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The first step to achieving ecological sustainability and intensification in agricultural systems is to have a comprehensive agroecological analysis of agricultural systems. This research analyzed the agroecological ecosystem of potato cultivation in the Torbat-e Heydariyeh Region of Iran over fifteen years (2001-2016). Based on the results, potato yield increased by 0.28 t ha-1 yr-1. The average potential yield of potato was calculated by the FAO method to be 64 t.ha-1. Also, the potential yield did not increase significantly during the study period. The average yield gap of potato was calculated to be 32.44 t ha-1. Also, with increasing yield, the yield gap showed a decreasing trend. The ecosystems experienced a steady rise in intensification, and the stability decreased. It was observed that although nitrogen fertilizer application was increased, its efficiency dropped from 110 kg tuber per kg of nitrogen fertilizer to 70 kg. Due to the decreasing trend of NUpE (Nitrogen uptake efficiency) and NUE (Nitrogen use efficiency) during the studied years, the NUE gap was the main factor in increasing nitrogen consumption, increasing intensification, and reducing stability in the studied systems. Therefore, changing the management method to increase the efficiency of nitrogen consumption can be suggested as the first step for moving towards ecological intensification and improving the sustainability of potato production systems. [ABSTRACT FROM AUTHOR]

Objective: The present study was conducted in order to estimate the yield gap of faba bean in the main production areas of this plant in Golestan province, including Gorgan, Ali Abadkatol and Aq Qola cities, and to identify the factors that cause it and to determine the contribution of each of them. Methods: Based on this, the information related to the production management of 445 faba bean farms in Gorgan, Aliabadkatol and Aqqola regions in 1398-1399 and 1399-1400 was collected and the yield gap was estimated using the comparative performance analysis (CPA) method. Results: The average, maximum, and gap yield of faba bean seeds were 2742, 4000, and 1258 kg per hectare, respectively. Additionally, based on the results obtained, the most important reasons for the yield gap and the contribution of each of them in creating the yield gap were: planting date 21%, pests 15 percent, the amount of pure nitrogen (N) 14 percent, the number of disc times 14 percent, the amount of seed used 12 percent, diseases 12 percent, waterlogging 5 percent, weeds 3 percent, non-use of working row 2 percent and improper planting depth 1 percent. Conclusion: In general, by optimizing the management of faba bean production and eliminating the mentioned factors of yield gap, it is possible to increase the yield of faba bean in the regions of Gorgan, Ali Abadkatol and Aq Qala of Golestan province by 46 percent (equal to 1258 kg per hectare) compared to the current amount increased. [ABSTRACT FROM AUTHOR]

Introduction: Feeding the Iran's over than 90 million people has been recognized as one of the most important challenges of country in 2050; so we need to increase yields of crops in cultivated areas. Mostly the actual yields obtained by farmers are less than the potential yields of the region, due to management, climatic, nutrients, soil properties, weeds and/or other living and non-living stress factors. The differences between these potential yield levels and actual farmers' yields define the yield gaps, and precise spatially explicit knowledge about these yield gaps is essential to guide sustainable intensification of agriculture. The goal of this experiment is finding of limiting factors that affected the wheat yield and then reduce the yield gap between potential and actual yields of farmers in the fields of Abarkooh city located in Yazd province. Materials and Methods: Eleven wheat farms were selected with the coordination and consultation of agricultural service centers in different regions of Abarkooh counties. Soil samples were prepared from all farms before planting. All agricultural operations performed by farmers such as tillage methods, planting date, cultivars used, seed rate, cultivation area, crop rotation, fertilizers used and fertilization time, irrigation operations, pest and disease control, weeding and/or spraying herbicide and harvest methods were noted or measured. At the end of tillering phase and harvest time, soil was sampled and its nutrients, organic matter and salinity were determined. At harvest time, samples were taken from different parts of the field by one square meter plots and 10 plants were randomly selected to measure yield components. The farmer's performance with the combine was also recorded based on the farmers' claims and the approval of the local expert. Nitrogen, phosphorus and potassium levels were measured in grain, straw and soil after harvesting operation. Meteorological data were collected daily from the Abarkoh weather station. The potential yield of region was calculated using regression model and the difference between obtained yield and potential yield was considered as yield gap. Eighty percent of potential yield is also considered as exploitable yield. Using step-by-step regression, the most effective factors in yield reduction were identified and a suitable regression model was fitted for these variables against grain yield. Then, the degree of influence of each variable was determined using Comparative Performance Analysis. Results and Discussion: The results showed that the average yield obtained from these farms was 5040 kg/ha and the yield gap was 4659 kg/ha, of which 2721 kg can be attainable. The order of the importance of agricultural operations in reducing yield in the form of insufficient number of irrigations (24 percent), lack of crop rotation with pulses (18 percent), low consumption of nitrogen fertilizer (16 percent), the method of preparing the cultivation bed and plowing times (12 percent), lack of manure fertilizer consumption (12%), improper weed control (11%), improper planting date (4%) and insufficient nitrogen split (3%). The analyze of grain yield components also showed that the share of the number of spikes per square meter, number of seeds per spike, 1000 kernel weight and harvest index in yield reduction are 39, 24, 12 and 25% respectively. Conclusion: Based on the results obtained, we can to define an optimal crop management: enough irrigation (10 times), rotation with legumes, use enough nitrogen fertilizer, use animal manure to increase soil organic matter, plowing in summer and autumn, weed control, proper planting date and Nitrogen split 3 times. Considering that management factors mentioned above have mutual effects on each other and cannot cause a significant yield increase alone, therefore, in order to have a successful agriculture, it is necessary to act on the basis of a suitable management package. [ABSTRACT FROM AUTHOR]

