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Increasing feed grain supply, particularly domestic supply, is intended to guarantee feed grain security and, as a result, food security. Based on the Global Agro-Ecological Zones (GAEZ) model, the potential yield and actual yield of feed and food grain in China were estimated. According to the theory of factor endowment, the yield potential development coefficient and the yield efficiency advantage index were then constructed to determine whether the current spatial layout of feed grain is reasonable and how it could be adjusted. The results showed that: (1) There was an imbalance in feed crops production: yield loss in high-potential regions and excessive development in low-potential regions. The imbalances lead to a mismatch between feed production and resource endowment which causes productivity losses and ecological risks. (2) There was considerable potential for increasing the feed grain yield on the Northeast China Plain, the Loess Plateau and in the northern arid and semiarid region. The soybean yield can be increased by about 25%, and the maize yield can be increased by even more. (3) The feed grain should be planted in regions with sufficient potential yield but insufficient actual yield; 26.42% of China's soybeans and 34.74% of its maize were planted in these regions. (4) Some 16.69% and 15.65% of wheat and rice planting areas could be adjusted to soybeans, respectively; 20.76% and 21.04% of wheat and rice planting areas could be adjusted to maize, respectively. Through agricultural technology research and development, infrastructure support, comprehensive planning design and policy design, the yield potentials of feed grain can be realized. This will redress the imbalance wherein a food grain surplus and a feed grain shortage coexist. [ABSTRACT FROM AUTHOR]

IntroductionCassava production is essential for food security in sub-Saharan Africa and serves as a major calorie-intake source in Nigeria. Estimating the yield gap in Nigeria is essential to indicate the most important limiting factors for production, and identify the yield gap hotspot areas. Secondly, these assessments may help set agendas in policy development and research prioritization where current information is scarce.Materials and methodsHere, Wwe used a crop model, LINTUL5, calibrated for five different cassava varieties based on field experiments embedded into a modeling framework SIMPLACE to estimate potential, water- and nutrient (current) limited cassava yield gaps (YG) as affected by climate factors and contributing a better understanding of yield gaps and its potentials in 30 states of Nigeria.ResultsOur study shows that cumulative radiation and precipitation were the most significant factors associated with cassava yield variability (p < 0.01). The YG averaged across states was estimated as 18.2 Ton7ha-1, with a maximum of 31.2 Ton7ha-1 35 in Kano state. Across the states, nutrient limitation accounts for 55.3% of the total cassava yield gap, while the remaining 44.7% is attributed to water limitation. The highest untapped water-limited yields were estimated in the northern states, such as Bauchi, Gombe, and Sokoto, characterized by the short rainy season.ConclusionOur results showed that most northern states are better equipped to become leading cassava producers in Nigeria under adequate crop management practices involving irrigation and soil fertility enhancement. We reached this conclusion because the northern states usually receive the highest radiation from their characteristic reduced cloud cover, even Therefore, policy and management interventions can be prioritized in these areas. Conclusively, the current cassava yield levels can be increased by a factor of five by emphasizing nutrient and soil health management and irrigation, particularly in areas characterized by a shorter rainy season (Sudan Savanna) in Nigeria.

