Yield Gap Research Articles

Bibliometric Network Analysis of Crop Yield Gap Research over the Past Three Decades

Achieving global food security requires an understanding of the current status and the future trends in the yield gap for cropping systems worldwide. The aim of this study was to scientifically understand the existing yield gap research, recognize the knowledge base and influential articles, and uncover key research themes and how these have evolved over the past three decades. Bibliometric methods were used to analyze articles related to the yield gap available in the largest scientific database, the Web of Science. A total of 6049 relevant articles published from 1993 to 2023 were numerically analyzed for patterns, trends, and clusters. The findings identified a few primary authors of widely cited publications. Geographically, the United States and China were the two major contributors to the publication pool, with articles from China mostly affiliated with the Chinese Academy of Sciences and China Agricultural University, while the United States had a more scattered distribution of affiliated institutions. The research on yield gaps primarily focused on biological factors, such as the effects of crop varieties, agronomic management, climate change, and soil conditions, with a limited exploration of social and economic factors. Within the auspices of the current food issues worldwide, this study provides a thorough view of the progress and key topics in crop yield gap research, contributing to the existing body of knowledge and providing guidance for researchers, policymakers, and stakeholders involved in agricultural productivity enhancement and sustainable food production. Amid the increasing trend in hunger worldwide over the past decade, we thus concluded that, by establishing appropriate benchmarks, re-prioritizing research needs, and focusing on transforming natural resources rather than inputs, the crop yield gap approach can be useful in terms of the clear inclusion of local contexts and socioeconomic constraints.

Impact of Front Line Demonstrations in Improving Rice Productivity and Profitability in Jaunpur District of Uttar Pradesh, India

A study was carried out during Kharif, 2019 to assess the impact of Frontline Demonstrations (FLDs) on productivity and profitability of rice crop in Jaunpur district of Uttar Pradesh. The FLDs were conducted by the ICAR-Indian Agricultural Research Institute, Regional Station Pusa, Samastipur, Bihar, under the IARI-Outreach Programme to know the yield gap, technology gap, extension gap, economic return, extent of farmer’s satisfaction, and constraints faced by the farmers, especially paddy growers. The critical inputs were identified in existing production technology through personal interaction, group meetings, and discussions with farmers and scientists. Improved variety, soil testing, seed treatment, integrated nutrient management, weed management, and pest and disease management are among the improved technologies. The result showed that switching from traditional farming methods to more advanced production technologies can result in yields of 30.00 percent and net returns of 27.00 percent. The extension gap of 1.20 t/ha, technological gap (0.55 t/ha), and technology index (9.57%) were registered for the Pusa Sugandha-5 variety. An additional returns of ₹16884.33/ha was obtained with an additional investment of ₹8395.67/ha, coupled with scientific monitoring of demonstrations and the use of rice varieties during investigations, which also influenced the economic returns per unit area. The constraint that was found to be the most difficult to overcome was the lack of improved, high-yielding rice varieties. In order to increase their yield and increase the production and productivity of rice in Uttar Pradesh, farmers in the area are advised to adopt new rice varieties as well as a recommended improved package of practices and technologies.

Assessing chickpea attainable yield and closing the yield gaps caused by agronomic and genetic factors

Assessing chickpea attainable yield and closing the yield gaps caused by agronomic and genetic factors

Suitability mapping and management monitoring in Castilian organic and conventional wheat fields with Sentinel-2 and spatial data

The Mediterranean region is a climate change hotspot due to projected precipitation decreases, soil erosion, and rising temperatures in the coming decades. In such a context, wheat productivity is expected to decrease; thus, all available croplands will need to be farmed to meet food demands. It is therefore crucial to have adequate management to help balance wheat production and environmental protection in specific target environments. With this aim, we present a study in Castile and Leon (Spain) in which we assess conventional and certified organic wheat grain yield and quality. Moreover, we spatially define wheat cultivation suitability categories and monitor crop rotation practices. For wheat suitability mapping, a fuzzy interference system was used to standardize topographic (height and slope), edaphic (pH, soil erosion, organic matter, and texture), and climatic (rainfall and temperature) variables and create marginal, suitable, and very suitable wheat cultivation suitability categories. We calculated the area of wheat suitability categories with confidence intervals and discussed factors affecting productivity. Additionally, we assessed the performance of certified organic and conventionally managed fields with organic and chemical fertilization. We also examined crop rotations using Sentinel-2 data over two seasons (2020−21). Certified organic management yielded 50% less than conventional management in similar environments while maintaining grain quality. Besides management, the main causes of the yield gap are the growing environment and variety. In conventional wheat management, organic fertilization achieves comparable yields to chemical fertilization. Crop rotation practices are uncommon, and over 50% of fields rotate wheat-to-barley or wheat-to-wheat, indicating poor soil management. The region has 25% of cropland classified as marginal wheat croplands (163,503 ± 33,796 ha) producing <2500 kg/ha. Wheat organic agriculture has decreased yield gaps in marginal croplands compared to more productive areas. By farming organic wheat in marginal croplands, the best croplands might be used for more productive farming.

