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Chickpea is an important livelihood option and nutritious food source for many subsistence farming communities in the developing world. Although India is the biggest chickpea producing nation, the demands of its growing population are not met by domestic production. This study uses a modelling approach to quantify the region-specific constraints and yield gaps limiting chickpea productivity and evaluates the potential for boosting production in the major chickpea growing regions of India. Information on bio-geo-physical properties (weather, soil, crop, management) of these regions was collated and the SSM-iLegume model used to reproduce seasonal variability and potential yield for the major chickpea producing districts to estimate the yield gap. Further, we estimated the difference between the yield potential and the currently achieved yields; i.e. yield-gap. The results showed that India has the capacity to produce 40% more chickpea (i.e. 80% of the achievable yield) than is the current production status under the standard crop management practices. We also found that chickpea crop production in rain-fed systems is largely limited by water availability during the season (∼64%) but with large variability in the drought stress effect on yields between the investigated districts. Observed geo-bio-physical properties of the districts and simulation results of yield gap analysis were used to cluster chickpea-growing districts into six distinct units with higher degrees of similarities; i.e. homogeneous system units (HSU). Within each HSU a similar system response to genotype-by-management (GxM) intervention is expected and the effects of particular interventions could be further tested using the modelling set-up developed for this study. The identified HSUs, each with a well-defined set of yield-limiting constraints, are proposed as authentic breeding units in crop improvement programs (“target population of environments”) and we further discuss the need to use the HSU-specific breeding strategy to enhance chickpea production in India. [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]

Efforts to anticipate how climate change and variability will affect future crop production can benefit from understanding the impacts of current and historic changes. This study aimed to quantify and compare the impact of increased night temperature on potential yield and phenology of wheat ( Triticum aestivum L. ) and barley ( Hordeum vulgare L. ) crops modelled using APSIM with historical climate series (1961–2014) in sites representative of the Argentinean Pampas. For each site, the sowing date was adjusted to avoid frost and heat events at flowering, based on historical probability. The critical period was the more sensitive crop phase (shortened by 0.6 d decade −1 ) for the observed asymmetric warming; regional minimum temperature trend of ca. 0.14 and 0.16 °C decade −1 in wheat and barley, respectively. Wheat and barley yields declined across the region between ca. 2% and 9% per °C increase in the minimum temperature during the critical period, linked to lower cumulative radiation capture as a result of a shorter crop phase and lower incident radiation due to displacement towards winter. Regional variability in the simulated yield response to the observed night warming was mainly explained by differences the response of incident solar radiation during the critical period to the minimum temperature increase. [ABSTRACT FROM AUTHOR]

This study was undertaken to suggest an effective fisheries resources management system by using stock assessment and potential yield analyses of crucian carp population in the mid-upper system of the Seomjin River. Fieldwork was conducted seasonally from 2008 to 2009 in the mid-upper system of the Seomjin River. The stock assessment was carried out by the swept area method and the potential yield was estimated by improved fisheries resource potential estimation system based on the Allowable Biological Catch. Also, the yield-per-recruit analysis was used to review the efficient management implication of the resource, Carassius auratus. As a result, the age at first capture (tc) was estimated as 1.468 year, converted body length (BL) was 10.8 cm. Meaning the current fishing intensities, the instantaneous coefficient of fishing mortality (F) was 0.067 year-1, and the yield-per-recruit analysis showed that the current yield per recruit was estimated to be 15.999 g with F and tc. The instantaneous rate of fishing mortality that provides for Allowable Biological Catch (FABC) based on the current tc and F was estimated as 0.618 year-1. Therefore, the optimum fishing intensities could be achieved at the higher fishing intensity for Carassius auratus. The calculated annual stock of C. auratus was estimated as 7,608 kg, and the potential yield was estimated as 343 kg with tc and F at the fixed current level. Using yield-per-recruit analysis, if F and tc were set at 0.618 year-1 and 2 year, the yield per recruit and total allowable catch would be predicted to increase to 62 g and 2,531 kg by about 3.9 times and 7.3 times, respectively.