IntroductionBarley (Hordeum vulgare L.) is considered as the second most important grain crop after wheat, due to 1.75 million hectares harvested areas and 3.2 million tons’ production in Iran. The irrigated fields are contributed up to 45% of total barley harvested areas (equivalent to 1.7 million ha) and 70% of total barley production (equivalent to 2.2 million tons). Based on the statistics reported in recent years, about 2.5 million tons of barley imported from other countries. According to the impossibility of extending the barley cultivated areas and even the necessity of reducing fields in some parts of the country, increasing productivity per unit area of cultivated lands is recognized as the only practical way to boost the production of barley in Iran. In this regard, this study was conducted to estimate barley yield gap (Yg) and the potential of increasing barley production in irrigated condition as the first step to promote the yield and production of barley over the country.Materials and MethodsFirstly, the main production zones of barley are determined; the zones which were contributed in more than 85% of barley production. The Designated climatic zones (DCZs) were identified using GYGA climatic zones (Global Yield Gap Atlas) and the distribution of barley harvested area raster layers. Subsequently, the Reference weather Stations (RWSs) within the DCZs were selected based on the values of the harvested area, and the types of soil in each of RWSs were determined by using of HC-27 soil map. SSM-iCrop2 as a crop simulation model has been employed to estimate the potential yield (Yp) in the RWSs of cultivated areas, which has previously been parameterized and evaluated, and the results have indicated the robustness of the model for simulating barley yield over the country. For estimating Yg, the data of actual yield (Ya) and the agronomic management data for estimating Yp during 15 growing seasons (2000-2014), were collected at RWSs scale. Using A bottom-up approach, the yield, and production gap values were calculated at RWSs and subsequently aggregated to DCZs and finally, extended from DCZ to country-level according to the spatial distribution of crop area and climate zones.Results and DiscussionBased on GYGA protocol, 48 RWSs within 12 DCZs of irrigated barley harvested areas were demonstrated. Aggregation from the RWSs results to DCZs illustrated that the average of potential yield in DCZs of irrigated barley was estimated 7090 kg.ha-1 and the range varied from 5283 to 8286 kg.ha-1. Nevertheless, the Ya range in these climate zones was calculated between 1406 and 3723 with an average of 3009 kg.ha-1. According to the results, the DCZs which confronted to higher temperatures during the growing season have lower yields and also a significant reverse correlation between the potential yield and the growth length period (R2 = 0.88 and p ≤0.01) were shown. The correlation between total received daily solar radiation during the growing and Yp in the DCZs was significant, positively season (R2 = 0.98 and p ≤0.01). At present, the range of difference between actual and potential yield varies between 3237 to 4697 kg.ha-1 with an average of 4081 kg.ha-1 (equivalent to 58% yield gap). In other words, just around 24 to 50 percent (on an average of 42 percent) of estimated Yp in irrigated barley fields can be attainable. According to the irrigated barley harvested areas, the actual and potential production gap are calculated about 2.21 and 2.99 million tons in the country, respectively, and under the best management condition can lead the production to be about 4.17 million tons.ConclusionAccording to the results, it was demonstrated about 58% relative yield gap between the averages of actual yield (3008 kg.ha-1) and potential yield (7090 kg.ha-1), which can be reduced by improving the production management in irrigated barley cultivated areas. For this reason, the current production of barley in irrigated lands can be increased from 2.12 to 4.17 million tons. This increase in production (1.96 million tons) could provide a significant part of the country's need to the barley and bring the country closer to achieve full self-sufficiency.

The present study tries to estimate the yield gap of irrigated canola in Iran as the first step for planning sustainable improvement of production. It has been performed in the modeling laboratory2 of Gorgan University of Agricultural Sciences and Natural Resources in 2017-2019. The protocol provided by the GYGA project is used for detection of climatic zones as well as major weather stations in canola production regions to estimate the yield gap. The actual yield of the irrigated canola in its major production regions is between 1184 to 2358 kg ha-1. The range of potential yield is estimated between and 3823 and 6520 kg ha-1. The highest potential yields belongs to Hamedan and Lorestan provinces and the lowest value to Khuzestan Plain. The range of the yield gap in its major production regions in the country is 2480 to 4365 kg ha-1, i.e. 53% to 77% of gap and with an average, 3276 kg ha-1 equal to 65% of the gap. With respect to the exploitable yield as the target yield, the exploitable yield is between 1544 and 3208 kg ha-1, with an average of 2261 kg ha-1. The magnitude of this gap indicates that the potentials of canola production in Iran are not exploited properly. Analyzing the reasons and methods of amendment the present yield gap and adoption of efficient management methods to achieve higher yields is crucial with regard to food security and economic. [ABSTRACT FROM AUTHOR]

