jafar kambouzia

In various regions of the world, particularly in arid and semi-arid areas, climate change accelerates development stages and intensifies the impact of extreme climatic events such as frost, floods, and storms. These factors, along with reduced water resources for plants, can significantly diminish agricultural productivity. This study aimed to assess the adaptive capacities to climate change risks among 368 household-head farmers in Hashtroud County using the AHP-Fuzzy method. A questionnaire was also employed to identify the detrimental effects of climate change-induced environmental risks on farmers and evaluate their willingness to adopt sustainable management practices. The correlation between the adaptive capacity index and the extracted methods was also analyzed. The findings revealed that farmers in the Qarranqou district exhibited the highest adaptive capacity, while those in the NazarKahrizi district showed the lowest. "Drought, late-season drought, and early-season drought" were the most detrimental to Hashtroud’s agricultural lands, with weighted averages of 4.29, 3.75, and 3.71, respectively. Sustainable practices like "weather forecasting, engaging in diverse agricultural activities (gardening and animal husbandry), and conservation tillage" were more favorably received by farmers, with weighted averages of 2.88, 2.17, and 1.92, respectively. The study concluded that farmers with higher adaptive capacity suffered less from climate change’s adverse effects. Moreover, those who adopted practices like "cultivating diverse varieties, utilizing new irrigation systems, and reducing nitrogen fertilizer use" demonstrated greater resilience. These findings can inform policymakers in other regions facing similar challenges, helping to identify key adaptation drivers and optimal management practices for effective climate change adaptation.

Crop simulation models are valuable tools for prediction of crop performance under various weather conditions and allow designing methods to limit the negative impacts of adverse environmental constraints. Agricultural Production Systems sIMulator (APSIM) is a comprehensive model that simulates the performance of a wide range of crops in response to climatic, soil and management factors. In this study, the performance of APSIM-Wheat model in simulating dryland wheat phenology and grain yield was evaluated for the first time in the dryland wheat belt of west and northwest of Iran. Model calibration and evaluation was performed using information of 91 experiments from 11 research field stations in five western and northwestern provinces of Iran from 2001 to 2016. Results showed that the mean observed and simulated days to flowering and physiological maturity were 215 and 218, and 252 and 252 days after sowing (DAS), respectively. These were further supported by an acceptable range of statistical indices of nRMSE (0.29 and 0.16%), CRM (-0.018 and 0.002) and D-index (0.091 and 0.013), for flowering and physiological maturity, respectively. The observed and the simulated mean grain yield were 2245 and 2249 kg.ha-1, respectively. The values of nRMSE (7.21%), CRM (-0.002) and D-index (0.037) showed that APSIM-Wheat performed quite satisfactorily and could be considered in planning to increase dryland wheat production in west and northwest of Iran. The overall results of this study showed that the APSIM-Wheat model can be used to determine the best crop management practices, yield gap analysis, climate change impact assessment and climate change adaptation strategies in dryland wheat fields in western and northwestern of Iran.

Cotton is one of the most important fiber plants in Iran which needs more production for national fiber sufficiency goal. Its cropping area in Iran is now about 140,000 ha in which 95.3% is irrigated; rainfed cotton is growing only in Khorasan, Golestan and Mazandaran. Planting date and nutrition management and their interactions are amongst the most important determinants of crop yield. 

Field experiment in 2016 in the fields of Cotton Research Center of Golestan province in Hashem Abad split plot factorial in a randomized complete block design was conducted. Treatments include the planting date as the main factor, cultivar (Latif and Golestan) and nitrogen (three levels: desirable, a third desirable and without fertilizer) as sub plots. The first planting date in the traits (TDM, LAI, CGR and RGR) was superior to the second planting date. Among the cultivars, Golestan cultivar showed a better response to Latif cultivar at zero fertilizer level and 160 kg ha-1 nitrogen fertilizer. 

TDM variation and LAI of cotton cultivars during the growing season were three stages. The first stage, the phase of presentation, in which the TDM variations continued up to 55 and 61 days after planting and the rate of changes in the LAI, respectively, was 55 and 43 days after planting in the first and second planting dates. TDM accumulation changes up to 109 and 96 days, the LAI was about 88 and 96 days, the RGR was 55 and 61 days, and the CGR was 88 and 96 days after planting in the first and second plantings increased linearly. Maximum RGR and CGR were observed at cultivar Golestan cultivar at zero and 160 kg ha-1 in first planting date.

In general, first planting date (29 June) in comparison with the second planting date (12 July) caused higher DM production, LAI, RGR and vegetative growth and Golestan cultivar had better performance than Latif cultivar at 0 and 160 khNha-1. The maximum RGR at these two fertilizer level in Golestan cultivar was recorded at the first planting date which caused a significant difference for the time reaching maximum LAI.

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.