Based on climate data from 254 meteorological stations, this study estimated the effects of climate change on rice planting boundaries and potential yields in the southern China during 1951–2010. The results indicated a significant northward shift and westward expansion of northern boundaries for rice planting in the southern China. Compared with the period of 1951–1980, the average temperature during rice growing season in the period of 1981–2010 increased by 0.4°C, and the northern planting boundaries for single rice cropping system (SRCS), early triple cropping rice system (ETCRS), medium triple cropping rice system (MTCRS), and late triple cropping rice system (LTCRS) moved northward by 10, 30, 52 and 66 km, respectively. In addition, compared with the period of 1951–1980, the suitable planting area for SRCS was reduced by 11% during the period of 1981–2010. However, the suitable planting areas for other rice cropping systems increased, with the increasing amplitude of 3, 8, and 10% for ETCRS, MTCRS and LTCRS, respectively. In general, the light and temperature potential productivity of rice decreased by 2.5%. Without considering the change of rice cultivars, the northern planting boundaries for different rice cropping systems showed a northward shift tendency. Climate change resulted in decrease of per unit area yield for SRCS and the annual average yields of ETCRS and LTCRS. Nevertheless, the overall rice production in the entire research area showed a decreasing trend even with the increasing trend of annual average yield for MTCRS.

This study was designed to calibrate and test an agrometeorological model over 18 growing seasons in three soybean production areas in Brazil: Passo Fundo (Rio Grande do Sul State), Londrina (Paraná State), and Dourados (Mato Grosso do Sul State).The soybean potential yield (Yp) was determined by two methods: estimated using the FAO Agroecological Zone Model or based on the maximum yield published by the Brazilian Institute of Geography and Statistics (IBGE), increased by 10, 20 and 30%.The estimate of actual yield (Ya) was calculated by correcting Yp for the relative water deficit at different growth stages. The results showed that the best performance was obtained when the Yp was represented by the maximum yield increased by a certain percentage. The model showed satisfactory Ya estimates for the three locations, generating R2 values of 0.64, 0.46 and 0.70, with mean absolute errors (MAE) of 303, 289 and 259 kg ha-1 for Passo Fundo, Londrina and Dourados, respectively. In a global analysis, the performance of the model was satisfactory, with an R2, agreement modified index (d1), confidence index (C) and MAE of 0.64, 0.52, 0.71 and 300 kg ha-1, respectively.

Standardization of crop yield estimation methods at various levels of farming helps to obtain accurate agricultural statistics as well as assessing the suitability of agricultural practices under various production conditions. The current paper reviews various maize yield estimation methods, taking into account available yield parameters, and it also analyses the yield gap between maize potential and attainable yield. The easiest and more reliable methods of yield estimation are based on yield parameters collected from the field. However, farmer estimation methods are cheaper and faster compared to any other method of yield estimation from farmers’ fields. This paper also elaborates on the importance of the use of more complex methods for yield estimation, such as remote sensing and crop modelling. These complex methods are more accurate and can predict yield before field harvest with less deviation from the exact harvest yield. However, they are very expensive and not efficient for small plots of land (less than 1 ha). Factors that contribute to the gap between potential and actual yield include poor implementation of agricultural policies, strict regulation of fertilizer inputs, vulnerability of smallholder cropping systems to adverse climatic conditions, occurrence of biotic and abiotic constraints, as well as unavailability of seeds and labor.

The federal government, through the General Direction of Tropical Zones of the Secretariat of Agriculture, Livestock, Rural Development, Fisheries, and Food (SAGARPA), has fostered the creation of 20,000 ha of Robusta coffee crops in the south-southeast states. As part of this initiative, the present study is done to determine what areas of the state of Tabasco are better suited for this type of coffee to prosper successfully and what the future impacts of climate change mid XXI century would be on its adaptation and yield. Thus, the objective of the present study was to determine the best areas, from the point of view of climate and soil, to grow Robusta coffee (Coffea canephora P.) in the state of Tabasco, as well as its vulnerability to a possible climate change in the middle of the present century. This was done using the Agro-Ecological Zoning methodology (AEZ) proposed by the FAO for the current conditions and for the worst-case scenario of climate change (RCP8.5) expected for mid XXI century. Also, the potential yields for three levels of input (low, medium, and high) were estimated in the areas that resulted to be very apt for both climatic conditions. The results indicate that if there were to be a mean daily increase in temperature of 1.6 ºC by the year 2050, under the worst-case scenario (RCP8.5), the very apt surface to grow Robusta coffee in the state of Tabasco is not modified. However, the mean potential yields would decrease by 41% by the year 2050 due to the effect of the increase in daytime temperatures on the maximum photosynthetic ratio. [ABSTRACT FROM AUTHOR]