China is the largest soybean-consuming country in the world, but its self-sufficiency rate (SSR) of 16% is very low and it therefore has to heavily rely on imports. To solve the soybean dilemma in China, it is necessary to examine the maximum amount of soybean that could be grown on the land currently used, how much land could reasonably be used to expand soybean acreage, and whether China could sustainably increase soybean self-sufficiency to reduce the risks of import reliance. To answer these questions, our paper presents a high-resolution spatial analysis of potential soybean production in China using primary data of weather and crop production practices that govern this potential. We employed a "bottom-up" scaling protocol to estimate gaps between potential yield with optimal management and current yields in three major soybean-planting regions, namely, Northeast China, Central China, and South China. We found that current soybean yield gap (Yg) in China is 49% and 45% of potential yield under irrigated and rainfed cropping systems, respectively. By closing the yield gap, Northeast China could provide additional soybean production equivalent to 32% of the current national total. Our results show that SSR could only be increased to 21–23% in 2030 by Yg closure alone but could be increased to a maximum of 52% by combining Yg closure and a reasonable area expansion. Even so, at least 61.08 million tons of soybean accounting for 38% of global soybean trade would still need to be imported to meet future domestic demand. We discuss strategies for soybean production increase based on Yg closure in the most valuable areas and cropland expansion in a sustainable manner in order to increase SSR as well as lessen the import pressure on the global market. [ABSTRACT FROM AUTHOR]

Rising temperatures and more frequent droughts caused by global climate change reduce yields and increase climate risk, especially in rain-fed agriculture. Together with scarce land and water resources, this poses a serious threat to food security. Field experiments have shown that relay intercropping systems under irrigated conditions can improve productivity. However, little is known whether these improvements could also be obtained with simultaneous intercropping in rain-fed agriculture under water-limited conditions. To investigate this question, we analyzed a maize/soybean simultaneous intercropping system, using a modeling approach. A light interception model for strip intercrops was implemented into the APSIM classic model for simulating crop growth and yield in strip-intercropped maize and soybean and then calibrated and validated using field experiments conducted from 2017 to 2019 at 4 sites in Northeast China. We then ran a simulation using climatic data (1961–2020) from these sites. Model validation showed good agreements between observations and simulations. The results obtained from our simulation over the period from 1961 to 2020 showed that intercropping was predicted to increase total yields by 41.3% and subsequently enhanced total economic revenue by 23.8% compared to sole systems. It also reduced yield gap of maize by 33%, soybean by 56%, and the system by 45%. Attainable land equivalent ratio (LER) under rain-fed conditions was 1.27 over 60 years across the 4 sites, with a relative yield gain of maize of 0.35 and a relative yield loss of soybean of 0.08. Attainable LER was higher than potential LER. Yields and LER were significantly higher between 1991 and 2020, indicating a potential increase in land productivity with intercropping under a warming climate. Our results thus suggest that simultaneous intercropping offers great opportunities for yield enhancement in rain-fed agriculture under global climate change. [ABSTRACT FROM AUTHOR]

