Highest Yield Gap Research Articles

Assessing yield gap in paddy cultivation: A case study from Shivamogga district, Karnataka

Paddy cultivation is a cornerstone of India’s agricultural economy, with Karnataka emerging as a key contributor to this sector. Despite its significance, persistent yield gaps across various paddy varieties pose a considerable challenge to achieving optimal productivity. These yield gaps primarily stem from factors such as traditional farming practices, resource availability, and varying environmental conditions. This study aimed to comprehensively assess the yield gap of paddy varieties specifically in the Shivamogga district of Karnataka, employing an ex-post facto research design to identify key factors influencing yield gaps. Data were systematically collected from a sample of 197 farmers using a structured interview schedule, ensuring a comprehensive analysis. The study identified four primary paddy varieties cultivated by the respondents: Jyothi, JGL-1798, MTU-1001, and MTU-1010 representing the major paddy varieties in the region. Notably, the highest yield gap was observed in the JGL-1798 variety, recording a gap of 19.33 quintals per hectare, followed closely by MTU-1010 at 18.89 q/ha, MTU-1001 at 17.50 q/ha, and Jyothi at 13.42 q/ha. The Jyothi variety exhibited the lowest yield gap, highlighting its superior adaptability and market preference. This study underscores the critical need to address the underlying factors contributing to yield gaps through enhanced agricultural practices and technology dissemination, ultimately fostering increased productivity and contributing to food security and farmers’ income in Karnataka.

Georgia’s potentials for sustainable intensification, increasing food security and rural incomes

Abstract Increasing global demand for agricultural commodities spurs conversions of natural ecosystems. Sustainable intensification in areas of high yield gaps has been proposed as a pathway to achieve food security, support rural livelihoods, and improve resource efficiency while also reducing the impact of commodity production by narrowing yield gaps on existing agricultural lands. Following the dissolution of the Union of Soviet Socialist Republics (USSR), Georgia experienced one of the highest losses of agricultural productivity among all former USSR countries and is now highly dependent on food imports. Closing yield gaps in Georgia through sustainable intensification has the potential to increase food self-sufficiency, support rural livelihoods, and strengthen food security and sovereignty. We estimated Georgia’s potential for sustainable intensification in current agricultural areas to achieve self-sufficiency for wheat, maize, and barley. We found that crop yields can be doubled to tripled under high-input production systems, using high-yielding varieties, optimized inputs, fertilizers, and pest control. Yet, self-sufficiency in wheat can only be reached if at least 80% of the attainable yields are achieved and if land is strategically allocated between crops. To achieve such increases, farmers need access to and training for using different crop varieties, fertilizers, and pest and disease control practices and products. Intensification with very high levels of inputs can increase the ecological and human risks of agriculture and raise equity concerns. Yet, intensifying very low input agricultural production systems is often found to be more sustainable, with high yield increases compared to limited impacts on the environment. The high employment rate in the agricultural sector in Georgia provides opportunities for intensification to help reduce poverty and improve livelihoods by increasing incomes and food security.

Simulation of Intra-seasonal Climatic Variability, Potential Yield and Yield Gap of Sugarcane for the South Gujarat Region, India

The validated CANEGRO (DSSAT v4.7) model was used to simulate the intra-seasonal climatic variation viz. temperature (-3oC to +3oC) and rainfall (-25% to +25%) variability in sugarcane yield and quantifying the yield gap of sugarcane at Navsari, Bharuch, Surat and Valsad districts of south Gujarat region under the various management options included dates of planting, irrigations and fertilizers application and compared with the reported yield of the districts. The cane yield increased with an increase in rainfall and a decrease in temperature. In contrast, the cane yield decreased with a decrease in rainfall and an increase in temperature. The extent of effect was found to vary with crop growth stages. The potential yield of sugarcane simulated by the model in different districts was found to vary between 107.0 to 114.7 t ha-1, while the reported yield in these districts varied between 68.1 to 72.0 t ha-1. This resulted in a total yield gap between 38.9 to 45.5 t ha-1 in different districts. The highest yield gap was in Navsari district while the lowest yield gap was found in Bharuch district.

Dye-Containing Polymers with π-Extened Diketopyrropyrrole Derivatives for Semi-Transparent Organic Photovoltaics.