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Understanding the interactions of genotype (G) × environment (E) × management (M) and their impact on crop yield enables prediction of the performance of genotypes across environment. It can help select the most suitable cultivars in target regions and identify contributions of novel traits in crop breeding. In this study, we used the process-based APSIM-Canola model to investigate the G × E × M interactions for the purpose of increasing canola yield in contrasting climatic regions of China. A dataset with observations for nine cultivars and 30 site-years was used to test the performance of APSIM-Canola model. Two representative genotypes (as base cultivars) were used to simulate canola potential yield and evaluate potential contributions of putative traits to increase canola yield at three representative sites. Our results show that APSIM-Canola was able to simulate seed yield of both spring and winter canola cultivars across contrasting climatic regions with acceptable accuracy. In the Upper and Middle Yangtze River Basin where rainfall is sufficient or irrigation is available, the yield potential of current winter canola cultivar was simulated to be 6.4 and 4.8 t ha −1 , respectively. In the Northern Region with limited rainfall, the yield potential was only 1.1 t ha −1 due to severe water stress. Traits that extended the grain filling duration by 20% could increase potential yield by 10% for winter canola, but 5% for spring canola. A 20% increase in radiation use efficiency (RUE) would increase yield by 10–20% in Yangtze River Basin, but had no impact on yield in the Northern Region. Traits that increased transpiration efficiency (TE) had the opposite impact, with 20% increase in TE leading to 30% increase in yield in the Northern Region, but with no significant yield increase in wet areas. A 20% increase in harvest index (HI) increased potential yield by nearly 20% across contrasting environments. A much larger yield gap for winter canola in the Yangtze River Basin was also found, indicating a much greater potential to increase canola seed yield there than in the Northern Region. This study highlights that very different traits need to be targeted for canola breeding across the contrasting climatic regions of China. [ABSTRACT FROM AUTHOR]

The growing importance of fodder beet ( Beta vulgaris subsp. vulgaris var. alba L.) as stock feed in recent years has created the need to develop a crop model to help assess crop yield potential across environmental growth conditions. This paper describes the development of a biophysical model for simulating fodder beet growth and development. The model was developed using the Plant Modelling Framework (PMF) within the next generation Agricultural Production Systems sIMulator (PMF-APSIM). The model was parameterised/calibrated and validated using independent datasets from field experiments conducted in the Canterbury region of New Zealand. A sensitivity analysis was conducted to explore yield response to variation in the extinction coefficient and the air temperature. The results show that canopy-related variables (leaf appearance, leaf senescence, leaf area index and light interception) were the most accurately simulated. Dynamic dry matter (DM) and nitrogen (N) accumulation in different plant organs were simulated with intermediary accuracy. Reduced accuracy was mainly observed in the earliest (September) and latest (December) sowing dates. This suggests that responses to seasonal environmental drivers, such as day length and threshold temperatures, are areas that require further research. Similarly, more mechanistic representations of carbon and N partitioning to different plant organs may improve simulation accuracy. The sensitivity analysis showed that DM production was responsive to temperature and the extinction coefficient. This initial development and testing of the fodder beet model in APSIM has helped to identify key knowledge gaps in the understanding of the physiology of the crop and provides new directions for model development. [ABSTRACT FROM AUTHOR]

Cotesia vestalis (Haliday) (Hymenoptera: Braconidae) (= plutellae ) is an important parasitoid of Plutella xylostella L. (Lepidoptera: Plutellidae) consistently accounting for high field mortality. However, indiscriminate use of broad-spectrum insecticides is reported to undermine this parasitoid's impact. To investigate the implications of selective and broad-spectrum insecticides on C. vestalis, trials were conducted in Eastern Cape Province, South Africa. Plutella xylostella infestation, C. vestalis parasitism, and yield variables were measured over three growing seasons on unsprayed cabbage, and cabbage treated with selective Biobit ® ( B. thuringiensis var. kurstaki , 32000 IU/mg) or broad-spectrum Cypermethrin ® (cypermethrin, 200 g/l). Plutella xylostella infestation was higher in control compared to treated cabbage during winter and spring but not summer. However, parasitism was consistently higher in the control (≥55%) compared to the Biobit (≤45%) and Cypermethrin (≤25%) treatments throughout the study period. Consistent with higher parasitism, the C. vestalis yield loss abatement function was highest in the control followed by Biobit and least in Cypermethrin during winter (42 > 24 > 10%), spring (36 > 35 > 22%) and summer (41 > 36 > 23%). These results demonstrate that Biobit reduces P. xylostella field density and crop damage with minimal impact on the C. vestalis yield loss abatement function. [ABSTRACT FROM AUTHOR]