IntroductionPulses play an important role in supplying human food and are a major source of protein in developing countries, so they have a special role in producing food in these countries. Peas (Pisum sativum L.) belongs to legume family and is well adapted to the cold climate. This plant has a lot of crude protein and starch and is therefore high in energy. Evaluating the status of pulses production is essential because of their importance in feeding the people of the world and their role in the design of cultivation patterns. Eliminating the gap between the yield currently achieved on farms and the yield that can be achieved by using the best environmentally adapted varieties and the optimum water, soil and plant management techniques is a key strategy to overcome the nutritional challenge of a growing global population. In recent years, due to concerns about food safety issues, studies on the issue of yield gap have also been increasing worldwide and it is necessary to estimate the yield gap and its causes using appropriate methods. Therefore, the present study was conducted to determine the yield gap of peas and determine the limiting factors and their contribution to the yield gap in pea farms in Gonbad kavus. Materials and MethodsThis study was carried out in pea farms (40 farms) during 2017-18 in Gonbad Kavus, Golestan province. The required information about farms was completed through observation, questioning of farmers or measurement. Information on soil properties was obtained using digital maps available at the Agricultural Jihad Office of Gonbad Kavus. Comparative performance analysis (CPA) method was used to determine the yield gap rate and to identify its causes. In this method, the relationship between all measured variables (quantitative and qualitative) and yield was evaluated using multiple regression. In this section, first, we used stepwise method to determine which variables should be included in the final production model. The average yield was calculated by placing the observed variables (x) of the studied farms in the yield model. The maximum yield obtained was then calculated by placing the best observed value of the variables in the model. The discrepancy between these two functions was considered as the performance gap. The ratio of yield gap for each variable to total yield gap represents its contribution in the yield gap and was expressed as a percentage. Results and DiscussionThe actual and potential yield calculated by the model were estimated to be 7941 and 17708 kg/ha, respectively, and yield gap was 10078.7 kg/ha. The reasons for this yield gap were as follows: Seed rate (19.56%), Nitrogen rate (17.04%), Frequency of herbicide application (15.02%), amount of available potassium in soil (34 (13%), soil organic matter (12.81%), amount of available phosphorus in soil (11.87%), farmer experience (10.36%). Therefore, it seems that with proper management of farms and taking into account the yield gap factors mentioned above, the yield of peas in Gonbad kavus can be increased to about 10078.7 kg/ha in comparison with current yield. ConclusionBased on the results in 40 farms studied, out of 45 variables studied, the final model was selected with seven independent variables. In the yield model, the actual and potential yield of farms calculated by the model were 7941 and 17708 kg/ha, respectively, and the yield gap was 10078.7 kg/ha. The recommendations of this research are based on the findings of the mentioned years in the region. Obviously, these recommendations may change in the future with changing farming systems (such as extension of conservation agriculture), agricultural management and possibly climatic conditions. In addition, by modifying the first-order causing factors of the yield gap discussed in this study, the second-order factors will emerge. Therefore, monitoring and evaluation of crop management in farms should be carried out on a continuous basis and the yield gap and its causes identified and resolved. In this study, among all the common agricultural management of farms, the cases that have the most impact on the yield gap and need to be modified and improved in the first stage are identified.

A yield gap analysis for rapeseed (Brassica napus L.) is critical to meeting the oil demand by identifying yield potential and yield constraints. In this study, potential yield (Yp), attainable yield (Yatt), and actual yield (Yact) for winter rapeseed were determined in five different zones of China. A boundary line approach was adopted to calculate Yp, based on a large-scale field experimental database. A meta-analysis was conducted on the data obtained from 118 published studies to evaluate the effects of agronomic factors on rapeseed yield. The main results indicated that farmers only achieved 37–56% of the yield potential across the zones. The low altitude areas (L-URY) and lower reaches (LRY) of the Yangtze River Basin (YRB), China had high yield levels. The total yield gap was 1893 kg ha–1, due to the agronomic management factors, environmental factors, and socioeconomic factors. The meta-analysis showed that weed control and drainage were the best management practices to improve yields (45.6 and 35.3%, respectively), and other practices improved yields by 17.1–21.6%. Consequently, to narrow the yield gap over the short term, the study could focus on techniques that are easily implemented to farmers.

Black gram, a pulse, is one of the major export crops in Myanmar. Because of a decline in the maximum possible yield of this crop in farmers' fields, a yield gap exists between potential and farmers' actual yields. Reducing the gap between actual and potential yields is critical for increasing crop production. This study was carried out to generate yield gap mapping, and to investigate the reasons responsible for this yield gap in black gram production. An annual survey was carried out to determine farmers' actual yield at Kyee Inn Village, Pyinmana Township during October 2017 and 2018. Drone photos were consolidated and prepared for digitizing and analyzed with Pix4D software. ArcGIS 10.7 software was used to map the spatial distribution of the yield gap of black gram in the selected area. Yield gaps of black gram with a range of 0.02 t ha-1 to 2.70 t ha-1 in the two consecutive years were observed. The yield gap between potential and farmers' actual yields (Yield Gap I) was greater in 2018 compared to the 2017 season. The gap between the yield obtained through an organized farm trials and the yield harvested by the farmers (Yield Gap II) was also larger in 2018 than that for the 2017 crop season. A technology gap for the variety Yezin-6 (0.68 t ha-1) was observed in 2018 whereas there were no gaps for Yezin-2 and Yezin-5 in 2017 and non for these varieties in the 2018 post-monsoon season. The reasons these large yield gaps may exist, is probably due to differences in crop management practices used at the experimental stations and those by farmers. The results of this study should provide useful information for policymakers, researchers, extension agents, and other stakeholders to upgrade a location-specific package of practices and increase crop yield by supporting technological solutions and training for the farmers. [ABSTRACT FROM AUTHOR]