Dye-containing polymers P1 (PEDPP-OT-BDT) and P2 (PEDPP-OT-BDTT) including a π-extended diketopyropyrrole (DPP) derivative and electron-rich thiophene fused ring units (4,8-bis((2-ethylhexyl)oxy)benzo[1,2-b:4,5-b']dithiophene for P1 and 4,8-bis(5-(2-ethylhexyl)thiophen-2-yl)benzo[1,2-b:4,5-b']dithiophene for P2) were synthesized as narrow band gap dyes. A π-extended DPP (EDPP-OT-BrPh), fragment of the polymers P1 and P2, was obtained by extending the π-conjugation of DPP using Ru(III)-catalyzed C-H and N-H activation reported by Gońka et al. in 2019, exhibiting a high quantum yield (ϕem=0.84) and small HOMO-LUMO gap (Eg=1.69 eV) due to the spatial overlap of the HOMO and LUMO orbitals. The solubility of the π-extended DPP was improved by introducing four 2-octylthophene side chains around the periphery of the planer dye moiety, while maintaining the high planarity of the dye molecule, which is essential to the function of optoelectronic devices. As a result, P1 and P2, polymerized with the π-extended DPP and BDT derivatives, exhibit carrier mobility of approximately 10-5 cm2/Vs in organic field-effect transistors (OFETs). In bulk heterojunction (BHJ) solar cells with [6,6]-phenyl-C61-butyric acid methyl ester (PCBM), they demonstrate a power conversion efficiency (PCE) of 1.0 % with an average transmittance (AVTs) of around 60 %.

Advanced prediction of rice yield gaps under climate uncertainty using machine learning techniques in Eastern India

The current study focuses on applying machine learning approaches to forecast future Kharif rice yield gaps in eastern India while accounting for climate change implications. To achieve the United Nations Sustainable Development Goals (SDGs), food security must be prioritized. Rice yield has been predicted using Cubist, GBM, MARS, RF, SVM, and XGB machine learning methods, considering six factors: elevation, soil moisture, precipitation, temperature, soil temperature, and actual evapotranspiration. Climatic change scenarios were generated using the latest climatic Coupled Model Intercomparison Project Phase 6 (CMIP6 MIROC6) Shared Socioeconomic Pathways (SSP) 2–4.5 and SSP5-8.5 datasets between 1990 and 2030. Finally, machine learning algorithms were used to identify rice yield gaps to achieve sustainable agricultural intensification. The rice yield validation was completed with 1889 field-based farmer observation records. The results suggest that Murshidabad and Purba Bardhaman districts had very high rice yields (5.60–3.45 t/ha) when using the Cubist model compared to another model. The findings also reveal a poor rice-yielding zone (1.44–0.39 t/ha) in the western region (Purulia) and a northwestern region (half of the west of Birbhum). The Cubist and RF models' maximum and minimum R2 values were 0.73 and 0.72, respectively. The R2 values were also negligible for the XGB, GBM, SVM, and MARS, machine learning models. Projections for rice production in 2030 indicate that the northern and north-eastern regions (Murshidabad and Purba Bardhaman) as well as the southeastern areas (Jhargram and Paschim Medinipur) have the highest yields, categorized as extremely very high (5.56–3.49 t/ha) and high (3.49–2.49 t/ha). A significant rice yield gap (50-40 %) was found in the center and south-east areas (Bankura, Jhargram, and Paschim Medinipur), the northern region (Murshidabad and Birbhum), and the western region (Purulia). In 2030, the north-western region (Birbhum), as well as the middle and south-eastern regions (Bankura, Jhargram, and Paschim Medinipur districts), had the highest proportion of high (50%–40 %) and very high (60%–50 %) rice yield gap. Our findings can contribute to a new viewpoint on agricultural planning and management for sustainable growth in the face of changing climate circumstances.

Silicon distyryl-BODIPY hybrid photodiode: moving a step ahead from organic interface layer to type II band alignment