Increasing feed grain supply, particularly domestic supply, is intended to guarantee feed grain security and, as a result, food security. Based on the Global Agro-Ecological Zones (GAEZ) model, the potential yield and actual yield of feed and food grain in China were estimated. According to the theory of factor endowment, the yield potential development coefficient and the yield efficiency advantage index were then constructed to determine whether the current spatial layout of feed grain is reasonable and how it could be adjusted. The results showed that: (1) There was an imbalance in feed crops production: yield loss in high-potential regions and excessive development in low-potential regions. The imbalances lead to a mismatch between feed production and resource endowment which causes productivity losses and ecological risks. (2) There was considerable potential for increasing the feed grain yield on the Northeast China Plain, the Loess Plateau and in the northern arid and semiarid region. The soybean yield can be increased by about 25%, and the maize yield can be increased by even more. (3) The feed grain should be planted in regions with sufficient potential yield but insufficient actual yield; 26.42% of China’s soybeans and 34.74% of its maize were planted in these regions. (4) Some 16.69% and 15.65% of wheat and rice planting areas could be adjusted to soybeans, respectively; 20.76% and 21.04% of wheat and rice planting areas could be adjusted to maize, respectively. Through agricultural technology research and development, infrastructure support, comprehensive planning design and policy design, the yield potentials of feed grain can be realized. This will redress the imbalance wherein a food grain surplus and a feed grain shortage coexist.

The concept of yield gaps provides a basis for identifying the main sources of production losses, caused by water or management deficiencies, which may help foresters and forest companies to better plan and make decisions in their areas. Thus, the aim of this study was to identify the magnitude and the major causes of yield gaps of eucalypts, being this the most planted forest genus in Brazil, in different producing regions of the state of Minas Gerais that has the largest planted area. To these ends, potential (Yp) and attainable (Ya) yields were simulated using the agroecological zone model (AEZ-FAO) adapted and calibrated for Brazilian eucalypt clones. Actual yield (Yr) data were obtained from 22 sites located in the state of Minas Gerais from 2009 to 2016, considering an average forest rotation of 6.7 years and plantings occurring between 2002 and 2010. From this, the total yield gap (YGtot), yield gap by water deficit (YGwd), and yield gap by sub-optimal management (YGman) were determined. The YGwd ranged from 37 to 69 m3 ha−1 year−1 across the 22 sites assessed, with an average value of 55 m3 ha−1 year−1. On the other hand, the YGman ranged from zero (optimal management) to 31 m3 ha−1 year−1. The eucalypt yield gap in commercial areas of Minas Gerais state was mainly caused by water deficit, which represented 77% of the total yield gap. On the other hand, the deficiencies in forest management accounted for 23% of the total yield gap. [ABSTRACT FROM AUTHOR]

For ensuring food demand of the fast growing population in developing countries, quantification of crop yield gaps and exploring production constraints are very crucial. Sorghum is one of the most important climate change resilient crops in the rainfed farming systems of semi-arid tropics. However, there is little information about yield gaps and production constraints. This study aimed at analysing existing yield gaps and exploring major constraints of sorghum production in Southwest Ethiopia. A crop simulation model approach using AquaCrop and DSSAT was used to estimate potential yield and analyse the yield gaps. Model calibration and evaluation was performed using data from field experiments conducted in 2018 and 2019. Sorghum production constraints were assessed using a survey. The actual and water-limited yield of sorghum ranged from 0.58 to 2.51 and 3.6 to 6.47 t/ha, respectively for the period 2003–17. The regional yield gaps of sorghum for the targeted period were 3.02–3.95 t/ha with a mean value of 3.51 t/ha. Majority of respondent farmers considered seasonal rainfall risk (98%), poor soil fertility (86%), lack of improved varieties (78%) and inadequate weed management (56%) as major factors responsible for the existing yield gaps. The mean exploitable yield gap (2.5 t/ha) between water-limited and actual yield showed the level of existing opportunity for improvement in the actual productivity of sorghum. The gaps also call for introduction of proper interventions such as adoption of improved varieties, planting date adjustment, conservation tillage, fertilizer application and on time weed management. [ABSTRACT FROM AUTHOR]