Among the field crops in Iran, wheat is one of the most importance crops and it is anticipated that country demand to this crop will be increased in the future. On the other hand, to improve the resilience and efficiency of agricultural systems, it seems to be urgent to anticipate the effects of climate change (changes in CO2, temperature and rainfall) on crops particularly on wheat in arid and semi-arid regions. So, this study was conducted to simulate yield and water use efficiency of wheat in four locations in the future (2050)

In this research, future projection (2050) was conducted in four locations in Khorasan Razavi province (Ghoochan, Gonabad, Sabzevar and TorbateHeydariyeh), Iran by using long term climate data at baseline (2010-1980) under two emission scenarios (RCP4.5 and RCP8.5). Future climatic scenarios were produced using the delta scenario of the CMIP5 General Circulation Model (GCM) and the climate scenario generation tools in R as introduced in the Agricultural Model Intercomparison and Improvement Project (AgMIP). A Global Circulation Model (MPI-ESM-MR) was applied. APSIM-Wheat model was used to simulate growth, yield and water use efficiency of wheat. Regarding CO2 concentration, two scenarios were considered: CC scenario (climate change along with increasing CO2 concentration) and FC scenario (climate change without increasing CO2 concentration).

Simulated results showed that average of growth season temperature in study locations in future will be increased by 1.6 ºC and rainfall will be decreased by 5.85 percent, in comparison with baseline. In CC, the average of yield increased 4.91 percent under RCP4.5 and 4.77 percent under RCP8.5. However, in FC the average of yield decreased (except Gonabad) 4.98 and 7.56 percent under two RCPs, respectively. In addition, water use efficiency in CC increased by 12.21 and 15.35 percent for RCP4.5 and RCP8.5, respectively. However, under FC, WUE increased 0.33 percent for RCP4.5 and decreased 0.41 percent for RCP8.5. Also, the finding of this study suggested that changing sowing date as two weeks earlier in Gonabad and Sabzevar will increase yield and water use efficiency, and two weeks later in TorbateHeydariyeh will relief the decreased yield.

Results of the current study showed that if the climate change accompanied with increasing CO2 concentration, the negative effect of climate change on wheat growth and yield would be compensated Also, changing sowing date in future will have further positive impacts on wheat yield and water use efficiency.

Due to the hydrophilic nature of cellulose, nanofibrillated cellulose (NFC) is supplied in low solid content and high viscosity. As a cost saving strategy, increasing the possible highest solid content is preferred, which is hardly feasible owing to the irreversible hydrogen bonding formation during drying. This phenomenon known as Hornification prevents the cellulose nanofibrils to be readily dispersed in water after being dried. This research assessed an environmentally friendly procedure for the production of water-dispersible nanofibrillated cellulose powder based on carboxymethyl cellulose (CMC) absorption.

The absorption of varying amounts of CMC (0, 20 and 40 ml to constant 100 ml NFC) on cellulose nanofibrils in different temperatures of 22 °C (ambient) and 121 °C (autoclave) was investigated using conductometric titration. As the innovative part of the project, hydrodynamic properties of the dispersed NFC suspension including viscosity, turbidity, hydrodynamic specific volume, and water uptake were explored. Besides, the size of powder particles was probed by Dynamic Light Scattering (DLS).

The results indicated that in the highest addition level of CMC (40 ml) and autoclaving at 121 °C for 25 min, the highest absorption was observed, which yielded maximum results in all hydrodynamic properties compared to the control and other treated samples. On the contrary, data recorded for DLS signified that Poly Dispersity Index and the hydrodynamic diameter of the treated samples were bigger than untreated NFC, which was ascribed to the aggregation and agglomeration of cellulose particles in aqueous media.

Based on the method presented in this research, NFC powders with suitable dispersibility were obtained after oven-drying. It is concluded that the addition of adequate CMC to NFC results in increased dispersion and waster absorption capacity. The achievements of this novel method facilitates the production, handling, and storage of NFC in industrial applications.

Plants show different morphological and phonological responses to ecological conditions within their tolerable range,which are in fact part of their heredity. These changes have a key role in species survival and ecosystems sustainability. Agricultural ecosystems are very fragiledue to the severe limitations of genetic diversity and biodiversity. In an agro- ecological approach, unlike current agriculture, careful consideration of the livelihood stages and other living organisms inthe ecosystem is of interest, and so it is attempted to manage productionas well as the optimal use of agricultural inputs.

In order to study the phonological changes in four bread wheat genotypes (Gonbad, Karim, Koohdasht, Morvarid), at different levels of urea fertilizer application (0, 66, 200 kg/ha), a factorial experiment was conducted in a randomized complete block design with three replications in two crop years of 2014 and 2015 at Agricultural ResearchStation ofGonbad-e-kavoos.

The results of this study showed that the length of vegetative and reproductive stages in these two years are different, and the effect of urea content on these stages is not the same in different ecological conditions. Therefore, it was concluded that under different temperature and humidity conditions. it is possible to apply fertilizer management, without having a significant effect on the length of the phonological periods.Observations of this experiment showed that the stalking stage is more stable compared to the previous steps, so that the length of this stage was only 0.63 day in two years, and changes in different levels of fertilizer application did not show any significant difference in two years. It seems that the length of this period is lessinfluenced by environmental factors than the other stages of wheat growth and in other words. it is expected to have a higher inheritance. Changes in the pregnancy stage are also relatively similar to the stalking stage. Even though the consumption of 200 kg/ha urea fertilizer slightly increased the change of the slope, in such a way that 68% slope the increase of the span of the period from the treatment until 66 kg/ha, urea fertilizer is changed into 111.9%, but the amount of this increase is only 0.75 day.It can be concluded that although the length of this stage of plant growth is
more affected by environmental factors over the pregnancy stage, in general, the amount of this impact is not high. Observations of this study showed that the studied wheat cultivars (whether they are introduced for dry conditions or supplementary irrigation) during the course of their growth reached the stages of emergence of spike, flowering, and seedling 7.5 to 8.5
days later in the second year (pluvious) than the first year (lower rainfall). So that the difference between these two years for the emergence of the spike on average was 8.33 day, for flowering stage 7.72 day, and for the processing stage 7.56 day. Changes in fertilizer use in these three steps were similar in both years.