Objective: To determine potential and water-limited yields in oil palm producing areas in the State of Tabasco, México. Design/Methodology/Approach: The ERIC III v. 3.2 database (IMTA, 2009) was used to select climatological stations with daily precipitation and maximum and minimum temperature records, going back to more than 20 years. The methodology proposed by the FAO and improved by Fischer et al. (2012) was used to estimate the potential yield. The equation reported by Ruiz-Álvarez et al. (2012) was used to estimate the annual water deficit from the climatic water balance. Results: The average potential yield of oil palm with a high level of inputs varies from 35.8 to 40.6 t ha1 of fresh fruit bunches. The average water-limited yield can vary from 15.6 to 23.5 t ha1 in plantations of at least 8 years of age, under rainfed conditions. The reduction in the maximum average attainable yield was the result of 19.2-49.5% soil moisture deficits. Study limitations/Implications: In order to determine their impact on potential and water-limited yields, climate change horizons must be included in future studies; this would enable researchers to establish the future theoretical economic profitability of the crop. Findings/Conclusions: The analysis between the yields indicates that --if the gap between the current yields and water-limited yields is closed-- output and percentage would be 6.5-14.4 t ha1 and 72.8-129% higher than the potential yield. [ABSTRACT FROM AUTHOR]

The potential yield of crops is not usually realised on farms creating yield gaps. Methods are needed to diagnose yield gaps and to select interventions. One method is the boundary line model in which the upper bound of a plot of yield against a potentially limiting factor is viewed as the most efficient response to that factor and anything below it has a yield gap caused by inefficiency of other factors. If many factors are studied, the cause of the yield gap can be identified (yield gap analysis, YGA). Though the boundary line is agronomically interpretable, its estimation and statistical inference are not straightforward and there is no standard method to fit it to data. We review the different methods used to fit the boundary line, their strengths and weaknesses, interpretation, factors influencing the choice of method and its impact on YGA. We searched for articles that used boundary lines for YGA, using the Boolean "Boundary*" AND "Yield gap*" in the Web of Science. Methods used to fit boundary lines include heuristic methods (visual, Binning, BOLIDES and quantile regression) and statistical methods (Makowski quantile regression, censored bivariate model and stochastic frontier analysis). In contrast to heuristic methods, which in practice require ad hoc decisions such as the quantile value in the quantile regression method, statistical methods are typically objective, repeatable and offer a consistent basis to quantify parameter uncertainty. Nonetheless, most studies utilise heuristic methods (87% of the articles reviewed) which are easier to use. The boundary line is usually interpreted in terms of the Law of the Minimum or the Law of Optimum to explain yield gaps. Although these models are useful, their interpretation holds only if the modelled upper limit represents a boundary and not just a particular realization of the upper tail of the distribution of yield. Therefore, exploratory and inferential analysis tools that inform boundary characteristics in data are required if the boundary line is to be useful for YGA. Statistical methods to fit boundary line models consistently and repeatably, with quantified uncertainty and evidence that there is a boundary limiting the observed yields, are required if boundary line methods are to be used for YGA. Practical and conceptual obstacles to the use of statistical methods are required. Bayesian methods should also be explored to extend further the capacity to interpret uncertainty of boundary line models. • The boundary line model for the yield gap can be interpreted under different agronomic hypotheses. • Boundary lines are widely-used for yield gap analysis but there is no standard method as yet. • Heuristic methods are more widely-used than statistical models, with no formal account of uncertainty. • Consistent methods for outliers, and exploratory examination of the proposed boundary are needed. • Agronomists need user-friendly software which encodes repeatable and robust boundary line methods. [ABSTRACT FROM AUTHOR]

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The present study has been conducted to evaluate the factors, limiting wheat yield in Kalaleh County via Comparative Performance Analysis (CPA) Method during 2015-16. The required information has been collected through fieldwork, along with personal interviews with the farmers. As a result, sixty wheat fields are selected in dry land areas of Kalaleh so that sufficient diversity could be maintained for all crop management, planting, crop protection, and harvesting areas. The amount of grain delivered to the wheat shopping centers has been recorded after determining the amount of drop as the final yield of the farm. Results from the yield model show that there has been a difference of 4071.7 kg between attainable (7248 kg/ha) and actual yield (377.4 kg/ha). Among the studied variables, the farmer experience, seeding rate, the amount of phosphorus in the soil, frequency of fungicide use, organic matter of the soil, amount of potassium absorbed in the soil, and the amount of applied nitrogen have influenced the wheat yield gap of the study area the most. These have been 19.4%, 16.8%, 14.9%, 14.3%, 12.7%, 11.7%, and 10.3% of the achievable yield, respectivelt. By amending these factors, it seems that it could reduce the difference between the achievable and the actual yield. [ABSTRACT FROM AUTHOR]

Rice crop production needs to be increased to meet the food demand of the growing global population by utilizing the limited available resources. Reducing yield gap between potential and actual farmers’ yields could be one of the promising options for increasing rice production. In order to quantify the yield gap of rice, field experiments were conducted at two different locations in the Lower Gangetic Plains. Decision Support System for Agro-technology Transfer model was used to quantify potential yield for analyzing the attainable yield gaps with respect to water limitation, agronomic managements, difference in transplanting dates and soil variability. The results showed that an attainable average yield gap of 0.33 t/ha in rainfed condition existed in farmers’ fields due to rice transplantation after 30th July, whereas the use of supplementary irrigations produced an average attainable yield gap of 0.86 t/ha in irrigated condition. Poor agronomic practices adopted by farmers may be causing the reduction in average yield of 0.29 t/ha. The yield gap due to different transplanting dates and agronomic managements suggested to identify yield optimum transplanting date of a cultivar and appropriate agronomic management strategy to reduce the yield gap. The soil variability contributed very less attainable yield gap (0.02-0.16 and 0.02-0.19 t/ha for rainfed and rainfed with subsequent irrigation, respectively), than other factors because of similar type of soil at the study sites. Results also suggested that farmers should emphasize more on management strategies such as quantity of N-fertilizers, timing of fertilizer applications, supplementary irrigation and transplanting date that might reduce the yield gap. [ABSTRACT FROM AUTHOR]

