Identifying the constraining factors of production and yield gap is very important. Therefore; this research was performed to identify the production constraining factors of local rice cultivars. All management practices from nursery preparation to harvesting stages for 100 paddy fields of local rice cultivars were recorded through field studies, in Sari, from 2015-2016. In the CPA, the actual and calculated potential yield were 4495 and 5703 kg/ha, respectively and the gap was 1221 kg/ha. The yield gap caused by number of top-dressing variables was 324 kg/ha, equal to 27% of the total yield gap. The yield gap related to previous year of legumes cultivation was 218 kg ha-1, equal to 18% of the total yield variation. Among the 10 variables entered in the CPA model, the effects of top-dress fertilizer application and its application frequency and foliar application were remarkable, which could compensate a significant part of the yield gap (444 kg/ha, 37% of total) in the farmers’ fields by managing these variables. According to boundary line analysis (BLA) finding, actual yield mean on the basis of optimal limit related to 12 variables under study was 5369 kg/ha, with 881 kg/ha yield gap . Mean relative yield and relative yield gap for 12 variables (transplanting date, seedling age, number of seedlings per hill, planting density, nitrogen and phosphorous per hectare, nitrogen before transplanting, harvesting date, lodging problem, pest problem, diseases problem and weeds problem) were 83.64 and 16.35 kg/ha, respectively. Based on the finding, it can be stated that the model precision is appropriate and can be applied for both estimation of the quantity of yield gap and determining the portion of each restricting yield variables.

Background and Objectives: Food security is a main subject in the world. Many international and governmental organizations to ensure the nutritional needs of human are being explored. According to the restrictions on agricultural lands, an increase in production per area unit is a way to improve food security. Despite high yielding varieties, these varieties do not reach their potential yield due to lack of access to favorable environmental conditions. Therefore, yield gap will be created between potential yield and actual yield. Before any progress in the agronomic operations of crop, it is necessary to identify the crop’ s potential yield and to calculate the gap between potential and actual yield. Therefore, the aim of this study was to evaluate the historical trend in different yield gaps and to calculate different mean yield gaps in the studied region. Materials and Methods: Potential and conventional yields were simulated using CropSyst model over 1981-2008 period and researchers’ potential yields over 1994-2008 period, maximum achievable yield over 1989-2008 period and actual yield over 1981-2008 period were collected from Agricultural Research Center, and Agriculture Organization. In this study, four types of yield gap were calculated as the difference between simulated potential yield and actual yield (yield gap 1), the difference between researchers’ potential yield and actual yield (yield gap 2), the difference between maximum achievable yield and actual yield (yield gap 3) and the difference between the simulated conventional yield and actual yield (yield gap 4). Results: The trend of changes in actual yield compared with both simulated potential and conventional yields over 1981-2008 period showed the gap between simulated potential and conventional yields with actual yield were decreasing. The decrease in the yield gaps was due to decrease in the trend of changes in simulated potential and conventional yields and increase in the trend of changes in actual yield over the studied period. According to the results, to increase the simulated potential yield, the varieties should be selected which have high radiation use efficiency. While for reducing the yield gap between simulated conventional yield and actual yield, the varieties with high radiation use efficiency should be cultivated under unlimited water and nitrogen condition. The trend of changes in yield gap between researchers’ potential yield and the actual yield was fixed yields over the period of 1994-2008 which was due to unchanged trend of both yields over this period. The trend of changes of the gap between actual yield and maximum achievable yield was increasing over 1989-2008. This was indicated the better management operations of prior farmers to achieve maximum yield, while other farmers did not work hardly to enhance the yield over the studied years. The simulated mean potential and conventional yield, the researchers’ potential yield, the maximum achievable yield and the actual yield were 6. 35, 6. 6, 6. 0, 4. 42 and 3. 4 t ha-1, respectively, over 1994-2008 period. The differences between these yield levels with the actual yield were about 3. 0, 1. 0, 3. 2 and 2. 6 t ha-1. Conclusion: It can be concluded that the difference between the management operations performed for achieving actual yield and the other yield levels can be created a yield gap and the more management differences, the higher yield gap.

