Accurate production planning is required for crop yield to be accurately estimated. Therefore we will be able to gain a forecast at the macro level by determining market demand for developing or mitigating products or other planning issues related to production systems. In order to study optimal cropping patterns in East Azerbaijan Province, potential productivity for wheat, barley, chickpea and safflower were studied based on an analysis of supply and demand sources. The AEZ model was used to estimate the potential of yield, as proposed by FAO. In this way, it is assumed that the cultivars enjoy high efficiency and that limitations of water and soil, pests and diseases do not exist. To form data layers, IDW and kriging methods were used. Zonation of potential production was conducted using the overlapping layers in the GIS. Model validation was conducted using RMSE and the Willmott index of agreement. The estimated values were more than the actual quantities for wheat and barley (r2=0.71) but, for chickpea and safflower, they were slightly lower than the actual data (r2@0.50). The production capacity was acceptable for all four crops in the study region. Land in that province was relatively suitable for rain-fed cultivation of wheat and barley. Conditions for growing chickpea were detected as marginally suitable and unsuitable lands for safflower growing were in the maximum. In most regions, wheat and barley potential production showed a moderate to high capability. Potential for chickpea production was higher in the southern regions of the province and safflower enjoyed this situation in the Eastern. SPA for each crop and the GPA for all of them and for various scenarios were calculated then, based on results achieved, the cropping patterns were calculated. The GPA index suggested that cropping patterns that included barley-chickpeas-safflower had the highest value. After that, were wheat-chickpeas and barley-chickpeas compositions.

Due to limitation of available water and soil resources in Iran, the challenge of optimizing the utilization of these resources has become more significant. In this study it was attempted to maximize the project benefit, estimating crop water requirements at different growth stages, and optimizing the cropping pattern and irrigation management. In order to achieve these objectives mathematical model was solved with simple genetic algorithm (GA) and linear programming (LP) methods. The proposed model was applied to an irrigation project with 7000 ha of farmland irrigated by the main canal network of Doroodzan dam (Fars province). Comparing the optimal cropping pattern proposed by this model (IPM) with those practiced by the farmers showed that the model had a good consistency with farmers’ decisions for cultivating different crops. The results of this model also indicated that optimal planting pattern (in the 1st and 2nd growing season) was the same for GA and LP models. To find the best response from GA in this study the number of generations of 800, population size of 100, probability of crossover of 0.6, and probability of mutation of 0.02 was considered.

BACKGROUND AND OBJECTIVES: Agriculture plays a significant role in the overall consumption of freshwater resources, accounting for approximately 70 percent of the total use. Energy is also essential at various stages of agriculture and the food chain. On a global scale, the agricultural and food industries account for approximately 30 percent of the overall energy consumption, with a significant portion derived from fossil fuel sources. This underscores the intricate interconnection between food, energy, and water resources. This study utilizes a linear programming model to determine the optimal cropping pattern while minimizing water usage in agriculture. This study's primary contribution lies in its dual approach: it identifies the optimal cropping patterns for a specified objective function through linear programming while simultaneously conducting a comprehensive analysis of these patterns by integrating considerations of food, energy, and water nexus.METHODS: The constraints applied in linear programming involve maintaining nearly the same agricultural revenue, conserving the total cultivation area, and limiting the change intervals in cultivation area by 5 percent. Using linear programming, crop patterns were determined for the periods of 2017, 2025-2050, 2050-2075, and 2075-2100. In each scenario, calculations were conducted to assess water consumption, energy demands, agricultural income, and carbon dioxide emissions, all framed within the context of the food-energy-water nexus. The various scenarios were subsequently analyzed to assess their effects. An evaluation was conducted regarding the sustainability of water usage in agricultural production.FINDINGS: All the scenarios examined resulted in lower water usage, reduced energy requirements, and decreased carbon dioxide emissions. Throughout various time periods, scenario 6, which permits a 5 percent variation in cultivation areas without imposing a total cultivation area limit, consistently proved to be the most favorable choice. It achieved an average reduction of 3.94 percent in water usage, 2.95 percent in energy requirements, and 1.62 percent in carbon dioxide emissions compared to the base scenario. Scenario 11, allowing for a 5 percent variation in cultivation areas while maintaining a total cultivation area limit, was evaluated as the second most effective scenario in terms of water conservation. It achieved an average reduction in water use of 3.45 percent, an average reduction in energy requirements of 1.85 percent, and a minimal reduction in carbon dioxide emissions of 0.11 percent across all time periods.CONCLUSION: The outcomes of this study reveal that the proposed model can play a crucial role in advancing sustainable agricultural management strategies. The obtained results indicate that significant reductions in water usage, energy requirements, and carbon dioxide emissions can be achieved simply by modifying the crop pattern, while agricultural income remains largely at the same level. The imposition of a constraint requiring the total cultivation area to be equal to or greater than that of the baseline scenario in the linear programming model has been found to restrict the extent of these reductions.