This study is important in management and controlling the population of non-cultivated plant species, pathogens (fungi and bacteria), insects and other species in the amount and sustainability of crop production.

Species inhabiting fresh waters are severely influenced by anthropogenic factors. Effective management and conservation plans require high accurate and reliable species distribution forecasts. Here, we modelled potential distribution of the genus Barbus in Iran, based on environmental variables using Species Distribution Models (SDMs). Six environmental predictors (i.e. slope, bankfull width, elevation, mean air temperature, range of air temperature and annual precipitation) were applied for modelling. The models were selected among different technique (GLM, GAM, CTA, SRE, GBM, RF, MARS, and FDA) which their results were summarized through ensemble forecasting approaches. According to the TSS (True Skill Statistic), the accuracy of the implemented models was greater than 0.8. The results showed that the projected distributions not only were observed in the same recorded basins but also in the new basins. Presented results deepen the conservation knowledge in Iran and act as a guidance for management decisions aimed at legal identification of critical habitats for species as well as informing them for translocation of threatened or captive-bred populations.

In recent decades, climate change and other anthropogenic pressures have seriously influenced freshwater biodiversity to decline faster than terrestrial biodiversity. This trend is likely to be continued in the future. We assessed the impact of climate change on the distribution of brown trout in Iran by simulating their conditions under optimistic and pessimistic climate change scenarios (RCP 2.6 and RCP 8.5) in 2050 and 2080 by using species distribution models (SDMs) tool and ensemble forecasting approach. The results showed a significant reduction in the distribution range of this species (100%) in our database in all optimistic and pessimistic climate change scenarios. Moreover, no new potential sites were predicted in those scenarios. These outcomes seriously warn that a conservation and management plans are required to protect this species in future.

The current study was conducted in six locations of Khorasan Razavi province (Ghoochan, Gonabad, Mashhad, Sabzevar, TorbateHeydariyeh and TorbateJam). At first, future climate (2050) was generated using long term climate data of baseline (2010-1980) and by AgMIP method on two climates scenario (RCP4.5, RCP8.5). A Global Circulation Model namely MPI-ESM-MR along with APSIM-Wheat model were used for growth and yield simulation of wheat under water-limited conditions. Simulating results showed that average changes in growth season temperature will be increased as 14.4 and 18.6 percent in the studied areas in future in comparison with baseline for RCP4.5 and RCP8.5, respectively (1.41 and 1.83 °C compared with the baseline). Also, results indicated that the length of growing season and days to flowering will be declined 13 to 24.6 days and 13.2 to 30.4 days, respectively. In this research, the grain yield had positive changes in future in most of the studied locations due to the interaction of temperature and CO2. The results of this study also revealed that changing sowing date could result in an increase in grain yield in future. Locations with higher baseline temperature well responded to two weeks earlier in sowing date while locations with lower baseline temperature had good performance in sowing date of two weeks later which resulted in further yield increase in the future. Overall, the findings of this study suggested that changing sowing date in future could further increase wheat grain yield which is highly important for food security, according to the increasing demand in future.

Heat stress caused by climate change will become a restriction for maize production in the future (Cairns et al., 2013). Damage of heat stress is very strong when is occurred in a critical stages of plant growth (particularly in the flowering phase) (Teixeira et al., 2013). Non-coincidentally of flowering stage with high temperature can be reduced the negative effects of heat stress, especially in climate change conditions (Zheng et al., 2012). In this theme, a useful change in the management practices such as early planting dates (Zheng et al., 2012; Liu et al., 2013) could be considered to avoid heat stress and reduce production risk, especially climate change situations. Khuzestan province in terms of grain maize has the highest cultivated area in Iran (Anonymous, 2013). Based on this and according to the impact of climate change on reducing maize yield in the Khuzestan province (Abbas Torki et al., 2011), this study tries to assess the risk of heat stress in grain maize at the Khuzestan province under rising temperature conditions caused by climate change.
This research was conducted in six locations of Khuzestan Province to investigate the risk assessment due to heat stress in maize in the future climate change. Accordingly, the future climate in the study areas was generated using long-term (1980-2009) climate data of the baseline (included minimum and maximum temperatures, rainfall and global radiation) and AgMIP technique under two climate scenarios (RCP4.5 and RCP8.5) for the future period of 2040 -2069. Long-term simulation experiments consisted of three sowing dates (3st February, 19st February and 5th March), six locations (Ahwaz, Behbahan, Dezful, Izeh, Ramhormoz and Shushtar), two future climate scenarios (RCP4.5 and RCP8.5) in 30 years. In total, around 1620 simulation experiments were carried out. To assess the risk of heat stress on maize, it was considered the time (phase), frequency and intensity of maize threshold temperatures in its sensitive phenological phases. To this end, flowering and grain formation phases of maize were noted as the most sensitive to high temperature stress. In this study, APSIM crop model was used for simulation of maize growth and yield. The OriginPro 9.1 and R software were used to draw figures and perform statistical analyses.
Results indicated that the average temperature during the growing season in the Khuzestan province was increased under RCP4.5 and RCP8.5 (8.5 and 34.57 percent, respectively) in comparison to the baseline (27.2 °C). The highest temperature rise was obtained in the Ramhormoz (27.2 °C) on 5th March under RCP8.5. Also, the highest temperature rise during the growing season under RCP4.5 obtained in Shushtar (27.2 °C) on 19st February. In the baseline, on average, grain yield and the number of grains/m-2 in the Khuzestan province were obtained 8.8 t ha-1 and 2305.7. These values in 2050 were 8.5 and 8.7 t ha-1 and 2227.3 and 2254.3 grains/m-2 for RCP4.5 and RCP8.5, respectively. When average across sowing dates, locations and periods, the cumulative probability function for economic yield, non-economic yield and zero yield were 45.4, 13.5 and 41.2 %, respectively for common sowing dates. Under, earlier sowing date (3 February) the cumulative probability for economic yield was higher than the other sowing dates both in future and the baseline periods (65.2 percent).
Overall, the results of this study showed that common sowing date which is used by most farmers (19st February) in Khuzestan province was not optimal for both current and future periods while the early sowing date (3st February) in most locations could be considered as an effective adaptation strategy to reduce the amount of extreme temperatures risk in future and to increase grain yield under the current conditions.