This position paper honours agricultural scientist and colleague, Professor Bob Loomis, by discussing the urgent global challenge of food security and the related impacts on the environment facing agricultural science and society in the next critical 20 years. It uses the concepts of potential and actual (farm) crop yields and the yield gap between them to assess current and future opportunities for food supply to satisfy increasing demand. The cropping world is seen in two parts. The first part predominantly comprises low-input farming with very large yield gaps and a faster growing demand that can only be met with increasing imports. For these regions, a well-established strategy is outlined for crop intensification through yield-gap closure that is essential for reducing rural malnutrition and poverty, and curtailing the likelihood of high food prices. For success, it must be complemented with strategies to remove the serious institutional and infrastructural barriers faced by farmers. The second part has more or less intensified, and yield gaps are generally small to moderate: it will fairly comfortably meet the demand from population growth. For these regions, some further yield gap closure is still possible but more importantly greater potential yields are required although the chances of accelerating this are discussed and seen to be limited. For all regions, sustainable intensification of cropping, predominantly on existing arable lands, is the best way forward. Combining sustainability with intensification is not a contradiction and is, in fact, essential; sustainability requires the efficient use of all inputs in cropping, and husbandry of the soil and agricultural biodiversity needed to continue to raise productivity. Off-farm environmental impacts are inevitable, but not insurmountable, hurdles. All aspects of sustainability require boosted RD&E and sound rural policies. Greater management skills for farmers and all others involved in crop production are also essential. Contestation based on biophysical aspects of food production and its impacts can be resolved through effective research and development with farmers, while that based on Northern cultural and normative views must not be allowed to obscure the goal of affordable food for all, and reward for farmers comparable with the rest of their societies. [ABSTRACT FROM AUTHOR]

The projected demand of maize production in India in 2050 is 4-5 times of current production. With the scope for area expansion being limited, there is need for enhancement of yield. This calls for identifying areas where huge unrealized yield potential exists. With a view to address the issue, the present study delineates homogeneous agro-climatic zones for maize production system in India taking district as a unit and using the factors production, viz. climate, soil, season and irrigated area under the crop. There are 146 districts in India that grow maize as a major crop. They were divided into 26 zones using multivariate cluster analysis. Study of variation in yield between districts within a zone vis-à-vis crop management practices adopted in those districts was found useful in targeting the yield gaps. These findings can have direct relevance to the maize farmers and district level administrators. [ABSTRACT FROM AUTHOR]

Rice-rapeseed cropping system (hereafter as rice-rapeseed system), as a major cropping system in the Yangtze River Valley (YRV) in China, plays an important role in national food and edible oil security. However, the production capacity of this system remains largely unknown. We evaluated the yield gap (Yg), energy gap (Eg), and production gap (Pg) of rice-rapeseed system. Regions with largest exploitable Pg were determined and possible scenarios were further analyzed for the evaluation of self-sufficiency rate (SSR) in the next decade. This study followed Global Yield Gap Atlas (GYGA) protocol (www.yieldgap.org) according to a bottom-up upscaling method with well-calibrated crop models to evaluate Yg, Eg, and Pg from reference weather stations to regions and national levels based on detailed database of daily weather, soil, crop management practices, and high-yielding experiments. Possible scenarios for the assessment of SSR were conducted further for rapeseed in the system. The relative Eg of the system of 42% was mainly affected by the larger relative Yg of 50% in rapeseed rather than that of 37% in rice. By Yg closure to 80% of Yp, a Pg was 8.54 million tons (Mt) for rice and 5.31 Mt for rapeseed in the system. Among the major planting provinces, Anhui had the largest Pg in rice, and Hunan had the largest Pg in rapeseed. As SSR in rice is high in China, we further evaluated rapeseed SSR in the system. We found that SSR in rapeseed was 79% currently and would decrease to 54% in 2031. According to scenario analysis, utilization of 4–39% of current winter fallow fields in YRV was important besides Yg closure for the system to reach a feasible SSR of 80% in the next decade. Large room existed in rice-rapeseed system for further yield increase, especially for rapeseed in the system. Partially utilization of winter fallow fields in YRV is promising to ensure system SSR in the next decade. This study has evaluated the Yg, Eg, and Pg for rice-rapeseed system, located the regions with large production capacity, and explored feasible strategies to increase rapeseed production and ensure high-level SSR in YRV. • Relative energy gap is 42% in rice-rapeseed system. • Relative yield gap of rice and rapeseed are 37% and 50% in the system, respectively. • Anhui and Hunan are the regions with largest production gap. • Utilization of 4–39% of winter fallow fields is important to ensure self-sufficiency. [ABSTRACT FROM AUTHOR]