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]

Africa has the largest population growth rate in the world and an agricultural system characterized by the predominance of smallholder farmers. Improving food security in Africa will require a good understanding of farming systems yields as well as reducing yield gaps (i.e., the difference between potential yield and actual farmer yield). To this end, crop yield gap practices in African countries need to be understood to fill this gap while decreasing the environmental impacts of agricultural systems. For instance, the variability of yields has been demonstrated to be strongly controlled by soil fertilizer use, irrigation management, soil attribute, and the climate. Consequently, the quantitative assessment and mapping information of soil attributes such as nitrogen (N), phosphorus (P), potassium (K), soil organic carbon (SOC), moisture content (MC), and soil texture (i.e., clay, sand and silt contents) on the ground are essential to potentially reducing the yield gap. However, to assess, measure, and monitor these soil yield-related parameters in the field, there is a need for rapid, accurate, and inexpensive methods. Recent advances in remote sensing technologies and high computational performances offer a unique opportunity to implement cost-effective spatiotemporal methods for estimating crop yield with important levels of scalability. However, researchers and scientists in Africa are not taking advantage of the opportunity of increasingly available geospatial remote sensing technologies and data for yield studies. The objectives of this report are to (i) conduct a review of scientific literature on the current status of African yield gap analysis research and their variation in regard to soil properties management by using remote sensing techniques; (ii) review and describe optimal yield practices in Africa; and (iii) identify gaps and limitations to higher yields in African smallholder farms and propose possible improvements. Our literature reviewed 80 publications and covered a period of 22 years (1998-2020) over many selected African countries with a potential yield improvement. Our results found that (i) the number of agriculture yield-focused remote sensing studies has gradually increased, with the largest proportion of studies published during the last 15 years; (ii) most studies were conducted exclusively using multispectral Landsat and Sentinel sensors; and (iii) over the past decade, hyperspectral imagery has contributed to a better understanding of yield gap analysis compared to multispectral imagery; (iv) soil nutrients (i.e., NPK) are not the main factor influencing the studied crop productivity in Africa, whereas clay, SOC, and soil pH were the most examined soil properties in prior papers.

To reduce the yield gap, specifying yield constraints in a particular area is necessary. A complete yield gap assessment method must provide information regarding potential yield, actual yield, and causes of the gap and their importance. Therefore, documenting the production process to explain crop management factors in each area is very important. The objective of the study was to perform a rice yield gap analysis by using comparative performance analysis (CPA) and boundary-line analysis (BLA). Data were gathered from about 100 paddy fields in Neka, eastern Mazandaran province, one of the major rice producing regions in Iran, in 2015 and 2016. All agricultural practices from nursery preparation to harvest have been recorded for improved rice cultivars. CPA focuses on the ability to estimate potential yield and the reason for a yield gap. Boundary lines were fitted to the edge of the data cloud of crop yield versus management variables in data from paddy fields monitoring. The documenting analysis shows that the range of paddy yield in 100 fields varied from 6100 to 8200 kg ha–1. Potential yields were 9241 kg ha–1 for CPA method, and 7999 kg ha–1 for BLA method. Furthermore, yield gap predicted 2047 kg ha–1 for CPA method and 874 kg ha–1 for BLA method. In BLA, the average relative yield and relative yield gap of the 13 investigated variables were 89.75% and 10.25% respectively. These results show the importance of each management factor in yield gap. It was concluded that CPA and BLA as applied in the study is a cheap and simple method that, without the need for expensive experimentation, is able to detect yield gap and its causes in a district. From these results, it can be said that the calculated yield gap is close to the definition given for the utilised yield gap and shows the difference between the actual yield and attainable yield in relation to the environmental conditions of the region.