Release of drought tolerant cultivars along with advance agronomic practices are effective ways to manage drought and water deficit in agriculture. In order to evaluate drought stress on 20 Iranian native and improved rice genotypes and determination of proper drought tolerance indicators in rice, an experiment was conducted based on factorial randomized complete block design with three replications at Rice Research Institute of Iran (Rasht), during 2014-15. In this study, on the basis of yield performance in stress and none stress conditions, indices of tolerance (TOL), yield stability index (YSI), stress tolerance index (STI), stress susceptibility index (SSI), harmonic mean (HM), geometric mean productivity (GMP) and mean productivity (MP). Among these indices, the indices that could led to increase yield under both normal and stress conditions, were considered as the best indices. Accordingly, stress susceptibility index (SSI), tolerance index (STI), geometric mean productivity (GMP) and harmonic mean (HM) were found to be the best indices for drought resistance selection. Regarding these criteria, the cultivars of the Hashemi, Alikazemi, Shiroodi and Sepidrood were considered as the most tolerant genotypes. The result of this research showed that the indices including stress susceptibility index (SSI), stress tolerance index (STI), geometric mean productivity (GMP) and harmonic mean (HM) could be used for selection of the best Iranian rice variety based on yield. Release of drought tolerant cultivars along with advance agronomic practices are effective ways to manage drought and water deficit in agriculture. In order to evaluate drought stress on 20 Iranian native and improved rice genotypes and determination of proper drought tolerance indicators in rice, an experiment was conducted based on factorial randomized complete block design with three replications at Rice Research Institute of Iran (Rasht), during 2014-15. In this study, on the basis of yield performance in stress and none stress conditions, indices of tolerance (TOL), yield stability index (YSI), stress tolerance index (STI), stress susceptibility index (SSI), harmonic mean (HM), geometric mean productivity (GMP) and mean productivity (MP). Among these indices, the indices that could led to increase yield under both normal and stress conditions, were considered as the best indices. Accordingly, stress susceptibility index (SSI), tolerance index (STI), geometric mean productivity (GMP) and harmonic mean (HM) were found to be the best indices for drought resistance selection. Regarding these criteria, the cultivars of the Hashemi, Alikazemi, Shiroodi and Sepidrood were considered as the most tolerant genotypes. The result of this research showed that the indices including stress susceptibility index (SSI), stress tolerance index (STI), geometric mean productivity (GMP) and harmonic mean (HM) could be used for selection of the best Iranian rice variety based on yield. Release of drought tolerant cultivars along with advance agronomic practices are effective ways to manage drought and water deficit in agriculture. In order to evaluate drought stress on 20 Iranian native and improved rice genotypes and determination of proper drought tolerance indicators in rice, an experiment was conducted based on factorial randomized complete block design with three replications at Rice Research Institute of Iran (Rasht), during 2014-15. In this study, on the basis of yield performance in stress and none stress conditions, indices of tolerance (TOL), yield stability index (YSI), stress tolerance index (STI), stress susceptibility index (SSI), harmonic mean (HM), geometric mean productivity (GMP) and mean productivity (MP). Among these indices, the indices that could led to increase yield under both normal and stress conditions, were considered as the best indices. Accordingly, stress susceptibility index (SSI), tolerance index (STI), geometric mean productivity (GMP) and harmonic mean (HM) were found to be the best indices for drought resistance selection. Regarding these criteria, the cultivars of the Hashemi, Alikazemi, Shiroodi and Sepidrood were considered as the most tolerant genotypes. The result of this research showed that the indices including stress susceptibility index (SSI), stress tolerance index (STI), geometric mean productivity (GMP) and harmonic mean (HM) could be used for selection of the best Iranian rice variety based on yield.