IntroductionAs suitable agricultural land for increasing crop production is decreasing, while the expansion of agricultural land is associated with irreparable damage to the environmen, intensifying sustainability in existing agricultural land is the only way to increase production to meet the increasing demand for food resources. Therefore, investigating the biophysical limitations on yield and estimating yield gaps  in the cultivated lands, as well as reducing this gap, is one of the ways to increase the yield per unit area. After soybean, rapeseed is the world's second produced oilseed. Ilam province is one of the most important oilseeds producer regions of the country, including rapeseed, and about 80% of the rapeseed crop of this province is produced in the border city of Dehloran, and this city is one of the pioneer cities and the main pole of rapeseed production in the province. Therefore, according to the importance of rapeseed in Deholran city, this study was conducted with the aim of determining the limiting factors of rapeseed production in Dehloran. Materials and MethodsIn the present study, all the management operations were performed from seedbed preparation to harvesting in 51 farms were recorded through field studies during the years 2021 to 2022. In this study, the yield gap was estimated by the method of yield comparison analysis and borderline analysis, and to determine the yield model, the relationship between quantitative and qualitative variables was measured and yield was evaluated by step-by-step regression method. Results and DiscussionDetermining the limiting factors on rapeseed production in the studied area showed that there was a gap between the actual yield of farmers and the yield predicted by the model of about 833.54 kgha-1, which was the contribution of the variables of potash fertilizer consumption, sulfur consumption, and the number of irrigations. The consumption of micronutrients from this yield interval was equal to 102.99, 118.56, 442.20 and 169.79 kgha-1, which is equivalent to 12.36, 14.22, 53.05 and 37, respectively. 20% of the total yield gap was observed. Gap analysis of rapeseed yield showed that the number of irrigations alone accounts for 53% of yield reduction compared to attainable yields.ConclusionAs, there is a need to irrigate the field in the very early planting date in October, it seems that with better management of rapeseed for this planting date in the region, the occurrence of drought stress can be reduced to the plant and to some extent fill the gap in the existing yield. In addition, 57% of the yield gaps in the region were related to the use of potash, sulfur and micronutrient fertilizers, which can be easily removed this limitations in the fields.

Context and purpose. Obtaining the private GAP standard for healthy product certification due to costs is out of reach in many small and mediumsized farms among smallholder farmers. GroupGAP has provided a much-anticipated alternative where operators and farmers' cooperatives can pay the cost of certification on a cost-sharing basis. Therefore, the purpose of this research was to explain the development strategies of GAP standard with emphasis on GroupGAP in the rice production system of Mazandaran province. Methodology/approach. Current research is qualitative and data analysis was conducted in the grounded theory method, during a three-stage process of open coding, central coding, and selective coding. The data collection tool included an in-depth and semi-structured interview with a qualitative content analysis technique, which was analyzed through Maxquda software. The statistical population of the research was 18 experts and specialists of the Agricultural Jihad Organization and managers of the Rice Farmers Cooperative Company of Mazandaran Province, who were selected by the purposeful sampling method. Findings and conclusions. After extracting the concepts of the content analysis of the interviews, 9 conceptual codes out of 30 initial codes were identified in the first stage of coding. After refining and merging, the codes were classified into 3 subcategories. These components include the group certification system, the development of publicGAP programs and the development of private GAP. In the group certificates, the two dimensions of contract system development and guaranteed purchase, the development of the cooperative company for the production of healthy products have been taken into consideration. It is recommended to strengthen the organizations and cooperatives of farmers and exporters, especially to strengthen young farmers and women organizations. Originality. Originality/innovation: Due to the importance of the GAP standard issue and farmers' problems in providing the audit fees and establishment of GAP certificate, so far, no comprehensive study has been carried out in Iran on the development of operational strategies for the establishment of GAP and GroupGAP. Therefore, the current research is an attempt to provide a useful framework in explaining GAP standard development strategies with the participation of farmers in adopting the government, private, group and cooperative certification system.

Long term weather data including temperature and radiation in Northern, Razavi and Southern Khorasan provinces were collected and used for agroecological zonation of wheat over the whole province. Weather data after spatial interpolation between stations and generation of daily values were used as inputs of a model for simulation of wheat growth and yield. The WOFOST model that showed acceptable performance during validation for predicting yield and development stages of wheat cultivars under favourable growth conditions, was used for estimation of potential (climatic) yield of wheat. The results showed that in spite of inter annual variations, mean potential yield of wheat was 6.2, 6.9 and 4.8 t ha-1 for Northern, Razavi and Southern Khorasan provinces, respectively. Actual wheat yield (harvestable yield) during a 10-year period from 1375 to 1385 was calculated as the average of the whole period and mean of the last 3 years of time series in each province. On this basis yield gap was estimated as the difference between potential and actual wheat yield. A regional yield factor was also calculated from the ratio of actual: potential yields. Yield data was stored in a GIS package and zonation maps were produced. Results indicated that mean actual wheat yield during the 3-year period of 1383-1385 compared to the 10-year period of 1375-1385 was increased by 28, 34 and 30% in Northern, Razavi and Southern Khorasan provinces, respectively which could be mainly due to improved management practices and introducing new cultivars. However, a relatively high yield gap of 3.7, 4.3 and 3.8 t ha-1 was estimated for Northern, Razavi and Southern Khorasan provinces, respectively. Regions with higher yield potential showed a higher yield gap and regional yield factor of wheat in Razavai and Southern Khoransan provinces with the highest and the lowest yield potentials was estimated as 0.37 and 0.42, respectively. During the period of 1383-85 in all 3 provinces the actual yield reached to the 50% of the potential yield indicating that the yield gap of wheat has been bridged due to improved management practices.