Landscape-based nutrient application in wheat and teff mixed farming systems of Ethiopia: farmer and extension agent demand driven approach

IntroductionAdapting fertilizer use is crucial if smallholder agroecosystems are to attain the sustainable development goals of zero hunger and agroecosystem resilience. Poor soil health and nutrient variability characterize the smallholder farming systems. However, the current research at the field scale does not account for nutrient variability across landscape positions, posing significant challenges for targeted nutrient management interventions. The purpose of this research was to create a demand-driven and co-development approach for diagnosing farmer nutrient management practices and determining landscape-specific (hillslope, mid-slope, and foot slope) fertilizer applications for teff and wheat.MethodA landscape segmentation approach was aimed to address gaps in farm-scale nutrient management research as well as the limitations of blanket recommendations to meet local nutrient requirements. This approach incorporates the concept of interconnected socio-technical systems as well as the concepts and procedures of co-development. A smart mobile app was used by extension agents to generate crop-specific decision rules at the landscape scale and forward the specific fertilizer applications to target farmers through SMS messages or print formats.Results and discussionThe findings reveal that farmers apply more fertilizer to hillslopes and less to mid- and foot slopes. However, landscape-specific fertilizer application guided by crop-specific decision rules via mobile applications resulted in much higher yield improvements, 23% and 56% at foot slopes and 21% and 6.5% at mid slopes for wheat and teff, respectively. The optimized net benefit per hectare increase over the current extension recommendation was $176 and $333 at foot slopes and $159 and $64 at mid slopes for wheat and teff (average of $90 and $107 for wheat and teff), respectively. The results of the net benefit-to-cost ratio (BCR) demonstrated that applying landscape-targeted fertilizer resulted in an optimum return on investment ($10.0 net profit per $1.0 investment) while also enhancing nutrient use efficiency across the three landscape positions. Farmers are now cognizant of the need to reduce fertilizer rates on hillslopes while increasing them on parcels at mid- and foot-slope landscapes, which have higher responses and profits. As a result, applying digital advisory to optimize landscape-targeted fertilizer management gives agronomic, economic, and environmental benefits. The outcomes results of the innovation also contribute to overcoming site-specific yield gaps and low nutrient use efficiency, they have the potential to be scaled if complementing innovations and scaling factors are integrated.

Characterising Productivity Factors Affecting Maize (Zea mays) Production in a Smallholder Crop-Livestock System

Socio-economic factors can influence decisions and the intensity of management practices, which when appropriately considered could bridge yield gaps. The study aimed to investigate factors affecting maize (Zea mays L.) production in a smallholder crop-livestock system. Social and management analyses were performed to ascertain the factors influencing maize productivity using interviews and questionnaires. The study was conducted in two main maize-producing regions of Eswatini, the Highveld at Mankayane and Middleveld at Luve. Additionally, on-farm trials were established for two cropping seasons to evaluate maize response to three fertiliser regimes: cattle manure only, cattle manure plus inorganic fertiliser, and inorganic fertiliser only and lastly to determine the most economic fertiliser regime. Each fertiliser regime was replicated six times. Weed biomass and maize yield were collected from a 5 m × 1 m quadrat. Moreover, economic analysis for each fertiliser regime was performed using partial budgets comprising fertiliser and weed management costs. The social and management analyses showed that maize yield was strongly associated with household size (p < 0.05), land area cultivated (p < 0.05) and herbicide application timing (p < 0.05) indicating the effect of these factors on yield. On-farm trials revealed that the inorganic fertiliser only regime resulted in a significantly (p < 0.05) higher maize yield compared to manure only and manure plus inorganic fertiliser regimes in both study areas. Weed biomass was significantly (p < 0.05) lower in the inorganic fertiliser only regime at Mankayane compared to the manure only and manure plus inorganic fertiliser at both localities. The economic analysis showed that the manure only fertiliser regime had low costs that vary and high net benefits indicating that manure has the potential to improve soil conditions, reduce environmental impacts, and increase profits.