An experiment was conducted at the experimental field of Agricultural Research Institute of Atomic Energy Organization in Karaj in 2015, as a randomized complete block design with three replications. Treatments included 14 barley cultivars . Results showed that there were significant differences between most of the studied barley cultivars regarding physiological and morphological traits. The newer cultivars and Roudasht showed advantages over older cultivars with regard to leaf area index, radiation use efficiency and crop growth rate. Cultivars Valfajr, Makouee and Bahman had the highest leaf mass fraction, mostly as a result of being late-maturity cultivars along with having high leaf area index and specific leaf area. On the other side, cultivars Behrokh, Roudasht and Makouee had the highest stem mass fractionmainly as a result of their corresponding growth habits (two-rows, gamma- irradiated and tall- statured, respectively). Also results showed that cultivars which had the highest stem and leaf mass fractions such as Makouee, Roudasht and Valfajr produced the lowest spike mass fraction and in turn grain yield. Cultivars Lout, Nosrat, Rayhann03 and Fajr30 had the highest spike mass fraction which could be attributed to their six-row habit of spike, early-maturity and lower leaf and stem dry matter at flowering stage. Overall, it could be concluded that tall statured late-maturity cultivars along with gamma- irradiated improved barley cultivar had the highest leaf and stem mass fractions compared to dwarf and early maturity cultivars. Such advantage, however, translated into lower spike mass fraction and grain yield of the former group.

The current study was implemented by using general circulation models (GCMs) aiming at predicting the future climate change as well as its impacts on wheat yield in seven locations of Khuzestan province including Ahwaz, Dezful, Ezeh, Behbahan, Bandar Mahshahr, Ramhormoz and Omidiye. Accordingly, general circulation model of HadCM3 (United Kingdom Met Office Hadley) under three emission scenarios (B1, A1B and A2) for three time periods (2011-30, 2046-65, 2080-2099) were investigated. LARS-WG software was used to generate daily climate parameters. The outputs of LARS-WG were used as inputs for APSIM crop simulation model to simulate growth and development of wheat under future climate change. According to the results obtained, the future minimum and maximum temperatures in Khuzestan will have increasing trend. Simulation results also showed that grain yield, biomass yield and leaf area index (LAI) substantially increased in all locations under future climate compared with the baseline period. Compared to the baseline, the highest wheat grain yield in the future would be obtained in Izeh and Ramhormoz (7691 and 6596 kg ha-1, respectively). Overall, it is concluded that over the coming decades, the wheat grain yield in Khuzestan province will have increasing trend largely due to an increase in LAI (which is highly correlated with grain yield). Other growth characteristics such as length of growing season had less impact on grain yield compared with the LAI under climate change in all study locations. Also, locations with cooler temperature in the baseline (i.e. Izeh) will produce higher grain yield in the future.

One of the main problems in rice cultivation and production is the lack of water resources, especially during periods of low rainfall which affect vegetative growth rate and the level of yield. Drought stress has been well documented as an effective parameter in decreasing crop production, and developing and releasing new varieties which are adapted to water deficit conditions can be a constructive approach to overcoming unsuitable environmental conditions. Hence, the characterization of genetic diversity and germplasm classification for parental selection in breeding purposes is of great importance.
In order to evaluate the adaptation of rice genotypes to drought stress and to identify tolerant and sensitive genotypes, 20 genotypes were studied using a factorial randomized complete block design with three replications at the Rice Research Institute (Rasht). During growth stages, some traits were recorded such as plant height, total and fertile tiller number, flag leaf area, panicle length, filled and empty grain number, 100-grain weight, number of days to maturity and yield.
Mean comparison showed that the lowest percentage changes in traits among local varieties (Hashemi, Alikazemi and Sangjo) and improved cultivars (Dorfak, Sepidrood and Shiroodi) respectively. Cluster analysis using Ward’s minimum variance and squared Euclidean distance for agronomic traits divided the genotypes into two groups. The separated varieties were grouped in clusters with high quality on the basis of morphological traits and this guides us to select the most different and the best for hybridization programmes, especially to hybridize with local varieties in order to create new varieties resistant to stress. The result of factor analysis based on the principal component showed that factors three and four accounted for 73- 85 of total variance.
For the selection of genotypes with high yield and stress tolerance in rice, total and fertile tillers, days to maturity, flag leaf area, panicle length and 100-grain weight could be considered through estimating suitable selection indices for these traits. local and improved cultivars. The study found that the different groups show genetic variation in rice genotypes.