Organic-inorganic heterojunctions are becoming an attractive topic of research for their applications in hybrid photodetectors, solar cells, resistive switching memory devices etc. The easy chemical synthesis and low-cost fabrication for organic thin films come with the benefit of high light absorptivity, high fluorescence quantum yield and band gap tunability along with high charge carrier lifetime that could be combined with the existing silicon-based technology. In this aspect, various organic dyes utilised as an interfacial layer with silicon Schottky junction are reported earlier. However, the photo responses are quite limited. Here, in this report, a Type II Silicon/Distyryl-BODIPY p-n junction has been proposed as an organic-inorganic hybrid photodetector which has not been explored extensively yet. The transformation from a mere organic interfacial layer to band aligned junction enhances the charge carrier separation providing higher photo-responsive behaviour. With the simple spin-coating technique, the Distyryl-BODIPY derivative with phenolic functionalities is coated to fabricate the p-n junction diode. To further improve the performance, pyramidal surface texturization on silicon is deployed using wet chemical etching that supplements the light absorption with internal reflections. Both the devices have been investigated for their photo-response characteristic where a high photo-responsivity of 4353 A W−1 is attained for the textured device as compared to 118 A W−1 for the planar silicon device at a − 3 V bias with an ultra-high specific detectivity of 1012 Jones and 1010 Jones respectively. The behaviours of interfacial states have been demonstrated using the capacitance (C), conductance (G) and series resistance (RS) vs voltage (V) curves at different frequencies. Further calculations of interfacial state density revealed the existence of 1000 times higher interfacial states in planar device leading to lower performance as compared to pyramidal device. The findings in this report suggest that dye-based organic-inorganic heterostructures find potential applications in photodetectors and other optoelectronic devices.

Grapevine yield gap: identification of environmental limitations by soil and climate zoning in the region of Languedoc-Roussillon (South of France)

Often unable to fulfill theoretical production potentials and to obtain the maximum yields set by wine quality labels, many vineyards and cellars need to solve the issue of so-called grapevine yield gaps in order to assure their durability. These yield gaps particularly occur in Mediterranean wine regions, where extreme events have intensified because of climate change. Yield gaps at the regional level have been widely studied in arable crops using big datasets, but much less so in perennial crops, such as grapevine. Understanding the environmental factors involved in yield gaps, such as those linked to climate and soil, is the first step in grapevine yield gap analysis. At a regional scale, there are numerous studies on ‘terroir’ linked to wine typicity and quality; however, none have classified spatial zones based on environmental factors identified as being involved in grapevine yield. In the present study, we aggregated into one big dataset information obtained from producers at the municipality level in the wine region Languedoc-Roussillon (South of France) between 2010 and 2018. We used a backward stepwise model selection process using linear mixed-effect models to discriminate and select the statistically significant indicators capable of estimating grapevine yield at the municipality level. We then determined spatial zones by using the selected indicators to create clusters of municipalities with similar soil and climate characteristics. Finally, we analysed the indicators of each zone related to the grapevine yield gap, as well as the variations among the grapevine varieties in the zones. Our selection process evidenced 6 factors that could explain annual grapevine yield annually (R2 = 0.112) and average yield for the whole period (R2 = 0.546): Soil Available Water Capacity (SAWC), soil pH, Huglin Index, the Climate Dryness Index, the number of Very Hot Days and Days of Frost. The clustering results show seven different zones with two marked yield gap levels, although all the zones had municipalities with no or high yield gaps. On each zone, grapevine yield was found to be driven by a combination of climate and soil factors, rather than by a single environmental factor. The white wine varieties showed larger yield gaps than the red and rosé wine varieties. Environmental factors at this scale largely explained yield variability across the municipalities, but they were not performant in terms of annual yield prediction. Further research is required on the interactions between environmental variables and plant material and farming practices, as well as on vineyard strategies, which also play an important role in grapevine yield gaps at vineyard and regional scale.

Assessing land suitability and spatial variability in lucerne yields across New Zealand