Climate change is threatening the ability to grow cotton ( Gossypium hirsutum L.) under low input rainfed production areas in Sub-Saharan Africa. In Northern Cameroon, yield has been declining due to unsuitable cropping practices such as sub-optimal planting dates, along with an absence in genetic gain. The aim of this study was to use a cropping system model (DSSAT CSM-CROPGRO-Cotton) to identify the best cultivars (ideotypes) for Northern Cameroon that are adapted to low input rainfed productions systems for 2050 under RCP4.5 and RCP8.5. Calibration and evaluation of the CSM-CROPGRO-Cotton were performed with field observations for two cultivars (Allen Commun and L484). For RCP4.5 and RCP8.5, 50 replications for 2050 were generated based on an ensemble of 17 Global Circulating Models. In total, 3125 virtual cultivars representing existing genetic variability for phenology, morphology and photosynthesis were simulated. Thereafter, they were evaluated for performance under the projected future climate based on potential yield and the resilience of yield to sub-optimal planting date. The widely cultivated cultivar L484 will be unsuitable under projected future climate, due to boll opening during the middle of the rainy season (median: 10/09 under RCP4.5 and 12/09 under RCP8.5). None of the ideotypes tested could optimize both yield and resilience ( Pearson correlation <−0.82). However, compared to the current cultivar L484, two virtual ideotypes were identified: (a) “Ideo_sub” had a wide planting window, especially in the 10 worst replications of 2050, up to +5 days in RCP8.5; (b) “Ideo_Pot” had a high potential yield trait with low resilience to sub-optimal planting date, in the 10 worst replications of 2050, +530 kg ha −1 in RCP4.5 and +591 kg ha −1 in RCP8.5. Both ideotypes had an earlier anthesis date, a longer reproductive duration, and increase in the maximum photosynthetic rate. Therefore, breeding programs should consider these traits suggested by this system analysis using a crop simulation model for the identification of suitable cultivars under the projected future climate. [ABSTRACT FROM AUTHOR]

In the Kanto region in Japan, the possibilities of running a bio-ethanol plant from rice straw has been assessed and sorghum production has been considered as a necessary part of the system. Two field experiments were conducted in 2012 and 2013 at the NARO--Agricultural Research Center in Tsukuba, Ibaraki to estimate yielding ability of sorghum in the Kanto region. Two cultivars of sweet sorghum and one of grain sorghum were sown using a pneumatic seeder. Above-ground dry matter (DM) yield ranged from 1.03 to 1.82 kg m-2 for the sorgo type cultivars and from 0.70 to 1.18 kg m-2, indicating that biomass production was restricted in this study. Stem brix values for the sweet sorghum cultivars were generally low (3.3-16.2%) compared with the values reported in the literature. It appears that there is still room to improve the field management of sorghum to minimize the gap between the potential and actual production observed in these experiments. [ABSTRACT FROM AUTHOR]

Wheat-maize relay intercropping has been widely used by farmers in northwest China, and based on field experiments agronomists report it has a higher productivity than sole crops. However, the yields from farmers' fields have not been investigated yet. Yield gap analysis provides a framework to examine land productivity, i.e. the actual yields realized in farmers' fields versus the potential yields when a crop is grown with water and nutrients non-limiting and biotic stresses effectively controlled. In this research, we aim to define yield potentials and yield gaps in intercropping systems, and apply this to an irrigated wheat-maize relay intercrop in Gaotai county (Zhangye city), Gansu province in northwest China. Data from three field experiments (2010 − 2012) were used to calibrate and test crop models for two sole crops and an intercrop. Potential yields were estimated for five years (2010–2014) by model simulations, and actual yields were determined by surveys of 310 farm households in 2014. The main results are: 1) in sole crops, the potential yield of spring wheat is 7.3 t ha − 1 and the potential yield of maize is 14.2 t ha − 1 ; 2) in a wheat-maize relay intercrop with a land area ratio of 0.5 for each crop, the potential yield of wheat is 4.8 t ha − 1 and that of maize is 12.0 t ha − 1 ; 3) comparing the yield in the intercrop and the expected yield (i.e. the yields in sole crops multiplied by the land area ratio in the intercrop for each species), the intercropped wheat gained 32% under potential growing conditions and 67% under actual growing conditions; while the intercropped maize gained 69% under potential growing conditions and 64% under actual growing conditions; 4) farmers achieved 67% of potential yield for sole wheat, and 85% for intercropped wheat; however, farmers achieved only 51% of potential yield for sole maize and 49% for intercropped maize. The farm survey showed that wheat-maize relay intercropping is still widely used by farmers in Gaotai county, and farmers gained extra yield from wheat-maize relay intercropping compared to sole crops, but the gap between potential and actual yields is especially large for maize in this region. Water is likely to be the main limiting factor for maize production despite the irrigation. We conclude by exploring how grain production in Gaotai county would be affected by substituting intercrops by sole crops. We find that the grain production will decrease between 18% to 44% if all the farmers would replace wheat-maize relay intercropping by either wheat or maize sole crop compared to the current land use. Intercropping thus contributes to food production at the regional level, and this contribution can be further increased by narrowing yield gaps. [ABSTRACT FROM AUTHOR]