A major challenge facing sustainable agricultural production is that of selecting cropping patterns that observe the restrictions on such natural local capacities as soil, climate, and renewable water resources. This important issue has also been reflected with due emphasis in the state laws and national documents on water and agriculture as evidenced by the number of laws and national documents (13) approved/adopted on the cropping pattern issue, standing second only to that of “ Efficient use of water” (with 25 laws/documents). In this paper, a comprehensive analytical review and a SWOT analysis are initially conducted of the laws and national documents on cropping pattern practices before recommendations and suggestions are formulated for the practical implementation of a national cropping scheme at the state level. Among the important conclusions to be drawn from this review is that despite the legally binding requirements (such as The Enhancing Productivity in Agriculture and Natural Resources Sectors Act), no serious and effective measures have yet been taken in this filed except in such cases as greenhouse crop production and extraterritorial farming. In the few cases where actions have been taken, they have been mostly restricted to those within a specific sector in the absence of an integrated approach or coordination with other sectors or organizations involved. It is also observed that little attention has been paid in the relevant laws and regulations to capacity building and training on cropping pattern issues while the published research and field studies in the this area are quite scant as well. Another area neglected in the development of a national cropping scheme is the inclusion of indigenous and under-utilized crops in such schemes, or introduction of exotic crops with low water demand but high economic value for adaptation to the present climate at the state level that ensure sustainable agricultural production. Finally, a long time has elapsed since these laws and legal documents were adopted/passed during which time the climate has drastically changed and new farm technologies have emerged. These considerations necessarily require revisions in the existing laws and regulations or development of brand new ones.

Avoiding the negative effect of herbicide residues in soils on the growth of subsequent crops is especially challenging in intensive cropping sequences involving numerous crop species and short fallow periods between crops. For intensive rice cropping patterns in Bangladeshthe residual effect of six herbicides: glyphosate, pendimethalin, ethoxysulfuron-ethyl, carfentrazone-ethyl + isoproturon, isoproturon, and fenoxaprop-p-ethyl were investigated in the following crops of mungbean and mustard through plant bioassay approach. These herbicides in ten different combinations were applied to mustard, mungbean, summer rice, winter rice, and wheat in an on-farm Conservation Agriculture experiment, which was conducted for three consecutive years (2013–2016). No detrimental residual effects of any herbicides applied to the prior crops in the rotation were detected on the plant population, root, shoot growth, and chlorophyll content in the leaves of test crops. Moreover, plant biomass, seed production, and the germination rate of the harvested seeds of both crops were not hampered by the residues of tested herbicides. It is concluded that these six herbicides examined for controlling weeds in the prior rice, wheat, mustard, and mungbean crops under the minimum soil disturbance and crop residue retention could be considered safe for cultivating crops in the next season. Under the increased prevalence of herbicide use for controlling weeds in intensive rice-based cropping sequences in South Asia, the systematic assessment of herbicide residual risk to crops needs to be instituted as a routine practice in this region.