Investigating the impacts of agricultural management on crop productivity in specific environments is easily possible through crop simulation models. These computer-based tools, provide the ability of making some decisions regarding the use of agriculture resources and inputs. However, prior to use of these models, they need to be fully evaluated under different locations and years. Hence, this study has been performed to evaluate APSIM crop model and estimate the cultivar-specific parameters as inputs for the model.
Different datasets were used in order to parameterize and evaluate APSIM-Maize model for three maize cultivars. So that, a four-year dataset (Shiraz) was used for the calibration of K.SC 260 cultivar from early maturing group. Also, for K.SC 704 (from late maturing group) and Maxima (from mid-maturing group) were applied from the two regions (Kerman and Khoramabad, each one at one year). These datasets are used to adjust parameters based on biomass, grain yield, the number of days from emergence to flowering, the number of days from flowering to physiological maturity and LAI for each cultivar. Model validation was conducted by a series of other datasets including published articles in journals and final reports of research projects.
Three statistical indicators including coefficient of determination (R2) root mean squared error (RMSE) and index of agreement (d value) were computed from observed and simulated variables. The OriginPro 9.1 software was used to statistical analysis and draw figures.
The results of the model evaluation indicated that the model simulated flowering and physiological maturity stages of three cultivars with high accuracy in different years and different locations, so that the values of root mean square for flowering and maturity dates were as 1 and 1.35 %, respectively. Also, the simulation of LAI trend for two K.SC 704 and Maxima revealed that the APSIM-Maize model simulated LAI trend of these two cultivars with high accuracy. The values of root mean square for LAI trend of K.SC 704 in Kerman and Khoramabad were as 16.7 and 9.48 %, respectively. Also, for Maxima in Kerman and Khoramabad were as 16.75 and 10.65 %, respectively. Ultimately, APSIM-Maize model exactly simulated grain yield and biomass with high accuracy by accurate simulation of leaf area index and phenological stages.
Genetic parameters were different among the cultivars. The highest (650) and lowest (545) maximum number of kernel per ear belonged to cultivars K.SC 704 and K.SC 260, respectively. Also, the highest and lowest thermal time accumulations from flowering to maturity and those of seedling emergence to end of juvenile phase belonged to cultivars K.SC 704 and K.SC 260, respectively. Investigations show that the K.SC 260 is better rather than other cultivars just in terms of grain growth rate (9.6 mg kernel–1d–1). Finally, among the three cultivars, K.SC 704 has the highest biomass (21.81 t ha-1).
The evaluation of APSIM-Maize model indicated that the model simulated phenological stages (flowering and physiological maturity) with high accuracy which proves that this model has suitable structure for simulation of phenological stages. Also, among the different cultivars, the number of kernel per ear, thermal time accumulation from flowering to maturity and thermal time accumulation from seedling emergence to end of juvenile phase, were greater in K.SC 704 rather than other cultivars.

In order to study the competition effects of redroot pigweed (Amaranthus retroflexus) and millet (Panicum miliaceum) on maize performance under different rates of N fertilizer, a field experiment was conducted in 2009 in the research fields of Tarbiat Modares University in Tehran as a randomized complete block design with factorial arrangement of treatments and three replications. Accordingly, three factors included nitrogen fertilizer (75% optimum or 138 kg N ha-1, optimum or 184 kg N ha-1 and 125% optimum or 230 kg N ha-1), weed species (redroot pigweed and millet) and weed densities (5 and 25 plants m-1 for redroot pigweed and 7.5 and 37.5 plants m-1 for millet) consisted. Results showed that the highest grain yield (921.89 g m-2) was achieved in treatment 230 kg N ha-1 while the lowest yields (466.72 g m-2) belonged to treatment millet fertilized with 138 kg N ha-1. High densities of millet and redroot pigweed resulted in significant reductions in number of grains per row and the ear length. Differences in N application rates cause significant variations in biological yield and some of the yield components of maize. Overall, results indicated that in fields where a nitrophile species is the dominant, increasing N application rate beyond the optimum not only does not increase maize grain yield but also reduces its yield and causes pollution of environment.

Iran is located in an arid and semiarid region that is vulnerable to environmental changes. So, it would appear that the occurrence of climate change in this region would have a significant impact on agricultural production systems (Eyshi Rezaie and Bannayan, 2012). Climate change might affect the water available for agriculture and, consequently, lead to drought occurring in semiarid areas (Koocheki et al., 2006). Evaluating adaptation strategies, such as changing the planting of dates, can help to increase maize water use efficiency under climate change conditions (Ramprasad et al., 2016). One of the cheapest ways to measure the effects of climate change on agricultural production is through a modelling approach and application of simulation models (Manschadi et al., 2010). This study aims at investigating the sowing date as a strategy for maize adaptation and improving its water use efficiency under climate change conditions in Khuzestan Province. For this purpose, six locations in Khuzestan Province were selected (Ahwaz, Behbahan, Dezful, Izeh, Ramhormoz and Shushtar). Daily long-term climatic data including minimum and maximum temperatures, rainfall and global radiation in a baseline period (1980-2010) were collected for these locations from their meteorological stations. Then, daily long-term climatic data were generated for the future period of 2040-2069 in these locations by using a method proposed by AgMIP under two climate scenarios (RCP4.5 and RCP8.5). In this study, the SC704 cultivar was used. Taking into account three sowing dates (4 February, 19 February [a common sowing date] and 5h March), six locations, and two climate scenarios over 30 years, a total of 1620 simulation experiments were carried out in this study. In order to simulate the growth and yield of maize under different sowing dates, the APSIM model was applied. Results indicated that early sowing date (4 February) with 10117.1 kg ha-1 had a higher economical grain yield compared to 19 February (10061.3 kg ha-1) and 5 March (7194.6 kg ha-1). Also, in the future period, the reduction percentage in economical grain yield at the different sowing dates compared to the baseline common planting date (19 February) showed that the early sowing date of 4 February recorded less reduction (-3.3 and -4.5 percent under RCP4.5 and RCP8.5, respectively) than 19 February (-6.5 and -6.7 percent under RCP4.5 and RCP8.5, respectively) and 5st March (-31.1 and -23.2 percent under RCP4.5 and RCP8.5, respectively). On average in Khuzestan Province, an early sowing date indicated higher water use efficiency (WUE) )11.8 kg ha-1 mm-1) compared to 19 February (10.7 kg ha-1 mm-1) and 5 March (7.6 kg ha-1 mm-1) in the baseline period. However, under climate change conditions, reduction of WUE in different planting dates compared to the baseline common sowing date (19 February) revealed that 4 February (2.8 and 3.3 percent under RCP4.5 and RCP8.5, respectively) was superior compared with 19 February (-12 and -11 percent under RCP4.5 and RCP8.5, respectively) and 5 March (-40.1 and -32.5 percent under RCP4.5 and RCP8.5, respectively) in term of WUE in Khuzestan Province. In general, according to the results found the common sowing date of maize in Khuzestan is not optimal for maize in terms of water use efficiency and economical grain yield. Accordingly, to increase economical grain yield and water use efficiency in both the future and baseline periods at Khuzestan Province, farmers should
choose the early sowing date (4 February) compared to the common and late ones.