To reduce the yield gap, specifying yield constraints in a particular area is necessary. A complete yield gap assessment method must provide information regarding potential yield, actual yield, and causes of the gap and their importance. Therefore, documenting the production process to explain crop management factors in each area is very important. The objective of the study was to perform a rice yield gap analysis by using comparative performance analysis (CPA) and boundary-line analysis (BLA). Data were gathered from about 100 paddy fields in Neka, eastern Mazandaran province, one of the major rice producing regions in Iran, in 2015 and 2016. All agricultural practices from nursery preparation to harvest have been recorded for improved rice cultivars. CPA focuses on the ability to estimate potential yield and the reason for a yield gap. Boundary lines were fitted to the edge of the data cloud of crop yield versus management variables in data from paddy fields monitoring. The documenting analysis shows that the range of paddy yield in 100 fields varied from 6100 to 8200 kg ha-1. Potential yields were 9241 kg ha-1 for CPA method, and 7999 kg ha-1 for BLA method. Furthermore, yield gap predicted 2047 kg ha-1 for CPA method and 874 kg ha-1 for BLA method. In BLA, the average relative yield and relative yield gap of the 13 investigated variables were 89.75% and 10.25% respectively. These results show the importance of each management factor in yield gap. It was concluded that CPA and BLA as applied in the study is a cheap and simple method that, without the need for expensive experimentation, is able to detect yield gap and its causes in a district. From these results, it can be said that the calculated yield gap is close to the definition given for the utilised yield gap and shows the difference between the actual yield and attainable yield in relation to the environmental conditions of the region. [ABSTRACT FROM AUTHOR]

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.

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.

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]

Barley (Hordeum vulgare. L) is adapted to drought and salinity as the most critical constrained factors in Iran's crop production. Hence, the grain barley's importance is exhibited via 1.75 million hectares of harvested areas and 3.2 million tons of production in the country with arid and semi-arid climate conditions. However, the current production status meets only about 50% of Iran's barley's grain demands and is globally recognized as one of the largest barley importers in recent years. This study aimed to estimate the potential and yield gap and the potential barley grain production increase under the irrigated and rainfed conditions as the first step in schematizing the promotion of barley production. The impact of determinant climate factors on barley yields was also investigated at dominant barley productions regions over Iran. The present study approach is implemented based on the Global Yield Gap Atlas (GYGA). Accordingly, 12 and 17 designated climatic zones (DCZ), are distinguished as the dominant areas of the irrigated and rainfed barley production in the country, respectively. Afterwards, 48 and 38 reference weather stations (RWSs) within the DCZs were distributed to irrigated and rainfed barley harvested areas, respectively. The SSM-iCrop2 crop model was employed to simulate potential yield in irrigated (Y p) and rainfed (Y w) conditions by utilization of required data in each RWS through 15 barley growing seasons (2000–2014). The yield gap (the difference between simulated potential yield (Y p or Y w) and actual yield (Y a)) were calculated based on the bottom-up approach of GYGA in RWSs, DCZs and national-scale, respectively. Based on the results, the estimated potential yield varies between 5283 and 8286 kg/ha (with an average of 7090 kg/ha) in irrigated condition, and in the case of rainfed barley ranged between 1072 and 4002 kg/ha (with an average of 2723 kg/ha). In contrast, the actual yield in the DCZs was reported in the range of 1406 and 3723 kg/ha (with an average of 3009 kg/ha) for irrigated barley and ranged around 390–1510 kg/ha in rainfed conditions (with an average of 1009 kg/ha). According to the results, the DCZs that are confronted with higher temperatures and shorter growth length periods due to less total received daily solar radiation have low yields in irrigated conditions. In rainfed barley harvested areas, a significant correlation between rainfall distribution, high temperature and Yw has existed during the reproductive phase within 17 DCZs. Ultimately, the results indicated that the calculated yield gap varies between 3237 and 4697 kg/ha (50–76%) with an average of 4081 kg/ha (58%), and also between 615 and 3125 kg/ha (53–82%) with an average of 1714 kg/ha (63%) in the DCZs of irrigated and rainfed barley harvested areas, respectively. Consequently, it has been concluded that by achieving attainable yield (80% of potential yield) via improving production management, irrigated barley yield production can be increased to 5672 kg/ha and 4.17 million tons, respectively, provided that water resources are available. It can also be exploitable to increase rainfed barley's current yield and production from 1009 to 2178 kg/ha and 1.05–2.26 million tons, respectively. Finally, it makes sense to be inspired by increasing total national barley production from 3.26 to 6.43 million tons per year and bring the country closer to obtain full self-sufficiency in supplying the required barley grain. • The bottom-up framework was implemented to assess barley production and yield gap in Iran. • Irrigated and rainfed barley yield varied across different agro-climatic zones due to different determinant climate factors. • The national potential yield of irrigated (Yp) and rainfed (Yw) barley was estimated at 7090 and 2723 kg. ha−1, respectively. • The average yield gap exhibited 58% (under irrigation) and 64% (under rainfed) of potential barley yield. • Closure of 1.17 million tons exploitable gap in production meets the country's demand for barley grain. [ABSTRACT FROM AUTHOR]

