Validation of the effect of increasing CO2 concentration on yield of wheat plant using meta-analysis method

Concerns about the potential effects of climate change on agricultural products have prompted significant research in the past decade. Cereals are the most important food in the world population and among the various cereals, wheat plays the most important role. In our country, wheat is the most important crop in the country and has a significant role in feeding people. Due to the importance of this plant in providing food security, this study was conducted to investigate the increase in the concentration of carbon dioxide on the yield of wheat. For this purpose, meta-analysis method was used to quantitatively compare the effect of CO2 on wheat crop yield.

The purpose of meta-analysis is to obtain more information than available information. In order to obtain the necessary data for the present study, the printed sources review method was used. 75 articles were extracted on the effect of increasing carbon dioxide concentration on wheat yield, then duplicate articles and articles that lacked the desired data were removed and among the remaining articles CO2 information, sample size, average and standard deviation was extracted. In the next step, these values were recorded in Excel software and finally, using Stata 16 software, the necessary forest plot and funnel plot were drawn, and to investigate the publication bias among the studies using the trim and fill method and drawing its graphs, this was investigated.

The results of the forest plot showed that after deleting the outlier data, the two groups T2 (15-25) and T3 (35_25) have a greater final size effect (about 1.6), which indicates that with increasing temperature up to Wheat plant yield increased by 35 ° C. Also, group T0, which is not mentioned in the articles of this group, has the lowest size effect (0.38). So, it can be inferred that the yield of wheat plant will increase with increasing temperature between 15 to 35 ° C and with increasing CO2 concentration in this temperature range. Examination of the funnel plot showed that most studies had accumulated at the top of the diagram. These studies have smaller standard error, larger sample size and higher accuracy.  Publication bias was also observed in a positive direction. After drawing the funnel plot, the trim and fill method was used to estimate the potential missing studies due to the biased dissemination in the funnel plot and the adjustment of the estimate of their overall effect. After performing the trim and fill method, 6 dots marked in orange are added. These points are missing studies that need to be placed to create symmetry in the graph. This indicates that previous studies have been positive.

The results of this study showed that the studies conducted in recent years have more reliable results (due to the larger sample size and greater accuracy in the results of these studies). Also, considering that increasing the concentration of CO2 can also cause an increase in temperature, it is suggested that in future studies, studies that have examined the interaction between increasing the concentration of CO2 and increasing the temperature simultaneously on important crops, using the meta-analysis method should be examined.