Lucerne (Medicago sativa L.) is a widely grown perennial legume worldwide which can provide high biomass and protein yields, biological N fixation, deep soil water extraction and a range of ecosystems services relevant to current and future agricultural systems. The potential to expand lucerne beyond its current cultivated areas in New Zealand, and its potential productivity across the country’s contrasting climate zones, are currently unknown. To gain such insights, we estimated land suitability and spatial distribution of lucerne above-ground biomass across New Zealand lands considering contrasting growth conditions (rain-fed or irrigated for different soils types) and two simulation methods of different complexity (process- and GIS-based approaches). This aimed to assess yield-estimate spatial patterns and sensitivity to model selection for a wide range of combinations of water supply (i.e. irrigation and soil water storage) across New Zealand climate zones. For example, highly suitable areas for lucerne cultivation, were estimated in ∼21 thousand km2 when considering the exclusion of steep slopes, poor soil drainage and excess annual rainfall. The two crop-yield models were applied in response to 30 years of daily historical (1971–2000) weather data downscaled at 5 km resolution on suitable areas. Simulated average lucerne yields ranged from ∼4.5–28 t dry matter/ha per year. Simulations showed a distinct spatial pattern of yield decline from north to south, mainly in response to decreasing temperatures. Temporally, water limited yields were up to 4-fold more variable than under irrigation, depending on the degree of drought stress across different years. Results also unveiled systematic spatial patterns of model uncertainty quantified as yield sensitivity to model selection. For instance, simulated yields were most sensitive to model selection (6–31% of total variability, Ti) within high abiotic-stress environments (e.g. low temperature and limited water supply). Overall, soil type selection accounted for most of yield variability (58–78% Ti), being particularly important in warmer environments with variable seasonal rainfall regimes (e.g. northern regions). As expected, water supply (i.e. rain-fed or irrigated systems) was relatively more impactful on yield (8–20% Ti) for limited rainfall areas, where crops are most drought prone (e.g. east coast and central southern regions). Long-term regional scale comparisons of annual lucerne yield, between 30-year simulated distributions and point-based observations from the AgYields database, helped identify hotspots of yield overestimation. Such insights are useful to guide future research on high yield gap areas (e.g. southern colder and drier locations) and highlight key areas for model improvement (e.g. representation of multiple biotic stresses). Overall, our results provide a first gridded-model assessment of lucerne suitability and yield at national scale and quantify the share of variability explained by key climatic, management and methodological components in spatial analysis studies. These insights can inform future modelling efforts and support agricultural planning that considers the expansion of lucerne and other perennial legumes.

Grapevine Yield Big-data for Soil and Climate Zoning. A case study in Languedoc-Roussillon, France

New winegrower and resource datasets appear to be a great opportunity to understand which are the environmental factors involved in grapevine yield spatially. Such analysis can help regional label managers and winegrowers for the conception of local adaptation strategies to climate change, reducing yield gaps. In the present study, we aggregated yield a big dataset obtained from Pays d’Oc winegrowers (n = 96677) between 2010 and 2018 at the municipality level (n = 606), located in the Languedoc-Roussillon region, in the South of France. We used a backward stepwise model selection process using linear mixed-effect models to discriminate and select significant indicators capable of estimating grapevine yield at the municipality level, these include: Soil Available Water Capacity (SAWC), soil pH, Huglin Index, the Climate Dryness Index, the number of Very Hot Days and Days of Frost. We then determined spatial zones by creating clusters of municipalities with similar soil and climate characteristics. The seven zones presented two marked yield levels. Yet, all zones had municipalities with both high yield and high yield gaps. On each zone, grapevine yield was found to be driven by a combination of climate and soil factors, rather than just by a single environmental factor. Environmental factors at this scale largely explained yield variability across the municipalities, but they were not performant in terms of annual yield prediction. Further research is required on the interactions between environmental factors, plant material and farming practices.

Modelling and mapping soil nutrient depletion in humid highlands of East Africa using ensemble machine learning: A case study from Rwanda

Soil nutrient depletion is one of the major causes of high yield gaps and nutrient deficiencies in East Africa highlands, including Rwanda. This research sought to determine the current soil nutrient balance and its spatial variation in 10 Rwandan agro-ecological zones. Soil nitrogen (N), phosphorus (P) and potassium (K) depletion in croplands were calculated using data from 455 field trials of the Optimizing Fertilizer Recommendations in Africa (OFRA) project in Rwanda. Calculated soil nutrient balances (NPK) and 15 environmental covariates were used to calibrate soil nutrient depletion models using ensemble machine learning (EML) and 10-fold cross-validation. In the 2019–2020 growing season, annual N and K depletions were 33.6 kg N ha−1 yr−1 and 71.0 kg K ha−1 yr−1, with a positive P balance of 2.30 kg P ha−1 yr−1. High soil nutrient uptake and high soil nutrient loss due to erosion and leaching were two main causes of NPK depletion. Spatial variations of NPK balance were influenced by soil nutrient stocks, soil erosion, elevation, rainfall, soil texture, and soil bulk density. The 10-fold cross-validation showed that coefficients of determination (R2) of NPK models were 62%, 58%, and 58%, respectively. Compared to single models, ensemble machine learning improved NPK model accuracy up to 5%. Our research revealed that soil nutrient depletion was highest in the northwest and lowest in the southeast of the study area. We conclude that increasing soil nutrient inputs without reducing soil nutrient loss due to soil degradation will not decrease soil nutrient depletion in Rwanda and ensemble machine learning outperforms single models in predicting soil nutrient balance. Thesolutiontoreducehighsoilnutrientdepletionin all agro-ecological zones of Rwanda would be to prioritize soil and water conservation measures and increase soil nutrient inputs.