In order to investigate the possibility of quinoa producing in Garmsar, Iran, a factorial experiment conducted in randomized complete block design with three replications in 2018-2019 growing season at Garmsar Agricultural Research Station. The factors were planting date at three levels (March 6th, April 1st and April 6th) and the three genotypes of quinoa (Q26, Q29 and Titicaca). Results showed that the effect of planting date was significant for all studied traits except the harvest index. Also, all studied traits were significantly different in all genotypes. Titicaca planted on March 6th had the highest yield (2276 kg.ha-1).The grain yield and yield components decreased with the delaying the planting date. Compared to early plantings, Latest date, April 6th, led to reduction of all traits, especially grain yield (about 50%). The results of simple phenotypic correlation between the studied traits showed that grain yield per hectare had the highest correlation with plant yield (0.877) and then with leaf area index (0.832), panicle weight (0.815) and number of branches per plant (0.745) that was significant at the 1% probability level.

Introduction: Due to limited water resources, increasing water productivity is very important to achieve water security and food security. One of the basic measures in this area is to determine the difference in product performance between the current situation and the potential situation. Methods: Crop potential yield is one of the parameters that can be used to calculate the yield gap and manage water and soil resources based on the factors affecting production. In this study, the potential yield of major crops in the composition of irrigation network in Qazvin plain has been determined by Agricultural Ecology method. Findings: The results showed that the yield gap in the crop composition of major crops in Qazvin plain was 3339 (kg / ha). Also, the average yield gap due to the composition of cultivation, yield gap of each crop and the area under cultivation of crops in the irrigation network of Qazvin plain, was 26. 23%. The results of estimating the potential yield at the level of the irrigation network of Qazvin plain show that not all crops have reached the achievable yield level (75 to 85% of the potential yield) and there has been high yield in crops such as sugar beet, tomato and alfalfa. Also, the research findings showed that the yield gap of strategic wheat crop in the irrigation network of Qazvin plain was 1502 kg / ha. One of the most important achievements in calculating potential performance is to obtain performance differences in different products in the region. Using such data, agricultural management of different crops in an area can be evaluated and finally the priority of cultivation of each crop can be explained. Quantification of production capacity per hectare of farms is needed for decision-making, research, development and investment, and to assist local farmers in farming decisions. In this regard, yield vacuum analysis provides a small estimate of the potential increase in production capacity for a given area.

Background and objectives: Wheat has an important role in feeding the people of world and Iran as well. It provides around 40 percent of edible energy and protein for people in Iran. Closing yield gap can increase wheat production, significantly. The first step of closing yield gap is to quantify the yield gap at a given region or country. The amount of wheat yield gap hasn’ t been measured for whole Iran by a global standard protocol so far. The aim of this study is to estimate irrigated wheat yield gap for Iran based on the global yield gap analysis (GYGA) protocol. Materials and methods: GYGA protocol suggested a method to calculate yield gap on a large scale like a country. Based on this protocol, at first the area covered by each weather stations were specified. Second, the main weather stations where cover irrigated wheat lands were selected named reference weather stations (RWS). Third, irrigated wheat potential yield was estimated by SSM-iCrop2-wheat simulation crop model within the RWSs. The actual irrigated wheat yield was calculated for each RWS based on GYGA protocol as well. Forth, amount of the actual and potential yield was calculated for whole country by using the values calculated for the RWS according to GYGA protocol. Finally, the yield gap was calculated by difference between potential and actual yield for the country. Results: The results of this study showed that average irrigated wheat in Iran was 3. 4 ton/ha, average potential yield was 8. 8 ton/ha and average yield gap was 5. 4 ton/ha (62%). At the moment, irrigated wheat producers just use 38 present of the existing wheat cultivars and environment potential. There was no significant relationship between climate in the irrigated wheat production RWS and irrigated wheat yield gap (based on percent) in Iran and the yield gap was around 62 percent in all the RWSs. If farmers could reach 80% of potential yield of their locations, by improving agronomy practices, average irrigated wheat would reach 7 tons/ha and there is around 2. 2 million ha irrigated wheat area in Iran. Thus, average wheat production in irrigated condition would increase from 7. 5 million tons to 19. 8 million tons. Conclusion: Owing to existing wheat cultivars and climates in the main irrigated wheat production RWS in Iran, there is a big yield gap of wheat in Iran. The low actual irrigated wheat yield in Iran (3. 4 tone/ha) can be attributed to the poor management condition because the existing cultivars and climates have no limitation to reach the yield around 8. 8 tone/ha. There are many factors to reduce the yield such as poor seedbed preparation, late planting date, weeds, pests and diseases, nutrition’ s deficits, fertilizer amount and timing, irrigation amount and timing etc. If we want to close the yield gap, we have to identify the reasons of yield gap in a given region.