The evolution of Russian concepts concerning the assessment of soil suitability for cultivation in relation to several campaigns on large-scale plowing of virgin steppe soils is examined. The major problems of agricultural land use in steppe areas-preservation of rainfed farming in the regions with increasing climatic risks, underestimation of the potential of arable lands in land cadaster assessments, and much lower factual yields in comparison with potential yields-are considered. It is suggested that the assessments of arable lands should be performed on the basis of the soil-ecological index (SEI) developed by I. Karmanov with further conversion of SEI values into nominal monetary values. Under conditions of land reforms and economic reforms, it is important to determine suitability of steppe chernozems for plowing and economic feasibility of their use for crop growing in dependence on macroeconomic parameters. This should support decisions on optimization of land use in the steppe zone on the basis of the principles suggested by V. Dokuchaev. The developed approach for assessing soil suitability for cultivation was tested in the subzone of herbaceous-fescue-feather grass steppes in the Cis-Ural part of Orenburg oblast and used for the assessment of soil suitability for cultivation in the southern and southeastern regions of Orenburg oblast. [ABSTRACT FROM AUTHOR]

Uma das práticas desafiadoras de manejo é aumentar a produção de arroz utilizando menos água. O experimento foi realizado nas safras de 2010/11 e 2011/12 na área experimental da Universidade Federal de Santa Maria, Rio Grande do Sul. O objetivo foi avaliar o rendimento de grãos e a eficiência do uso de água na semeadura no início e final da época recomendada. Os tratamentos foram as épocas de semeadura (01/10/10 e 01/12/10) safra 2010/11, e (27/09/11 e 07/12/11) safra 2011/12, com cinco repetições, e a cultivar utilizada foi a 'IRGA 424'. Não houve diferença no volume de água aplicado entre as épocas de semeadura, com volume médio de 5757 e 8420m³ ha-1, respectivamente, para safra 2010/11 e 2011/12. A época de semeadura afetou o rendimento de grãos, com rendimento de 13 e 24% a mais nas semeaduras do início da época (01/10/10 e 27/09/11), comparado às semeaduras do final da época (01/12/10 e 07/12/11), respectivamente. A semeadura realizada no início da época recomendada (início de outubro) proporciona maior rendimento de grãos e maior eficiência no uso de água.One of the challenging management practices is to increase rice production using less water. The study was conducted during the harvest of 2010/11 and 2011/12 in the experimental field of Universidade Federal de Santa Maria, Rio Grande do Sul State, Brazil. The objective was to evaluate the yield and water use efficiency at sowing at beginning and end of the recommended time. Treatments were at planting dates (10/01/10 and 12/01/10) 2010/11 harvest, and (9/27/11 and 12/07/11) 2011/12 harvest, with five replicates, the cultivar used was the 'IRGA 424'. There was no difference in the amount of applied water between sowing times, with an average of 5757 and 8420m³ ha-1, respectively for season 2010/11 and 2011/12. The sowing date affected grain yield, with yields of 13 and 24% more in the beginning of the sowing season (10/01/10 and 9/27/11) compared to the end of the sowing date (12/01/10 and 12/07/11), respectively. Sowing early in the recommended period (early October) provides greater yield and more water use efficiency.