ABSTRACT Despite a wide range of components and criteria affecting travel behavior presented through empirical research, the results of these studies are inconclusive, which could be due to the difference between these components and criteria in the study areas. Therefore, this research presented a method to determine which factors in different physical developments affect travel behavior due to the differences in various physical developments. The required information was collected through 271 questionnaires at the level of three neighborhoods of Monirieh, Koye Bimeh, and Koye Golestan in Tehran, Iran, as the old, conventional, and new neighborhoods, respectively. ANOVA test was exerted to analyze the significant difference between different development patterns in three neighborhoods. Dunnett's T3 was applied to determine which neighborhood caused the difference between groups. Also, the factors affecting travel behavior were obtained based on exploratory factor analysis indicators. Finally, by comparing the results of the ANOVA test and regression analysis, it was discovered that factors such as car ownership, dependence and pro-liking for private cars, density and access to educational centers and parks, access to medical and service centers, and variety and density of retail stores had been introduced as the factors affecting travel behavior due to the differences in development patterns. However, proximity to the public transportation station, accessibility preferences in choosing a residence, dependence, and pro-liking for other than a private car, having a license, number of children under five years old, and age have influenced travel behavior regardless of the variation between neighborhoods. Extended Abstract Introduction Finding factors affecting travel behavior has been one of the main concerns of transportation planners. However, in the last two decades, the importance of the influence of the features of the built environment, including land use, along with demographic-economic characteristics, travel behavior, and attitudes of people, has been raised by urban planners. Studies seek to find factors affecting travel behavior, especially land use characteristics. Despite presenting a wide range of components and criteria affecting travel behavior, the results of the studies are inconclusive, which could be due to the difference between these components and criteria in the study areas. Therefore, this research presented a method to determine which factors in different physical developments affect travel behavior due to the differences in various physical developments. In order to do this, it must first be determined whether the study areas/different development patterns have a significant difference in terms of travel behavior or not. In case of a positive answer to the previous question, the following question is which study areas caused this difference. The next question arises: -Which physical and non-physical characteristics affect travel behavior due to distinctions between different development patterns?   Methodology The present research method is analytical and experimental based on quantitative methods. This research chose the frequency of travel by private car, public transportation, and walking as the travel behavior. According to the research's purpose, indicators and criteria affecting travel behavior were extracted after reviewing the theoretical and experimental literature. Then, the required information was collected through 271 questionnaires at the level of three neighborhoods of Monirieh, Koye Bimeh, and Koye Golestan as the old, conventional, and new neighborhoods, respectively. The questionnaire was compiled as a Likert scale in five parts of travel information, demographic-economic characteristics, perceptual characteristics of land use, travel habits, and access preferences of people in choosing their residence. ANOVA test was used to analyze the significant difference between different groups of a characteristic (here, different development patterns or the three case studies). Dunnett T3 was exerted to determine which neighborhood caused the difference between groups. Also, the factors affecting travel behavior were obtained based on exploratory factor analysis indicators. Finally, by comparing the results of the ANOVA test and regression analysis, it was discovered which factors affecting travel behavior were due to the differences in study areas and which factors affect travel behavior regardless of development patterns.   Results and discussion This research aims to identify the factors affecting travel behavior due to the differences in development patterns. In this regard, the findings in line with the first research question show that the frequency of three modes of travel, by private car, transportation, and pedestrian, differ significantly in the three neighborhoods. Furthermore, ANOVA test results depict that there is a significant difference between these three neighborhoods in terms of factors affecting travel behavior, such as perceptually environmental characteristics of the neighborhood, dependence and pro-liking for personal cars, variety and density of retail stores, density and access to educational units and parks, access to medical and service centers, and car ownership. Finally, by comparing the results of the ANOVA test with the regression analysis assessing the relationship between physical and non-physical factors (the same indicators in the same study areas) with travel behavior, the factors affecting travel behavior owing to different development patterns were identified. Factors such as car ownership, dependence and pro-liking for private cars, density and access to educational units and parks, access to medical and service centers, and variety and density of retail stores have been introduced as the factors affecting travel behavior due to the differences in development patterns. However, proximity to the public transportation station, accessibility preferences in choosing a place of residence, dependence, and pro-liking for other than a private car, having a certificate, number of children under five years old, and age have influenced on travel behavior regardless of the variation between neighborhoods (different physical development patterns).   Conclusion In In order to discover the factors affecting travel behavior due to the differences in patterns of physical development, this research has provided a more detailed analysis of the factors affecting travel behavior. It has achieved more accurate components than previous studies in this regard. Detailed analysis of studies related to travel behavior and finding the main components affecting it, considering the extent of variables and data, can pave the way for professionals in transportation planning and urban planning, in addition to providing detailed methods and criteria in the related literature.   Funding There is no funding support.   Authors’ Contribution Authors contributed equally to the conceptualization and writing of the article. All of the authors approved thecontent of the manuscript and agreed on all aspects of the work declaration of competing interest none.   Conflict of Interest Authors declared no conflict of interest.   Acknowledgments  We are grateful to all the scientific consultants of this paper.