Crop simulation models have been used to determine potential yield in a given environment. The twenty one years (1990-10) weather data and reported rice yield of Bhagalpur, Ranchi, Kalyani and Jorhat districts of eastern and north eastern region of India were used to simulate the yield under the various management conditions and compared with the reported yield of the districts. The management option included dates of sowing, irrigations and fertilizers application. The potential yield, attainable yield, yield gap etc were computed over the period. The results revealed that the rice yield of Kalyani and Ranchi districts showed increasing trend (30 to 65 kg ha-1yr-1) while decreasing trend was observed in Bhagalpur and Jorhat districts (6 to 9 kg ha-1yr-1). The potential yield simulated by model in different districts varied between 2864 to 4742 kg ha-1, while reported yield varied between 1159 to 2224 kg ha-1. The delay in sowing by 15 days caused reduction in rice yield by 31 to 74 kg ha-1day-1 at different locations. The management yield gap was between 1495 to 3216 kg ha-1 while sowing yield gap was between 467.4 to 1114.0 kg ha-1 in different districts under study.

A science-based, reliable, and feasible fertilizer recommendation method is required to respond to the low nutrient use efficiency caused by inappropriate fertilization practices. Soil test-based fertilizer recommendations are difficult to use for smallholder farms because of constraints such as access, cost and timeliness in multiple cropping systems. In this study, we combined on-farm experiments from 2012 to 2014 in 20 farmers’ fields on spring maize in Northeast China with a simulation model (Hybrid Maize model), to test the continual performance in agronomic, economic and environmental aspects of the Nutrient Expert for Hybrid Maize decision support system. Six treatments were set as follows: Nutrient Expert (NE), farmers’ practice (FP), soil testing (OPTS) and nitrogen (N), phosphorus (P), and potassium (K) omission treatments based on NE. We estimated yield gaps as the difference between simulated yields with the Hybrid Maize model and measured yields; calculated economic benefit and nutrient use efficiency; and estimated greenhouse gas emissions using published equations approximating nitrous oxide emissions as a function of N fertilizer rate. On average, the NE, FP, and OPTS treatments attained yields of 80%, 74%, and 77% of the potential yield, respectively. The exploitable yield gap between the NE and FP treatments was 0.9 t ha −1 , and between the NE and OPTS treatments was 0.5 t ha −1 . On average, the NE treatment increased the gross return above fertilizer cost (GRF) by US$303 and US$167 compared with the FP and OPTS treatments across all sites, respectively, in which about 91% and 98% of increase GRF was attributed increase in grain yield rather than reduction in fertilizer cost. There were slightly higher nutrient use efficiencies under the NE treatment than under the OPTS treatment. Relative to the FP treatment, however, on average, the NE treatment increased recovery efficiency of N, P, and K by percentage point of 12, 15, and 10, respectively. Agronomic efficiency of N, P, and K were increased by 6, 35, and 10 kg kg −1 , respectively. Finally, partial factor productivity increased by 14 kg kg −1 for N and 45 kg kg −1 for P while decreased by 29 kg kg −1 for K. Furthermore, the calculated soil inorganic N at harvest of maize crop, total greenhouse gas (GHG, kg CO 2 eq ha −1 ) emissions, and GHG emission intensity (kg CO 2 eq t −1 grain) were 42%, 17%, and 23% lower in the NE treatment than the FP treatment, respectively. We conclude that the Nutrient Expert for Hybrid Maize system has the potential to close existing yield gaps in the spring maize production systems of Northeast China by improving yield, nutrient use efficiency, and profitability with low environmental pollution. [ABSTRACT FROM AUTHOR]

In Canterbury, New Zealand, potato (Solanum tuberosumL.) growers are concerned that current fertiliser inputs limit yields. We tested if increasing these inputs would enable the crops to achieve their potential yield (Ypot). In four crops, nitrogen (N), phosphorus (P) and potassium (K) fertilisers were applied at or double the growers’ current rates. We also included two rates of calcium (Ca). Tuber yields were compared using ANOVA and by simulation using PARJIB, a nutrient response model. None of the crops achievedYpot. Yield was unaffected by changes in K or Ca rate. Doubling N and P applications increased yield at one site only (whereYpotwas largest but soil P and mineral N concentrations were least). Up to 21% ofYpotwas lost because of factors not included in the PARJIB model. Except at the least fertile sites, increasing fertiliser rates is unlikely to improve yield until the non-nutritional causes of yield gaps are identified and remedied. [ABSTRACT FROM AUTHOR]