Synergistic Influence of Sulphur and Boron Fertilization on Enhancing the Productivity of Rapeseed (Brassica napus L.) and Nutrient Status in Subtropical Acidic Soil of Assam, India

ABSTRACT Rapeseed has an immense requirement for S and B, largely for the biosynthesis of glucosinolates and S amino acids. The present investigation was conducted for three consecutive rabi seasons of the year 2014–17 in rapeseed (cv.TS-38) to assess the impact of S and B fertilization on crop yield, soil chemical properties and nutrient status. Results of three years of investigations indicated that among the various soil chemical properties, the combined appliance of S and B level of S30B1.5 (30 kg S ha−1 + 1.5 kg B ha−1) significantly augmented the SOC, while soil pH, Fe2O3 and Al2O3 content in soil were found to be non-affected significantly. Interaction effect between S and B significantly affected available primary nutrients as fertilization with S30B1.5 registered maximum available N (298.7 kg ha−1), P (31.0 kg ha−1) and K (126.2 kg ha−1), respectively. Application of the same levels of S30B1.5 enhanced the status of exchangeable Ca and Mg, available S and B up to 0.90 cmol(p+) kg−1, 0.50 cmol(p+) kg−1, 13.67 mg kg−1 and 0.65 mg kg−1, respectively. The NUE in soil were found to improve on scaling both the levels of S and B. Yield attributing characters were not significantly affected by graded levels of S and B, however, there was a significant improvement in seed yield, stover yield and biological yield of rapeseed. Yield gap analysis exhibited that the combined application of S30B1.0 resulted in the lowest yield gap of 275 kg ha−1 while the control plot recorded the highest yield gap of 647 kg ha−1. Correlation study indicated the existence of a highly significant correlation among most of the soil parameters under investigation. Path analysis revealed that available P was the most dominant soil nutrient implicated in improving the BYR. The inclusive results indicated that higher levels of both S and B could improve the soil fertility status and yield of rapeseed.

Global cropland could be almost halved: Assessment of land saving potentials under different strategies and implications for agricultural markets.

The pressure on land resources continuously increases not only with the rising demand for agricultural commodities, but also with the growing need for action on global challenges, such as biodiversity loss or climate change, where land plays a crucial role. Land saving as a strategy, where agricultural productivity is increased to allow a reduction of required cropland while sustaining production volumes and meeting demand, could address this trade-off. With our interdisciplinary model-based study, we globally assess regional potentials of land saving and analyze resulting effects on agricultural production, prices and trade. Thereby, different land saving strategies are investigated that (1) minimize required cropland (2) minimize spatial marginalization induced by land saving and (3) maximize the attainable profit. We find that current cropland requirements could be reduced between 37% and 48%, depending on the applied land saving strategy. The generally more efficient use of land would cause crop prices to fall in all regions, but also trigger an increase in global agricultural production of 2.8%. While largest land saving potentials occur in regions with high yield gaps, the impacts on prices and production are strongest in highly populated regions with already high pressure on land. Global crop prices and trade affect regional impacts of land saving on agricultural markets and can displace effects to spatially distant regions. Our results point out the importance of investigating the potentials and effects of land saving in the context of global markets within an integrative, global framework. The resulting land saving potentials can moreover reframe debates on global potentials for afforestation and carbon sequestration, as well as on how to reconcile agricultural production and biodiversity conservation and thus contribute to approaching central goals of the 21st century, addressed for example in the Sustainable Development Goals, the Paris Agreement or the post-2020 global biodiversity framework.