With the intensification of the water crisis in the world, it has become necessary to pay attention to the concept of virtual water and water footprint in agricultural planning and policy-making, especially in countries located in arid and semi-arid regions. The agricultural sector in Iran, as the largest water consumer, will require serious attention to the concepts of virtual water and water footprint. The aim of this study was to reduce the water footprint of optimal patterns under the simultaneous goals of profit and risk compared to current cropping patterns. Also, consequences for not implementing the optimal cropping model in terms of benefits and water footprints were investigated. For this purpose, data of production cost, cultivated area and crops production of Varamin region has been used for the crop year 2017-2018. Also, the research method in this study was to estimate water footprint indices and goal programming models. The results of this study showed that in the equilibrium patterns of profit and risk, the net profit of farmers will increase by 10.8% and at the same time, the water footprint will decrease by an average of 5.5%. In fact, the footprint of blue, green and gray water in the current model of cultivation is equivalent to 52.45, 2.79 and 17.56 million cubic meters, respectively, and in the optimal model of profit and risk balance, it is equivalent to 51.60, 2.24 and 96, respectively. It was estimated to be 14 million cubic meters. Finally, the total water footprint in the two models was estimated to be 72.81 and 68.81 million cubic meters, respectively. Considering only 2% water consumption for the total need of industry and mining and saving 5.5% in water footprint in the country, by implementing the optimal model of profit and risk balance in the agricultural sector, in addition to earn more profit by farmers, more water can be saved than the industry's need. This amount of savings can be done by the government at no cost, and in fact, more benefits and less risk will encourage farmers to follow this pattern.

Statistical detection is a method to reveal significant changes that cannot be attributed to natural variations. The agricultural sector heavily relies on climatic parameters such as temperature and precipitation, thus demonstrating a higher degree of responsiveness to climate change with increased intensity and speed. Climate change can also influence the cropping patterns and agriculture of a region over a long period. To enhance the quantity and quality of agricultural production in Golestan Province, it is necessary to study the climatic background and precipitation and temperature regimes over a long period (at least 25 years) to examine the trend of changes. Therefore, the Mondal and Papadakis methods were utilized on statistical data from meteorological stations in the province to obtain suitable winter and summer cropping types for Golestan Province. The climatic data used in this research includes monthly average minimum, maximum, and mean temperatures, monthly average absolute minimum and maximum temperatures, and annual average temperature and precipitation from 9 meteorological stations in Golestan Province within the time range of 1990-2018, obtained from the National Meteorological Organization. The results of statistical analysis showed no significant changes in the cropping pattern of the region during the study period (1990-2017), which can be justified by the defined temperature thresholds of the Papadakis model. For instance, the dominant winter cropping pattern was dual-headed barley, which requires the average maximum temperature of the coldest month to be above 10 degrees Celsius, a threshold observed in the region during the statistical period, thus indicating the continued cultivation of this crop in the future. Additionally, the prevalence of maximum temperatures above 20 and 25 degrees Celsius in the region and the prolonged absence of frost during the season are reasons for the stability of dominant summer cropping types in this province.

Volumetric water delivery is one of the main components of the groundwater balancing plan. In the volumetric water delivery condition, the increase in farmers' income and the optimum use of water should be considered at the same time. The aim of this study was to determine optimum cropping patterns in agriculture wells under volumetric water allocation constraints in the Qazvin plain. In this research, 9 agriculture farms were studied and linear programming was used in the optimization process. The average water productivity in the formal cropping pattern (FCP), optimum cropping pattern with monthly water allocation (OCPM), and optimum cropping pattern with yearly water allocation (OCPY) was estimated at 5283, 9080, and 10570 Rials per cubic meter, respectively. The average productivity in the OCPM and OCPY has increased by 72% and 100%, respectively, compared to the FCP. Also, the average net benefits in the FCP, OCPM, and OCPY were estimated at 52978, 48275, and 88844 thousand Rials per hectare, respectively. The average net benefit in the OCPM has declined by 8.9%, and the average net benefit in the OCPY has increased by 67.7% compared to the FCP that mentioned in water licenses. The average water use in the FCP, OCPM, and OCPY was estimated at 10287, 5150, and 8501 cubic meters in ha, respectively. The average of water use in OCPM and OCPY has declined by 49.9% and 17.4% respectively. The results showed that the formal crop pattern that is mentioned in water licenses of agricultural wells requires a considerable revision and does not conform to volumetric water delivery (allocation) conditions.