE and the number of parameters during growing season was the most appropriate model. Model validatedby means ofrecordedcrop yieldsduring 2011 and2014 years. The simulated yieldswere 1470, 1639 and 1226 with average of 1445 kg per hectare. Error percent was 45.1, 9.3 and -7.1for the following years with an average of 15.7. RMSE was 9.4, 2.6 and 2.3 with average of 7.4. The predictive value of the model was excellent for all these years.
Conclusion: Model predicted the yield of canola based on the average maximum temperature (Tmax) and total precipitation (R)with error correction to reduce15.7. These variables described 86.8percent yield in the growing season and were significant at 5 percent. Canola planting date wascalculated for 23 September. Time phenology was germinated 25 September until ripening 4 Jun.
ghassem aghajani mazandarani
Abstract
Introduction: Better use of water and soil resources in paddy fields, increase in rice production and farmer's income, installation of subsurface drainage system is necessary. The main goalof these systems, are aeration conditions improvement prevention of water logging, yield increase, land use increase ...
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Introduction: Better use of water and soil resources in paddy fields, increase in rice production and farmer's income, installation of subsurface drainage system is necessary. The main goalof these systems, are aeration conditions improvement prevention of water logging, yield increase, land use increase and multiuse of the land. In different countries, installation of subsurface drainage cause yield increase and working condition on the land, but no research has been conducted in different depths and spacing. On the other hand, spacing and depth are the most important parameters in the installation of drainage systems, have a direct effect on incoming water into the drains. The aim of this research, is an investigation of the effect of subsurface drainage with different depths and spacing on discharge rate variation and water table fall, in order to analyze the improvement of water flow movement in the soil. Also, study the effect of different drainage systems on the increase of the canola yield as the second cultivation in these treatments have been compared.
Materials and Methods: To measure hydraulic conductivity in different depths, the auger holes have been dug (excavated). The saturated hydraulic conductivity in these holes wasdetermined using Ernst method (1950) before installation of drainage systems. In the drainage pilot plot of Sari Agricultural Sciences and Natural Resources University three subsurface drainage systems with mineral envelope have been installed. 1- The first one with the 0.9 m depth and 30 m spacing (D90 L30), 2- The second one with 0.65 m depth and 15 m spacing (D0.65 L15) and 3- The third one with 0.65 m depth and spacing (D0.65 L30) and one bi-level system with mineral envelope including four drains of 15 m spacing with 0.9 m and 0.65 m depths were installed alternatively. After auger hole equipment installations, in the middle spacing of two subsurface and water table reading possible, the water table fluctuation and drain outlet discharge rate from farm drains during canola growing season were measured on a daily basis. Also, canola yield during 4 years after drainage systems were monitored.
Results and Discution: The results showed that mean discharge rates of drainage systems have increased with time and in the fourth year it was better than first and second years. Duringthe second year, the highest discharge rate onthe first day was in the low depth treatment and after 3 days the discharge rates become the difference among less. In the third year, the discharge rates of high spacing drains (D0.65 L30) have become higher than of spacing drains (D0.65 L15) discharge rates. But, in the first day its discharge rate was less and one can conclude that it is due to horizontal flow. With passing time and soil structure improvement, one can observe better yield from drains with higher spacing (30 m) also. By performance of drainage and soil conditions improvement in the third and fourth year, the deeper drainage systems have becomes better and water table fall of deep drain discharge rate and soil condition improvement in these systems become higher. In bi-level drainage, by increasing deep percolation, the water table fall in this treatment increased with time. Also, based on monitoring water table, in the first and second years after 5th day and in the third and fourth years after 4th day the water tables of deep drains decreased to lower depth drains. Due to heavy soil in paddy fields and existence of hardpan, the performance of low depth drains in falling water table was better in the first years. With passing time and performance of drainage the conditions for water movement in the soil become better and performance of deep drainage systems improved and at the fourth year, deep drainage systems had better performance in draining water with respect to low depth drainage systems. Also, canola yield as second cultivation, has increased from first to fourth year and along with important of soil aeration conditions and performance of drainage systems, the grain yield hasincreased in different drainage treatments. The results showed a direct relationship between improvement of system performance and increase in grain yield. In the second year, grain yield increased in all treatments. On the other hand, the yield under drainage systems with deeper depth (D0.9 L30) even higher in the 2nd and 4th years than with low depth drain (D0.65 L30). This was because of more fall in water table levels during days after rainfall and also with next rainfall, saturation of soil up to surface layer in the plots with deeper drains were performed later and it may not reach up to thesoil surface.
Conclusion: Due to betterconditions of deep drains and with higher spacing in the improvement of paddy field use and also less environmental harm use of drains with higher spacing are recommended for these lands. On the other hand,a low increase in drain depth from 0.65 m to 0.9 m along with increase in spacing of30 m with respect to 15 m and even with 0.65 m depth, will have less cost. Due to decrease in the costs of drain installation with higher spacing, due to improvement of conditions, the performance of these systems in 2 to 3 years one can have cheaper drainage systems in the longest time and will improve the economic situation of farmers due to higher yield.