Mississippi state and county level yield gap in corn production

AbstractContinuous corn (Zea mays L.) yield increases are required to promote economic development and support a larger population. Reducing the existing yield gaps is a potential strategy to accomplish this goal. The objective of this study was to evaluate yield trends, and gaps at different production levels in Mississippi using data from 2012 to 2021. Production levels considered were Mississippi yield contest (Yc), Mississippi State University hybrid testing trials under irrigation (Yp) and dryland (Yw), and actual yield (Ya) from USDA National Agricultural Statistics Service. Since 2012, Yc, Yp, and Ya are stagnant, and Yw has a nonsignificant positive trend. Averaged over 10 yr, a yield gap of 5.6 Mg ha−1 between Yc and Ya, 4.1 Mg ha−1 between Yp and Ya, and 2.0 Mg ha−1 between Yw and Ya were noted at state level. Existing yield gap underlines current production limitations and necessitates adoption of improved agronomic practices.Core Ideas In the last 10 yr, contest yield, potential yield, and actual yield in Mississippi have been stagnant. State level yield gap ranges between 2.0 to 5.6 Mg ha‐1 at different levels. Washington County showed the lowest (25.9%) and Lee County (48.8%) the highest yield gap in Mississippi.

Empirical Analysis of the Factors that Affecting Maize Production of Farmers among Smallholders: The Case of Eastern Oromia, Ethiopia

In Ethiopia, maize is the second largest in production areas and first in its productivity but there are high yield gaps between the actual yield currently producing and the potential yield. Therefore, this study was aimed to identify factors that affecting maize production of smallholder farmers at the farm level in the Meta district in the east Hararge zone, Oromia, Ethiopia. A two-stage random sampling technique was employed and a total of 200 smallholder farmers were randomly and proportionally selected to collect primary data. Multiple linear regression models were used to analysis factors that affect maize production among smallholder farmers. The result showed that the production of maize was influenced by several factors. The coefficient provided that as the farmers obtained 1 dollar from non-farm activity, the maize production of farmers increased by 293.2 kg, keeping other factors constant. Thus, the farmers who had money from non-farm sources used as additional income to gain agricultural inputs for maize production and thus generate more maize quantity. The result was pointed out that the size of the cultivated areas of land had a positive influence on the quantity of maize production of farmers. The coefficient entailed that as the size of the cultivated areas of land increased by one hectare, the farmer‘s quantity of maize production increased by 140.4 kg by keeping other factors constant. The result was also indicated that other factors being constant, the maize crop production of smallholder farmers of Meta district was decreased by 4 kg as Development Agent‘s (DA‘s) office distance increased by one minute. The possible explanation was that extension services were a critical source of information on agronomic practices. Therefore, policy makers should encourage the current maize production and supplying improved seed and chemical fertilizer which support to improve smallholder farm households‘ welfare by increasing their sources of income.

Abstract 255: National Institutes of Health Research Funding of the Top Science Gaps Recognized in the 2015 American Heart Association Emergency Cardiac Care Guidelines

Objective: A descriptive analysis of NIH funding of the top science gaps recognized in the 2015 AHA Emergency Cardiac Care cardiac arrest (CA) guidelines over a five-year period. Methods: A search within NIH RePORTER for the period of 2015 to 2019 was performed using the following terms: “cardiac arrest” or “cardiopulmonary resuscitation” or “heart arrest” or “circulatory arrest” or “pulseless electrical activity” or “ventricular fibrillation” or “resuscitation”. Grants were identified as CA research (yes/no) using predefined, published criteria. NIH funded CA abstracts were individually reviewed and categorized using the previously recognized ten most urgent science gaps in the 2015 AHA ECC CA guidelines published by Panchal et al. The data were analyzed descriptively. Results: The search yielded 1,518 NIH-funded grants over the study period, of which 172 (11.3%) were classified as individual CA grants. A total of 42 (24.4%) did not address a top 10 scientific gap. The remaining 130 grants addressed the following scientific gaps: optimization of post-CA care (78 grants, 45.3%), prediction of patients at risk of CA (12, 7%), developing tools for early neuroprognostication (7, 4.1%), hemodynamic monitoring/goal directed resuscitation (4, 2.3%), optimizing educational strategies for providers (4, 2.3%), optimal airway strategies (2, 1.2%), and understanding why bystanders fail to respond (1, 0.6%). Previously existing scientific networks or data centers accounted for 19 (11%) grants and 3 (1.7%) grants addressed both optimizing post-CA care and early neuroprognostication gaps. Recognized scientific gaps in dispatch-directed CPR, individualized resuscitation strategies, and novel technology for out-of-hospital CA identification and response did not receive specifically directed NIH grant funding. Conclusion: Additional research funding targeting critical knowledge gaps in the 2015 cardiac arrest guidelines is needed promote broader evidence-based guideline development. Current NIH funding is concentrated in a few areas leaving disparity among recognized high-yield scientific gaps in CA care.