The significance results of the paper to the readers of the Ecological modeling is: • This is the first report to analysis of potato potential yield, yield gap based on GYGA protocol in Iran. • According to the results, the average Y p was 67.3 t. ha-1 and actual yield (Ya) was 30 t ha-1. • Iranian farmers produced 5 million tons of potato from about 164000 ha. If they can obtain only 80% of Yp (53.8 t. ha-1), amount of potato production will be 8.8 million tones. • As result, they can produce 5.2 million tons tuber yield of potato in 97000 ha cultivation area. Thus, with closing yield gap and increasing potato production, it is possible to decrease potato lands. Understanding yield potential (Yp) and yield gap (Yg) in current intensive potato (solanum tuberosum L.) production is essential to meet future food demand with the limited resources. Evaluating yield gap is a strong approach to estimate maximum production potential when all factors are in the best condition. A complete estimation of yield gap and potential yield across all major potato producing regions in Iran is lacking. The global yield gap atlas (GYGA) protocol was used to estimate potential yield of potato in Iran. This protocol is based on the climatic zones (CZs) and the reference weather stations (RWS) buffer zones, soil types in each buffer zone. Thirty-five RWS buffer zones in potato producing regions were selected, and total potato area in the RWS buffer zones covered 83% of the whole potato harvest area. According to the results, the average Y p was 67.3 t ha–1 and actual yield (Y a) was 30 t ha–1. Therefore, the average tuber yield gap was 37.3 t ha–1. These results indicate that the Potato producers achieved 45% of the potential yield in Iran. Iranian farmers produced 5 million tons of potato from about 164,000 ha. If they can obtain only 80% of Y p (53.8 t ha–1), amount of potato production will be 8.8 million tones. As result, they can produce 5.2 million tons tuber yield of potato in 97,000 ha cultivation area. Thus, with closing yield gap and increasing potato production, it is possible to decrease potato lands. [ABSTRACT FROM AUTHOR]

Yield gap analysis provides an essential framework to prioritize research and policy efforts to reduce yield constraints. To identify options for increasing chickpea yield, the SSM-chickpea model was parameterized and evaluated. The model was applied to analyze seed yield at both potential and water limited production levels and subsequently to find the yield gap for nine different locations. Study locations are selected to represent major chickpea-growing areas of Khorasan Razavi province (located between 37° N and 33° S latitude and 61° E and 56° W longitude). The average simulated potential yield of chickpea across all study locations was 2251 kg ha-1, while for the water limited yield was 1026 kg ha -1, indicating 54% lower due to adverse soil moisture conditions. Average irrigated and rainfed actual yields were 64% and 79% less than simulated potential and water limited yields respectively. Maximum and minimum of simulated potential yield minus simulated water limited yield (YGMM) and simulated potential yield minus irrigated actual yield (YGMI) were observed in Torbat-Jam and Quchan, respectively. Generally, YGMI and YGMM showed an increasing trend from the north (including Neishabur, Mashhad, Quchan and Daregaz) to the south of the study province (Torbat-Jam and Gonabad). In comparison to other indices, simulated water limited yield minus rainfed actual yield (YGMR) was very low because both simulated water limited and average rainfed actual yields were low in these locations. Overall, YGMR was almost unaffected by the quantity of rainfall received at these locations. [ABSTRACT FROM AUTHOR]