Eficiência agrícola (EA) é utilizada como indicador do nível de desenvolvimento agrícola regional, expressando, por meio da relação entre as produtividades real e atingível, o nível tecnológico empregado nas culturas. Com base nisso, o objetivo deste estudo foi avaliar a EA das culturas da soja, do milho e do trigo para o estado do Rio Grande do Sul, entre os anos de 1980 e 2008, identificando os principais fatores que as condicionaram. A EA foi obtida pela relação entre a produtividade atingível (PA) e a real (PR). A PR foi obtida junto ao banco de dados do Instituto Brasileiro de Geografia e Estatística (IBGE). A PA foi obtida pela estimativa da produtividade potencial (PPf), pelo método de Zona Agroecológica da FAO, deflacionada pelo déficit hídrico em cada uma das fases da cultura. Verificou-se que as EAs médias para as culturas do milho, da soja e do trigo para o RS foram iguais a 54, 61 e 43%, respectivamente. Nas localidades de Santa Rosa, São Borja e Veranópolis, a EA para a soja foi, ao contrário das demais localidades, negativa. Os principais fatores que contribuíram para o aumento da EA, na maioria das localidades, foram: mudanças no uso e fertilidade do solo; uso de mecanização agrícola; preços pagos pelas commodities; investimentos em pesquisa e desenvolvimento; adoção do zoneamento de risco climático; e melhoramento genético.Agricultural efficiency (EA) is used as an indicator of the level of regional agricultural development, reflecting, by mean of the ratio between actual and achievable yields, the crop technology level. Based on that, the objective of this study was to evaluate the EA for soybean, corn and wheat crops in the state of Rio Grande do Sul, Brazil, between 1980 and 2008, identifying the main factors which conditioned it. EA was obtained by the relationship between the achievable yield (PA) and actual crop yield (PR). PR was obtained from the Brazilian Institute of Geography and Statistics (IBGE) data base. PA was obtained by estimating the potential yield (PPf) with the FAO Agroecological Zone method, penalized by the water deficit for each crop phase. Average EAs for corn, soybean and wheat crops were 54, 61 and 43%, respectively. On the contrary of the majority of location, in Santa Rosa, São Borja and Veranópolis EA values were negative for soybean crop. The main factors that contributed to the increase of EA, in the majority of the locations, were: change on the soil use and fertility; use of agricultural machinery; prices paid for commodities; investments in research and development; climatic risk zoning; and plant breeding.

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]

Sowing dates are currently an essential input for crop models. However, in the future, the optimal sowing time will be affected by climate changes and human adaptations to these changes. A better understanding of what determines the choice of wheat type and sowing dates is required to be able to predict future crop yields reliably. This study was conducted to understand how climate conditions affect the choice of wheat types and sowing dates globally. We develop a model integrating optimality concepts for simulating gross primary production (GPP) with climate constraints on wheat phenology to predict sowing dates. We assume that wheat could be sown at any time with suitable climate conditions and farmers would select a sowing date that maximises yields. The model is run starting on every possible climatically suitable day, determined by climate constraints associated with low temperature and intense precipitation. The optimal sowing date is the day which gives the highest yield in each location. We evaluate the simulated optimal sowing dates with data on observed sowing dates created by merging census-based datasets and local agronomic information, then predict their changes under future climate scenarios to gain insight into the impacts of climate change. Cold-season temperatures are the major determinant of sowing dates in the extra-tropics, whereas the seasonal cycle of monsoon rainfall is important in the tropics. Our model captures the timing of reported sowing dates, with differences of less than one month over much of the world; maximum errors of up to two months occur in tropical regions with large altitudinal gradients. Discrepancies between predictions and observations are larger in tropical regions than temperate and cold regions. Slight warming is shown to promote earlier sowing in wet areas but later in dry areas; larger warming leads to delayed sowing in most regions. These predictions arise due to the interactions of several influences on yield, including the effects of warming on growing-season length, the need for sufficient moisture during key phenological stages, and the temperature threshold for vernalization of winter wheat. The integration of optimality concepts for simulating GPP with climate constraints on phenology provides realistic predictions of wheat type and sowing dates. The model thus provides a basis for predicting how crop calendars might change under future climate change. It can also be used to investigate potential changes in management to mitigate the negative impacts of climate change. [Display omitted] • Uncertainties in projected crop yields stem from specifying sowing dates; there is a need to predict sowing dates reliably. • We investigate if wheat type and optimal sowing date can be predicted from climate constraints on phenology. • Including constraints to avoid frost and rain damage in an optimality-based model gives good predictions of sowing dates. • Global patterns in wheat type and sowing date, reflecting management practices to maximise local yields, are predictable. • Our model can be used to predict climate change impacts on wheat yield and if changing sowing dates mitigate these impacts. [ABSTRACT FROM AUTHOR]

A decision support system (DSS) tool has been developed for providing information on the optimum time of planting and the likely consequences of early or late planting of potato in about one hundred and seventy three locations of Nilgiris region of Tamil Nadu state in India for the most popular variety of the region i.e., Kufri Jyoti. The effect of harvest at two different durations i.e., 100 and 120 days after planting is also incorporated in this DSS. The tool consists of a database of simulated yield at 100 and 120 days after planting derived through InfoCrop-potato model. This DSS is developed with the data base generated using the daily weather data developed through weather generators and the potential yields estimated with the help of InfoCrop-Potato model. The methodology of development of the data base and the user interface of the DSS has been discussed in this paper.

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.