In recent decades, plant yield is said to have been affected by three major factors: genetics, management and climate change (Ciampitti and Vyn, 2012). However, climate change has been reported as the most effective factor on the yield of wheat, rice and maize crops (Li et al., 2010). Both modeling and empirical studies have indicated that maize yield is negatively affected by climate change at the global scale (Lobell et al., 2011). Among climatic factors, temperature plays a significant role on crop growth (Wallach et al., 2006) and each species has a specific temperature range represented by a minimum, maximum, and optimum (Hatfield and Prueger, 2015). This study was performed to investigate the effect of these factors on grain yield of irrigated maize in two provinces of Iran, Khuzestan and Fars, which include the largest area of maize cultivation.
The present experiment was conducted in 2014 and by study of eight locations in Khuzestan and Fars Provinces. The long-term data of irrigated maize yield in the studied cities were collected from the Ministry of Agriculture and the long-term weather data including minimum temperature, maximum temperature and average temperature were collected from the Iranian Meteorological Organization. Total weather data were controlled by the Tamet program and outliers were deleted. Then, the appropriate period for investigating weather data was selected based on maize growth period in each city. Also, in order to eliminate the effects of genetic improvement and management, the double exponential smoothing method was employed. To calculate weather parameter changes, trend and the relationship between maize yield and weather parameters were used as a simple linear regression. Finally, drawing graphs and Fig.ures was performed using Microsoft Excel 2003 and SigmaPlot v.11.
The results of present study showed that the minimum, maximum and average temperatures increased in most of the cities studied. Also, it can be stated that a rise in the average temperature has been more greatly affected by the minimum temperature than the maximum temperature. Generally, in all cities of Fars province the temperature throughout the maize growing season was in the optimal range for maize and higher yields in these cities could be due to a more favorable temperature. The results showed that the lowest median average temperature during growth period belonged to Fasa (22.87 ° C) and Shiraz (25.42 ° C). Similarly, the highest median yield was also belonged to Fasa and Shiraz with 8539.11 and 7934.42 kg ha-1, respectively. In contrast, Shushtar and Ahvaz showed the highest median average temperature and had the lowest yield among the studied cities. In general, it seems that higher grain yield in the locations studied in Fars province could be because of a lower temperature in the maize growing season compared with Khuzestan province. Results of the double exponential smoothing method and regression analysis indicated that the regression coefficients between smoothed maize yield and maximum, minimum and average temperature were not significant in any cities except in Marvdasht where there was a negative relationship between rising temperature and maize yield.
Despite the non-significant statistical relationship between maize yield and weather parameters in the studied locations, it is important to consider national food security which will probably be affected by rising temperatures in the future. This negative effect may be overcome by developing and using suitable new methods for adaptation and mitigation in face of climate change.

In order to investigate the impact of the sowing date on yield, yield components and physiological growth indices of grain maize (Zea mays L.) cultivars, a field experiment was conducted at the Faculty of Agriculture of the University of Lorestan in 2011 as a randomized complete block design with factorial arrangement of treatments and three replications. Treatments consisted of two sowing dates (21st May and 13th June) and six maize cultivars, namely T.V.C.767 and S.C.704 from a late maturing group, cultivars T N.S640 and Maxima from a mid maturing group, and cultivars Koppany and D.C.370 from early maturing group. Results indicated that the main effects of the experimental factors were statistically significant in terms of 1000-kernel weight, number of kernels per ear, number of kernels per row, number of rows per ear and harvest index. The interaction between sowing date and cultivar was only significant in the case of biological and grain yields, ear length and plant height. In the first sowing date the highest and lowest grain yields belonged to cultivars S.C.704 and D.C370 (12.7 and 7.5 t ha-1, respectively). In the second sowing date, N.S.640 from mid maturing group was ranked first in this regard (13.37 t ha-1). Higher grain yield in S.C704 and N.S640 compared to other cultivars, could be attributed to their higher leaf area index, leaf area index duration and crop growth rate. In total, planting late maturing group cultivars is not recommended for the second sowing date.