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The article highlights potential features for the varieties of vegetable bean and actual losses of yield subject to the total amount of photosynthetically active radiation (PAR) received over the vegetation period in the Forest-Steppe of Ukraine. It is established that the potential of the vegetable bean yield in Ukraine depends on PAR received over the vegetation period. All the varieties had their yield upon receiving PAR higher by 0,26-0,41 t / ha compared to that of control. Potential yield of vegetable bean varieties when PAR is used by 2% amounted to 57.25–59.30 t / ha, which was 2.2–3.6 times more than their actual yield. The smallest actual yield loss compared to that potential was inherent in the varieties of Bartoli and Windsor (2.2–2.3 times). The actual yield losses for Karadag and Karestyno varieties were the highest, namely 3.6 times higher compared to the potential prospect.

Cocoa (Theobroma cacao) progenies in a field trial showed a mean yield loss of 10.3% due to unusable pods. This was equivalent to an annual loss of 98 kg ha-1 of dry beans, and 64.1% (62.8 kg ha-1), 30.5% (29.9 kg ha-1), 4.1% (4.0 kg ha-1) and 1.3% (1.4 kg ha-1) were due to black pods, immature ripe pods, rodent damage and other damage, respectively. Copyright © 2006 John Wiley & Sons, Ltd [ABSTRACT FROM AUTHOR]

Africa has the largest population growth rate in the world and an agricultural system characterized by the predominance of smallholder farmers. Improving food security in Africa will require a good understanding of farming systems yields as well as reducing yield gaps (i.e., the difference between potential yield and actual farmer yield). To this end, crop yield gap practices in African countries need to be understood to fill this gap while decreasing the environmental impacts of agricultural systems. For instance, the variability of yields has been demonstrated to be strongly controlled by soil fertilizer use, irrigation management, soil attribute, and the climate. Consequently, the quantitative assessment and mapping information of soil attributes such as nitrogen (N), phosphorus (P), potassium (K), soil organic carbon (SOC), moisture content (MC), and soil texture (i.e., clay, sand and silt contents) on the ground are essential to potentially reducing the yield gap. However, to assess, measure, and monitor these soil yield-related parameters in the field, there is a need for rapid, accurate, and inexpensive methods. Recent advances in remote sensing technologies and high computational performances offer a unique opportunity to implement cost-effective spatiotemporal methods for estimating crop yield with important levels of scalability. However, researchers and scientists in Africa are not taking advantage of the opportunity of increasingly available geospatial remote sensing technologies and data for yield studies. The objectives of this report are to (i) conduct a review of scientific literature on the current status of African yield gap analysis research and their variation in regard to soil properties management by using remote sensing techniques; (ii) review and describe optimal yield practices in Africa; and (iii) identify gaps and limitations to higher yields in African smallholder farms and propose possible improvements. Our literature reviewed 80 publications and covered a period of 22 years (1998-2020) over many selected African countries with a potential yield improvement. Our results found that (i) the number of agriculture yield-focused remote sensing studies has gradually increased, with the largest proportion of studies published during the last 15 years; (ii) most studies were conducted exclusively using multispectral Landsat and Sentinel sensors; and (iii) over the past decade, hyperspectral imagery has contributed to a better understanding of yield gap analysis compared to multispectral imagery; (iv) soil nutrients (i.e., NPK) are not the main factor influencing the studied crop productivity in Africa, whereas clay, SOC, and soil pH were the most examined soil properties in prior papers. [ABSTRACT FROM AUTHOR]