Yield gap analysis is gaining increased scientific attention, as estimating and explaining yield gaps shows the potential for sustainable intensification of agricultural systems. Explaining yield gaps requires detailed information about the biophysical environment, crop management as well as farm(er) characteristics and socio-economic conditions in which farmers operate. However, these types of data are not always available, mostly because they are costly to collect. The main objective of this research is to assess data availability and data collection approaches for yield gap analysis, and to summarize the yield gap explaining factors identified by previous studies. For this purpose, a review of yield gap studies (50 agronomic-based peer-reviewed articles) was performed to identify the most commonly considered and explaining factors of the yield gap. Besides a global comparison, differences between regions, crops and methods were analysed as well. The results show that management and edaphic factors are more often considered to explain the yield gap compared to farm(er) characteristics and socio-economic factors. However, when considered, both farm(er) characteristics and socio-economic factors often explain the yield gap. Fertilization and soil fertility factors are the most often considered management and edaphic factors. In the fertilization group, factors related to quantity (e.g. N fertilizer quantity) are more often considered compared to factors related to timing (e.g. N fertilizer timing). However, when considered, timing explained the yield gap more often. Explaining factors vary among regions and crops. For example, while soil fertility is considered relatively much both in Africa and Asia, it is often explaining in Africa, but not in Asia. Agronomic methods like crop growth simulation models are often used for yield gap analysis, but are limited in the type and number of factors that can be included. Qualitative methods based on expert knowledge can include the largest range of factors. Although the data included in yield gap analysis also depends on the objective, knowledge of explaining factors, and methods applied, data availability is a major limiting factor. Bottom-up data collection approaches (e.g. crowdsourcing) involving agricultural communities can provide alternatives to overcome this limitation and improve yield gap analysis. [ABSTRACT FROM AUTHOR]

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]

Optimum field management practices need to be developed and improved to solve the challenge of increasing food production while retaining the ecological integrity of farming system underlying the goal of sustainable agriculture. In our study, the concept of ecological intensification (EI) was applied to a spring maize cropping system in Jilin province, China during 2009–2013. Results indicated that the average grain yield was 11.8 t ha −1 in the EI treatment; while the farmers’ practice (FP) treatment had an average of 11.4 t ha −1 grain yield across five seasons. The Hybrid Maize Model was used to simulate the potential yield under water-limited condition, and the results showed that grain yield with 92.6% of the average potential yield (14.3 t ha −1 ) in EI treatment was closer to the yield potential than FP treatment. Adjusted nitrogen (N) fertilizer rate, split-application of N at the right time and suitable recommended hybrid maize plant density were used for improving N use efficiency and decreasing the negative effects to the environment. Consequently, a total of 180 kg N ha −1 was enough for maize growth and resulted in equal plant N uptake as the 251 kg N ha −1 applied in FP. Higher agronomic efficiency of N (AE N ), recovery efficiency of N (RE N ) and partial factor productivity of N (PFP N ) in EI treatment (39.7 kg kg −1 , 66.1% and 66.2 kg kg −1 , respectively) were observed relative to those in FP treatments (26.9 kg kg −1 , 42.5% and 50.4 kg kg −1 , respectively). Improved N use efficiency contributed significantly less N loss to the environment. Our results showed that calculated residual N min , the apparent N loss and total GHG emission was 37.5%, 34.3% and 29.8% lower in EI treatment when compared to FP treatment. This study helps quantify and understand the concept and practices of EI. Adoption of 4R Nutrient Stewardship (fertilizer right source, right rate, time and placement) and supporting agronomic practices (optimizing plant density and plant hybrid selection) in our study optimized crop production and minimized potential environmental impact. [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]

The potential yield estimator model developed by Central Potato Research Institute, Shimla was run for four different planting dates under rainfed situations in plateau regions of India since the potato crop is grown under rainfed conditions during kharif season so as to estimate the yield potential and to find out the optimum time of planting for each location. The analysis showed that the latitude of the region greatly influenced the length of growing period, start of planting season and also the yield. The simulated yield ranged from 400 q ha-1. The suitable locations for kharif potato cultivation along with potential yields are listed for plateau region of India.