Rice Yield Gaps in Smallholder Systems of the Kilombero Floodplain in Tanzania

To meet the growing rice demand in Africa, gaps between actual and attainable yields have to be reduced. In Tanzania, this particularly concerns smallholder rain-fed production systems in the floodplains. After quantifying the existing yield gaps, key contributing factors need to be analyzed to improve site-specific management. Field experiments were conducted for three years and in three pedo-hydrological environments (fringe, middle, and center positions) of the Kilombero floodplain to evaluate: (1) The grain yield under farmers’ management (actual yield), (2) yield with the best-recommended management (attainable yield), and (3) the non-limited yield simulated by the APSIM model (potential yield). In the field, we additionally assessed incremental effects of (1) field bunding and soil levelling, (2 and 3) additionally applying of 60 kg N ha−1, as urea or as farmyard manure (FYM), and (4 and 5) incorporating in-situ-grown leguminous green manures. Attainable yields were determined with mineral N application at 120 kg ha−1, additional PK fertilizer and supplemental irrigation. On average across years and positions, the potential, the attainable, and farmers’ actual yields were 11.5, 8.5, and 2.8 t ha−1 indicating a high total yield gap. About 16–38%, 11–20%, and 28–42% of this gap could be attributed to non-controllable yield-reducing (i.e., pest and diseases), yield-limiting (i.e., water and nutrient deficiencies), and yield-defining factors (i.e., poor soil and crop management), respectively. Results indicate a closure of the exploitable yield gap (differences between attainable and farmers’ actual yields) by up to 6.5 t ha−1 (nearly 60% of the potential yield). This exploitable yield gap was larger in 2016 than in 2017. Also, the gap was larger in the water-limited fringe and middle than in the frequently submerged center positions. Simple field bunds combined with land levelling could close 15–35% of the exploitable yield gap, depending on field positions and year. FYM or green manures were less effective than mineral N; however, in 2017 and in the wetter middle and center positions, they reduced the yield gap by >50%. We conclude that yield gaps in rainfed rice in Kilombero floodplain are large, but that a site- and system-specific adaptation of crop management can close much of the exploitable yield gap and increase grain yields by 0.7–4.8 t ha−1. Similar benefits may be obtained in other hydrologically variable floodplain environments of the region and beyond.

Does a trade-off between yield and efficiency reduce water and nitrogen inputs of winter wheat in the North China Plain?

Increasing both grain yield and water use efficiency (WUE)/nitrogen partial factor productivity (NPFP) of winter wheat is crucial to realize the sustainable development of agricultural production in the North China Plain (NCP). This study was conducted to test the hypothesis that a trade-off between yield and efficiency could reduce water and nitrogen inputs of winter wheat in the NCP. Wheat yield, WUE and NPFP under three production levels, i.e. the potential, high-yield and high-efficiency (HH), and on-farm, and their gaps were investigated with APSIM-Wheat model. The results showed that simulated potential yields were close to observed potential yields with RMSE of 1150 kg ha−1 (NRMSE of 12 %) and simulated on-farm yields followed with observed yields with RMSE of 576 kg ha−1 (NRMSE of 8.8 %). Simulated yield gap between the potential and on-farm yields was 2565 kg ha−1 averaged across the NCP from 1981 to 2015 with the highest yield gap in the central part of NCP and the eastern Shandong province, and the corresponding gaps of WUE and NPFP were 0.45 kg m−3 and 10.9 kg N kg−1 with a large spatial difference. To narrow the gaps, about 33 mm additional irrigation and 5 kg N ha−1 reductions from the current irrigation (242 mm) and N fertilizer (267 kg N ha-1) application amounts were needed across the NCP. WUE and NPFP could be increased by 29 % and 43 % from the on-farm to the potential levels. However, if on-farm yield only attained 80 % of the potential, WUE and NPFP could be increased by 0.96 kg m−3 (60 %) and 19.3 kg kg−1 (77 %) across the NCP. Irrigation and nitrogen fertilization amounts could be reduced by averaged 127 mm and 89 kg ha−1 from current averaged irrigation and nitrogen fertilization amounts across the NCP. Especially, the irrigation schedule at on-farm level should be adjusted from three or four irrigations at (sowing), overwintering, jointing and flowering to two irrigations at jointing and flowering across the NCP. Our results suggested an explicit potential for wheat yield and water-nitrogen efficiency win-win by optimizing water and nitrogen management in the NCP.