Introduction: To realize global food demand by 2050 world cereal production should be increased up to 49% compared to 2006. This level of production could be achieved by annual yield increment of 1. 16%. However, the current rates are much lower. At the same time, there is a very restricted area to increase cultivated lands because of resource limitation, provided that increase in crop yields is the main option to sustain food security. Potential yield (YP) could be achieved when limiting and reducing factors are completely absent during crop growth. YP is an indicator for the yielding capacity of a given environment and management system and estimating the difference between YP and actual yield, known as yield gap, is crucial for improvement of crop production systems at regional or national scale. In this study yield gap and its temporal trend for sugar beet, irrigated and rainfed wheat are estimated over Khorasan Razavi province based on the method developed by Global Yield Gap Atlas. Materials and Methods: Following the protocol provided by Global Yield Gap Atlas, Khorasan province was clustered into agroclimatic zones using the proposed indices (cumulative degree days above 0 º C, aridity index and temperature seasonality) based on 10 years (1384-1393) weather data. YP of sugar beet and irrigated wheat for the study period in the climatic regions was first estimated for selected cities within each region using LINTUL model and finally the simulation results were up scaled from cities to region and from regions to the whole province. The model was cross-validated against measured data using leave-one-out (LOO) method to increase accuracy of predictions. Potential yield of rainfed wheat (YW) was estimated from frontier production function which was fitted to yield data over a wide range of annual precipitation. Yield gap (YG) of the studied crops was estimated as the difference between potential (YP) and actual yields (YA) for each region and over the 10-year period. In addition exploitable gap (YG85%=85%YP-YA) was also calculated. Results and Discussion: The accuracy of LINTUL model for simulation of sugar beet and irrigated wheat yields was considerably increased after cross validation and the prediction error was reduced by 6. 5-7. 8%. Mean YP of irrigated wheat in the climatic region 1 (temperate, semi-dry), 2 (hot, dry) and 3 (temperate, dry) was respectively, 7248, 6478 and 7852 and for the whole province 6936 kg ha-1. Time trend of YP for irrigated wheat was not significant in 3 climatic regions however, high annual variation of YP was found over the studied period. Results indicated that up to 74% of this variation was accounted for by changes in the effective grain filling period in response to temperature. YG85% of irrigated wheat in all climatic regions was increased up to 4 t ha-1 during 1384-1388 but decreased later on so that relative gap was 0. 48-0. 50 of YP in 1993. Average YW of rainfed wheat in the climatic regions of the province was estimated as 2000-2800 kg ha-1 with a negative trend due to decreased precipitation, the highest negative slope in YW (59 kg ha-1 y-1) was found in the hot dry region. Rainfed wheat showed an extremely high yield gap in all climatic regions and mean relative yield gap (YG/YW) was estimated as 0. 75-0. 80 over the province. Mean YP of sugar beet in different climatic regions of the province was estimated from 78 to 88 t ha-1 with the lowest potential in hot-dry region. However, declining trend was found in the yield gap of sugar beet in all studied regions with the highest gap filling rate of 1. 44 t ha-1 y-1 in temperate-dry region. Conclusions: Simulated YP of sugar beet and irrigated wheat were higher in temperate-semi arid regions of the province and lower in hot-dry regions. However, cold-semi arid regions had the highest YW of rainfed wheat. When up-scaled over the province, YG85% was about 50% of YP for irrigated wheat and sugar beet and 25% for rainfed wheat. It was concluded that closing yield gap of sugar beet and irrigated wheat would be possible mainly by improving management practices however, for rainfed wheat breeding strategies should be considered as the first priority.

Maize (Zea mays L.) is the most important silage plants in the world because of its high yield, energy and quality of forage and low fiber. Due to the severe water deficit in Iran and the high water demand of maize plant, the only way to increase maize production is to increase the yield per unit area and reduce the yield gap by optimizing production management. Therefore, this study was aimed to estimate the yield potential and gap in the main forage maize production areas of Iran. For this purpose, GYGA protocol method was used. Yield potential based on the data from a 15-year period (2001-2015) was calculated using the SSM-iCrop2 simulation model. First, parameterization and evaluation of the simulation model for the studied plant were performed using data from all over the country. In the major maize production regions of Iran, 27 reference weather stations (RWS) and 11 main climatic zones (CZ) were selected. The average Ya and Yp of maize in Iran was estimated at 49.3 and 85.6 T/ha-1, respectively. Furthermore, in the major climatic zones was 9.9 T/ha-1yield gap in the country. In fact, forage yield and production in Iran can be increased from current 49 T/ha-1and 11.2 million tons to 68 T/ha-1 and 15.6 million tons through optimized management and elimination of exploitable yield gap.