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]

Understanding how changing climate and cultivars influence crop phenology and potential yield is essential for crop adaptation to future climate change. In this study, crop and daily weather data collected from six sites across the North China Plain were used to drive a crop model to analyze the impacts of climate change and cultivar development on the phenology and production of winter wheat from 1981 to 2005. Results showed that both the growth period (GP) and the vegetative growth period (VGP) decreased during the study period, whereas changes in the reproductive growth period (RGP) either increased slightly or had no significant trend. Although new cultivars could prolong the winter wheat phenology (0.3∼3.8 days per decade for GP), climate warming impacts were more significant and mainly accounted for the changes. The harvest index and kernel number per stem weight have significantly increased. Model simulation indicated that the yield of winter wheat exhibited increases (5.0∼19.4 %) if new cultivars were applied. Climate change demonstrated a negative effect on winter wheat yield as suggested by the simulation driven by climate data only (−3.3 to −54.8 kg ha year, except for Lushi). Results of this study also indicated that winter wheat cultivar development can compensate for the negative effects of future climatic change. [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]

The largest reported soybean grain yield is approximately three-fold more than the highest reported U.S. average yield. An understanding of yield determination is needed to identify avenues for increasing yield and for defining the yield potential of soybean. To illustrate physiological traits important for yield determination, we used a framework that models yield as the product of seed number (seed m −2 ) and individual seed mass (mass seed ). Developmentally, seed m −2 is determined first and is proportional to the biomass accumulation rate (BAR, g m −2 d −1 ) and the fraction of assimilate allocated to reproductive structures. Seed m −2 is inversely proportional to the individual seed growth rate (ISGR, mg seed −1 d −1 ) where the ISGR represents the minimum amount of assimilate necessary to prevent a flower or pod from aborting. Hence, seed m −2 can be increased by optimizing conditions for crop growth (e.g., radiation interception, stress-free environment, high soil fertility levels) and having a low ISGR. Determination of mass seed occurs later during ontogeny than seed m −2 and can be expressed as the product of the ISGR and the effective seedfilling period (EFP, d). Variation among genotypes for ISGR is quite large and is generally not affected greatly by the environment. There is also genotypic variation in the EFP, but the EFP is decreased by a variety of biotic and abiotic stresses. Our analysis indicates that reaching the potential yield of soybean depends upon high BAR and extending the EFP, and a key factor affecting both of these variables is ensuring non-limiting crop nutrition, especially nitrogen. Strategies for increasing soybean maximum yield include early planting (which extends the EFP), optimizing crop nutrition, minimizing biotic and abiotic stresses, and developing breeding programs tailored for high yield environments. Characterizing physiological traits important for yield with genetic markers offers tools for combining favorable traits for high-yield environments. [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]

Amid declining yield of apple (Malus domestica) in Balochistan, this study analyzed yield gaps of commonly grown varieties ‘Katja’ (Malus domestica ’Katy’) and Red Delicious (Malus domestica ‘Borkh’) grown at experimental station and in farmers’ fields using data collected through a survey of 181 officially designated small farmers in Mastung district in Balochistan, Pakistan. The average actual yields of commonly grown Katja and Red Delicious apple in farmers’ fields were below one-third of the experimental station yields, leading to an average experimental-station based yield gap (YGE) of about 14,593 and 15,942 kg hectare−1, respectively. A significant variation in the yields of both varieties was also found within farmers’ fields. The average yield gaps between the model-farmer (farmer with highest yield) and common farmer yields (YGM) were 4960 and 7288 kg hectare−1for Katja and Red Delicious, respectively. Yield gap indexes (YGI) were also developed to calculate yield variability between experimental station and current farmers’ yield (YGIE), and also within farmers’ yield variability (YGIM). The mean YGIEwas 69.3%, whereas the mean YGIMwas 46.5%, indicating the possibility of increasing yield by 53.5%. Farmer’s experience in apple farming, household labor force size, tree density, soil suitability, weed management, access to credit and extension services, and attendance of training on apple farming had significantly influenced apple yield gap. Landholding size and contract apple marketing system were other factors significantly expanding the yield gap. Addressing constraints to farmers’ access to yield-improving resources and farm management would be a vital step towards significant productivity improvements in apple farming. [ABSTRACT FROM AUTHOR]

Rapid urbanization in China has raised great concerns regarding food security caused by conversion of limited cultivated land to urban use. In this study, the loss of potential crop yield due to urban expansion in China during 1990-2010 was calculated by the Global Agro-Ecological Zones (GAEZ) model. Over this period, potential yield decreased by approximately 34.90 million tons due to urban expansion, accounting for 6.52 % of China's total actual production. The decrease was 13.07 and 21.83 million tons during the first and second decade, respectively. Key areas of lost potential yield were primarily in the Middle-lower Yangtze Plain and the Huang-Huai-Hai Plain. However, South China became a new key area of lost potential yield during the second decade. These findings provide useful information for the development of land use policy, protection of suitable arable land resources and urban development plans in China. [ABSTRACT FROM AUTHOR]