Socio-Economic Appraisal of Farming Households in Marginal Areas in Botolan, Zambales, Philippines

Farm households in four barangays in Botolan, Zambales were studied to make a socio-economic appraisal of their condition after the eruption of Mt. Pinatubo in 1991 and the massive flooding in 2009 that further marginalized their farms. A self-construct questionnaire was used for 150 farming households. Socio-economic data, farm management practices, production, and income per household were described, pooled, and analyzed descriptively. As of 2018, rice farming was the main source of household income despite the land being less suitable for rice and production area reduced. There was low productivity and a high yield gap compared with the province’s and the region’s yield levels. There was high input cost in rice farming due to various factors including the marginal condition of the farms. There was low income from rice farming during both seasons, but the yield was much lower during the wet season due to lower yield.

Yield gap in cowpea plants as function of water déficits during reproductive stage

ABSTRACT The cowpea bean presents low productivity in the Pará state, Brazil, due to low soil fertility and climatic adversity, mainly water deficiency. The aim of this study was to evaluate the yield gap of cowpea bean in northeast of Para state in response to water deficit during its reproductive phase. The experiment was carried out in Castanhal, PA, Brazil, during 2015 and 2016. A randomized block design with six repetitions and four treatments was used; where T1 consisted of 100% replacement of the crop evapotranspiration (ETc), T2 to 50%, T3 to 25% and T4 without irrigation, in the reproductive phase. The yield was determined at R9 stage. The simulations with the SARRAZON model were carried out with different sowing dates. The total deficiencies in the reproductive phase were spatialized considering the 30 locations in order to assess the temporal and spatial seasonality of water availability and the sowing period in the study region. The cowpea bean was sensitive to soil water availability with considerable reductions in productivity due to the increase in water deficit compared to the treatment T1 (100% ETc). When water deficits reached more than 47 mm, there were yield gaps over 20%. According to the spatial variability of simulated water deficiency, the sowing of cowpea bean in regions located above 2° latitude may extend until June 20 without showing high yield gaps.

Assessing alternative crop establishment methods with a sustainability lens in rice production systems of Eastern India.

Sustainability of rice production systems is a prime concern for Asia to maintain food security and to support economic growth. This gain in productivity not only depends on agricultural inputs but also depends on social and environmental factors. To address these emerging issues, new resource- and capital-efficient and profitable technologies have been introduced. The conventional method of rice production (puddling and manual transplanting, PTR) is considered as highly input intensive. As an alternative, dry direct seeded rice (DSR) using seed drill has been promoted to save labor and production costs compared with PTR. Similarly, machine transplanted rice (MTR) has been also considered and promoted in many rice growing countries of South and East Asia. Economic, environmental, and social performances of DSR and MTR (alternative rice establishment technologies) were compared to the PTR using Sustainable Rice Platform (SRP) defined 12 Performance Indicators (PIs) (version 1.0) as a gauge to measure their sustainability. For that, a household survey was conducted on 652 households in Odisha India during 2016. The gaps, i.e., the target to achieve better sustainability, were computed for most of the indicators from the difference between top 10th percentile and the population mean value of the indicator. The results indicated a yield gap of 1.35 t ha−1, a profit gap of $273 ha−1, labor productivity gap of 21 kg day−1, nitrogen (N) use efficiency gap of 22 kg grain kg−1 N, phosphorus (P) use efficiency gap of 105 kg grain kg−1 P, and water productivity gap of 0.00010 kg grain L−1 water in rice production systems in Odisha. Among the compared technologies, MTR results in the highest yield, profit, labor productivity, nitrogen-, phosphorus-use efficiency, and water productivity (at par), and is positive for children’s welfare and the overall energy productivity, indicating better sustainability and has the potential to replace PTR. Direct seeded rice has the highest yield gap (1.57 t ha−1; 38%) but has the lowest production cost (can reduce the cost of production by $130 ha−1), and the highest greenhouse gas (GHG) reduction potential. SRP PIs are capable for assessing the sustainability of rice establishment technologies except for a few indicators, for example food safety and workers health and safety, which are more applicable to watershed and household level indicators, respectively. The SRP PIs provide scientific evidence and practical impetus for the selection and promotion of sustainable rice production technologies.