Iran is one of the major chickpea ( Cicer arietinum L.) producing countries of the world. Average chickpea yield in Iran is about 500 kg ha −1 while the world average is 900 kg ha −1 . The objective of this study was to investigate chickpea water limited potential yield ( Y w ) and yield gap in Iran. The analysis was based on data from five representing chickpea producing locations of Iran. Estimated country Y w and yield gap were 991 and 463 kg ha −1 , respectively, indicating that farmers have reached 53% (range: 38–64%) of Y w . If farmers could reach 80% of Y w of their locations, by improving agronomy practice, country average yield would increase by 50%, from 528 to 793 kg ha −1 . A key finding of the study was that chickpea yield in Iran is largely limited by inefficient use of environmental resources and not the genetics of the current cultivars. Much higher yield increase is obtainable via an agronomic option than a genetic improvement option: using shorter duration cultivars increased Y w to 1237 kg ha −1 (25% increase), but applying a single irrigation of 60 mm at first-pod alone or in combination with shorter duration cultivars increased Y w to 1804 kg ha −1 (85% increase) and to 1997 kg ha −1 (104% increase), respectively. Thus, tripling chickpea production would be feasible using a single irrigation with or without shorter duration cultivars (from 528 to 1443 or 1598 kg ha −1 ). The availability of water for the single irrigation is discussed. [ABSTRACT FROM AUTHOR]

Given the importance of crop yield and yield progress, this review endeavours to clearly define the different representations of yield, discuss their measurement, and elucidate some controlling factors in yield change. For a field, farm, district or region, average farm or actual yield (FY) is central, but potential (and water-limited potential) yield (PY, PY w ) is also an important yardstick. PY is defined here as the measured yield of the best cultivar, grown with optimal agronomy and without manageable biotic and abiotic stresses, under natural resource and cropping system conditions representative of the target area. Economic yield, governed by considerations of profit and risk, and record and theoretical yield, complete the picture. Yield gap is defined as the difference between PY and FY under the same environment. Across most crop-region combinations in the last 2 to 3 decades, FY progress has been associated with both PY progress and yield gap closing, and a simple model, based on linear regression against time, is proposed for understanding this. PY advance is the result of plant breeding and new agronomy (and their interaction, usually positive), while yield gap closing arises with the adoption by farmers of known innovations faster than new ones are invented. Unravelling the true technological component in apparent progress in PY, and especially in FY, is not necessarily simple, and confounding factors are listed and discussed. [ABSTRACT FROM AUTHOR]

The potential yield of potato is defined as the theoretical yield that can be assessed for a well-adapted cultivar, grown from the best possible seed under optimal conditions. More than in crops that are grown from generative seeds, the growth, development, yield and quality of the potato crop are strongly influenced by the quality of the seed tubers, including their genetic, physical and physiological quality and their seed health status. Potato is very variable in maturity type: late cultivars can intercept large quantities of light whereas early cultivars show more efficient resource use. We describe potential and actual yields as well as impact of climate change on these yields, based on simple, robust models. Potential yields may be as high as 160 Mg ha −1 , in production systems with abundant irrigation, high radiation levels and long seasons. In such systems, actual yields of above 120 Mg ha −1 are feasible. However, potato is also grown as a short-cycle crop and in those conditions potential and actual yields are much lower. Potential yields might not change much in potato over time, but there is still a large gap between actual and potential yields to fill. The ratio between actual and potential yield ranges from 10 to 75%, but typical values are between 30 and 40%, although they obviously depend on the level of input. These ratios allow great yield improvements provided inputs are economically feasible in practice and if climate change does not interfere. In most countries, yields of potato might increase by climate change, provided water supply remains adequate. Main changes through climate change will probably occur by changes in the number of growing days per crop cycle. In some areas with abundant potato production, such as the Indo-Gangetic plains, however, climate change might reduce yield because of a reduction in number of growing days, but it has been projected that the effects of climate change on potato will be regionally diverse. [ABSTRACT FROM AUTHOR]

Water deficit and N fertilizer are the two primary limiting factors for wheat yield in the North China plain, the most important winter wheat (Triticum aestivum L.) production area in China. Analyzing the yield gap between the potential yield and the attainable yield can quantify the potential for increasing wheat production and exploring the limiting factors to yield gap in the high-yielding farming region of North China Plain. The Decision Support System for Agrotechnology Transfer (DSSAT) model was used to identify methods to increase the grain yield and decrease the gap. In order to explore the impact of N and cultivars on wheat yield in the different drought types, the climate conditions during 1981 to 2011 growing seasons was categorized into low, moderate, and severe water deficit classes according to the anomaly percentage of the water deficit rate during the entire wheat growing season. There are differences (P < 0.0001) in the variations of the potential yields among three cultivars over 30 yr. For all three water deficit types, the more recent cultivars Jimai22 and Shijiazhuang8 had higher yields compared to the older 'Jinan17'. As the N fertilizer rate increased, the yield gap decreased more substantially during the low water deficit years because of the significant increase in attainable yield. Overall, the yield gaps were smaller with less water stress. Replacement of cultivars and appropriate N fertilizer application based on the forecasted drought types can narrow the yield gap effectively. [ABSTRACT FROM AUTHOR]