Exploring weather variability and its effects on crop yield may help to provide a better understanding of its effects on agricultural production. In this study, the relationship between weather descriptors and wheat (Triticum aestivum L.), barley (Hordeum vulgare L.) and potato (Solanum tuberosum L.) yields were assessed under irrigated farming conditions in Hamadan Province. Long term data (1990 to 2010) of yield and weather variables (rainfall and temperature) were collected from the Agricultural and Meteorological Organizations of HamadanProvince. The relationships between crop yields and climatic variables were studied using correlation and simple linear regression analysis. Results indicated that the association between various crop yield and descriptors varied in different study locations. In Razan and Bahar, yields of the crops studied did not correlate with weather indicators whereas, in other regions, the relationship between rainfall and temperature with crop yields was strong. In Kabodar Ahang, the correlation between wheat and barley yields and Malayer wheat yield with the growing season maximum was negative and decreased with an increasing maximum temperature during the growing season. In all study areas, potato yield did not correlate with rainfall. However, was a significant and positive correlation between barley yield with rainfall in Hamedan, Toyserkan and Nahavand and wheat yield with rainfall in Malayer, Nahavand and Toyserkan. The association of results between various crop yields on a monthly scale, indicate a high and significant correlation (positive or negative) between temperatures in March and April rainfall with crop yield in each part of Hamedan Province.

Insecticides are one of the most important pesticides applied in Iran and، during the last two decades، have accounted for about 50 percent of pesticide usage. However، the negative impacts of insecticide have resulted in several environmental problems and placed human health in danger. In this study، the environmental impacts of registered insecticides in Iran were evaluated using the environmental impact quotient (EIQ). EIQ has three major variables، namely the farm worker، consumer and ecology for which the final score is the average of these variables. Following this، insecticides were classified according to the International Resistance Action Committee (IRAC) classification and the results for each class were analyzed. Results show that، potentially، classes 2 and 6 (based on EIQ scores) are the most hazardous and Imidacloprid، which is classified in group 4، received the highest EIQ score. Considering the active ingredients of registered insecticide، EIQ scores، and their rates of application in Iran during 2000-05، the EIQfield which demonstrates practical hazards was calculated. According to this، classes 2، 1 and 4 are، respectively، the most hazardous insecticides. Therefore، it seems that it is vital to find an alternative for Imidacloprid. Considering the environmental impacts of pesticides and their mode of action simultaneously could be a valuable approach in order to achieve sustainable pest management in sustainable agriculture.

Today، the agricultural sector is one of the main energy consumers worldwide. Increasing world population، accompanied by natural resource limitations، reveals the importance of research about energy use efficiency in agriculture that is responsible for supplying food security for this population. This study was performed to evaluate and compare energy efficiency in the rice agroecosystems of Kohgiluye and Bouyerahmad and Guilan Provinces of Iran in the 2010-2011 crop season. Data acquisition was performed using the field study method and completing a questionnaire. Completion of the questionnaire was accomplished by face-to-face interviews on farms. According to the results، the total energy input of Guilan rice agroecosystems was 43496. 33 MJ/ha، of which the greatest share of energy inputs was related to water for irrigation (38. 54 %)، electricity (23. 99 %) and nitrogen fertilizers (18. 98 %). The energy input amount of the Kohgiluye and Bouyerahmad rice agroecosystems was 33668. 16 MJ/Ha، and the geatest share of energy inputs was related to water for irrigation (49. 7 %)، nitrogen fertilizers (27. 99 %) and phosphorous fertilizers (4. 65 %). The combined energy output of Guilan and Kohgiluye and Bouyerahmad Provinces’ rice agroecosystems was obtained at 122913. 16 and 113820. 21 MJ/Ha، respectively. Energy efficiency for the aforementioned fields was calculated as 2. 82 and 3. 38، respectively.

Therefore in order to provide a clear image of current situation of collection throughout district 1 of Tehran municipality, all required statistics and information about collection and analysis of wastes disposal were applied by the use of field studies. In order to present a proposal for Solid Wastes management of municipality, we applied WAGS software with 40 major parameters and 14 indirect parameters for further calculations. Then according to the data, it was possible to specify time interval of wastes collection, coming & going of trucks to & from disposal place equal to 112 minutes, compressed volume of garbage equal to 3.5 cubic meters, functions of trucks in collection & transfer of wastes to burring place. It had an output and useful life span of 11 years at district. The required number of vehicles between 2010 up to 2024 will be between 60 to 200 5-tons vehicles according to the estimations of this software. In case of any replacement %25 of vehicles due to have wider streets at districts 7, 2 and 10, there will be a reduction in the number of vehicles between the years 2010 up to 2024 from 59 to 186 systems. In case of a complete recycling of disposals of the mentioned district, there is an increase rate from 39 systems to 130 systems accordingly. Regarding worker ship force also it is estimated to need 120 to 400 workers between 2010 up to 2024 then in case of any reduction in number of forces into half amount there is a reduction in budget from 29547,88 million Rials to 14773,94 million Rials. The most effective factor on required budget is collection of Municipality disposals of district 1 and separation of recyclable dry wastes at origin. Therefore with regard to %94 required budget, it is anticipated to have a reduction in required budget for supplying of collection machinery from 1808979,04 to 1174862 million Rials. It has been anticipated to have relevant costs of repairs and maintenance of collecting machinery for a sum of 29900,48 million Rials up to the end of 2020 which is %1.6 of total required budget. In order to make better current situation, any training courses for personnel and for better collection of disposals and legalization of citizens duties and responsibilities and mayors will have great importance role in reduction of costs and increasing the quality of disposals collection.