Global food security requires eco-efficient agriculture to produce the required food and fiber products concomitant with ecologically efficient use of resources. This eco-efficiency concept is used to diagnose the state of agricultural production in China (irrigated wheat-maize double-cropping systems), Zimbabwe (rainfed maize systems), and Australia (rainfed wheat systems). More than 3,000 surveyed crop yields in these three countries were compared against simulated grain yields at farmer-specified levels of nitrogen (N) input. Many Australian commercial wheat farmers are both close to existing production frontiers and gain little prospective return from increasing their N input. Significant losses of N from their systems, either as nitrous oxide emissions or as nitrate leached from the soil profile, are infrequent and at low intensities relative to their level of grain production. These Australian farmers operate close to eco-efficient frontiers in regard to N, and so innovations in technologies and practices are essential to increasing their production without added economic or environmental risks. In contrast, many Chinese farmers can reduce N input without sacrificing production through more efficient use of their fertilizer input. In fact, there are real prospects for the double-cropping systems on the North China Plain to achieve both production increases and reduced environmental risks. Zimbabwean farmers have the opportunity for significant production increases by both improving their technical efficiency and increasing their level of input; however, doing so will require improved management expertise and greater access to institutional support for addressing the higher risks. This paper shows that pathways for achieving improved eco-efficiency will differ among diverse cropping systems. [ABSTRACT FROM AUTHOR]

Although China is the world second largest cotton (Gossypium hirsutum L.) producer, it is the world largest cotton consumer with high reliance on import. Cotton cropping system in China underwent substantial changes in the past few decades as 85% of the previous cotton area changed into other uses, and its production center has shifted fast to new croplands in Xinjiang where farm size is larger and mechanization more prevalent. Given these rapid changes, we performed the first comprehensive assessment of cotton production capacity and self-sufficiency ratio in China based on the analysis of yield gap (difference between current farm yield and yield potential) by employing a bottom-up scaling approach which entails local weather, soil, crop management and latest high-yielding experimental data. We found that current yield gap represents 40% of estimated potential yield, suggesting a large scope for total production increase by yield gap closure. China's current cotton self-sufficiency ratio is 68%, and it could reach 90% by yield gap closure in Xinjiang alone and up to 94% in all major cotton growing provinces by 2030. Results also highlight the regions with the greatest prospect for further production increase in China by considering current yield gaps, production area, and potential for expansion. Xinjiang alone could achieve 71% of additional production, while opportunities also exist in the other major cotton growing provinces, i.e., south part of Hebei and southeast part of Hubei provinces. • First explicit estimate of cotton production capacity and self-sufficiency in China. • Employed a novel "bottom-up" scaling protocol with well calibrated model. • High degree of spatial resolution and agronomic relevance at different levels. • A large scope for total cotton production increase by yield gap closure. [ABSTRACT FROM AUTHOR]

Yield gap analysis plays an important role in determining potential food availability. The Global Yield Gap Atlas maps yield gaps of crops from point to regional scale across the globe. The calculated yield gaps are based on comparisons between modelled potential yields with actual farmers' yields derived from statistical sources. The calculations are subject to uncertainty due to various sources, including measurement errors, modelling limitations, and scaling issues. An important goal of the Atlas is to convey an uncertainty evaluation of the yield gap analysis. The aim of this paper is to provide a practical methodology that can make the assessment of the uncertainty by experts explicit and accessible for users of the Atlas. We developed an uncertainty protocol and guidelines listing several sources of uncertainty to be considered by country agronomists who were involved in the calculation of the yield gaps. These experts are asked to score the level of uncertainty of each source, as well as the relative impact of each source. Both scores are combined into uncertainty scores for each source. Aggregated uncertainty scores for yield gaps, potential and actual yields are mapped as colours in the Atlas to indicate ranking. Moreover, experts are encouraged to provide a justification for their scores, which are also made available to users of the Atlas. The uncertainty protocol was applied to 189 country-crop combinations by fourteen experts. They ranked lack of data for model calibration, model sensitivity to specific conditions, weather data, and the data quality on cropping system as the most important uncertainty sources for potential yields. The quality of yield data was ranked as the highest source of uncertainty for actual yields. The justifications provided by experts suggest which uncertainty sources may be reducible with relatively little effort, while other uncertainty sources may be more difficult or impractical to address. The decision making on options to improve food production is better informed when uncertainties are accounted for. The proposed uncertainty protocol allows users to distinguish between different sources of uncertainty as well as their level and relative effect on the end result. The ranking of uncertainty sources suggests a prioritization of future effort to reduce the uncertainty around yield gaps. The justifications given by the experts can provide suggestions for options to reduce uncertainty. [Display omitted] • The Global Yield Gap Atlas maps yield gaps of crops from point to regional scale across the globe. • Many different uncertainty sources affect the calculation of yield gaps. • We present a protocol for experts to score uncertainties with their justifications made available to users • The expert scores of the uncertainty sources provide a ranking for users to consider per crop-country combination. • The expert justifications reveal which uncertainties can be reduced and which are not reducible [ABSTRACT FROM AUTHOR]