Impact of Cluster front-line Demonstrations on Productivity and Economics of Groundnut in Southern Transition Agro Climatic Zone (Zone-7) of Hassan District, Karnataka, India

Groundnut is a important commercial legume cum oilseed crop growing in Hassan district of Karnataka and there is a notable yield gaps found between the farmers and demonstration plots due to non adoption of improved agronomic technological practices and use of local varieties. Integrated crop management (ICM) practices in groundnut under cluster front-line demonstration were conducted by ICAR-Krishi Vigyan Kendra, Hassan during Summer seasons of 2018-19 to 2022with active participation of 250 groundnut growers with a objective of practicing improved agronomic practices over a 100 ha area in 5 consecutive years.The highest groundnut pod yield was achieved in demonstration plots with an mean of 1842.8kg/ha as compared to farmers practices with an mean of 1254.80kg/ha; which was 22.24 per cent higher yield as compared to farmers practices. The demonstration plots average mean of extension gap, technology gap and technology index were calculated as 281.20 kg/ha, 564 kg/ha, 26.75 per cent, respectively. The higher mean net returns of 62592.60/ha with B:C ratio of 2.35 was exhibited in improved agronomic practices demonstrated plot as compared to local practices (Rs.43897.60/ha). So it’s concluded that improved agronomic technological practices have high potential to increase the groundnut productivity through cluster front-line demonstration.

Priorities for narrowing the yield gap and increasing farming systems resilience in the Fiji sugar industry

Sugarcane (Saccharum officinarum L.) is the single most important agricultural industry in Fiji and occupies half of the nation's cropped area while supporting 25% of the labour force. However, the industry is facing comprehensive challenges across the supply chain, underlain by declining productivity and changing climate. The purposes of this study were to: (1) use model simulation to determine the potential of conservation agriculture (CA) practices to narrow yield gaps in sugarcane production systems under historical and projected climates in a case study; (2) identify and rank candidate practices that would contribute to narrowing such yield gaps; and (3) identify the limitations of the modelling approach and make recommendations for improving it. We simulated nine scenarios of CA practices with potential to reduce the estimated yield gap (55 ​Mg ​ha-1) by increasing nitrogen (N) fertiliser rates (30 ​Mg ​ha−1), liming (25 ​Mg ​ha−1), improved weed control (5–9 ​Mg ​ha−1), replacing uncropped fallow with legume crops (2–3 ​Mg ​ha−1), crop cycle duration (0 ​Mg ​ha−1), and retaining crop residues (−2 ​Mg ​ha−1). The yield benefit of CA practices was similar under projected climates that were warmer and wetter or drier, or hotter and wetter. For a projected climate that was hotter and drier, the greatest yield benefit was obtained from liming, weed control, and retaining crop residues. The study was limited by the availability of daily weather data, and it would be complemented by additional studies incorporating more local crops, evaluation of barriers to mechanisation needed to implement new practices, and economic assessment of scenarios.

Assessing the yield difference of double-cropping rice in South China driven by radiation use efficiency

Double-cropping rice in South China continues to break the total yield record, but the yield potential of single-cropping rice is not being realized. Radiation use efficiency (RUE) has been singled out as an important determinant of grain yield in many cereal species. However, there is no information on whether the yield gaps in double-cropping rice involve differences in RUE. Field experiments were performed over two years to evaluate the effects of intercepted radiation (IP) and RUE on the above-ground biomass production, crop growth rate (CGR), and harvest index (HI), in four representative rice varieties, i.e., Xiangyaxiangzhan (XYXZ), Meixiangzhan 2 (MXZ2), Nanjingxiangzhan (NJXZ), and Ruanhuayoujinsi (RHYJS), during the early and late seasons of rice cultivation in South China. The results revealed that grain yield in the early season was 8.2% higher than in the late season. The yield advantage in the early season was primarily due to higher spikelets per panicle and above-ground biomass resulting from a higher RUE. The spikelets per panicle in the early season were 6.5, 8.3, 6.9, and 8.5% higher in XYXZ, MXZ2, NJXZ, and RHYJS, respectively, than in the late season. The higher early season grain yield was more closely related to RUE in the middle tillering stage (R2=0.34), panicle initiation (R2=0.16), and maturation stage (R2=0.28), and the intercepted photosynthetically active radiation (IPAR) in the maturation stage (R2=0.28), while the late season grain yield was more dependent on IPAR in the middle tillering stage (R2=0.31) and IPAR at panicle initiation (R2=0.23). The results of this study conclusively show that higher RUE contributes to the yield progress of early season rice, while the yield improvement of late season rice is attributed to higher radiation during the early reproductive stage. Rationally allocating the RUE of double-cropping rice with high RUE varieties or adjustments of the sowing period merits further study.

The Effect of One-Year Seed Spaceflight Storage on Yield, Biochemical and Mineral Characteristics of Mature Leafy Vegetables Belonging to Brassicaceae, Apiaceae and Asteraceae Families

Spaceflight is known to produce genetic changes in seeds, usually accelerating aging, though species and varietal differences have been poorly investigated. Comparisons were carried out in terms of yield, biochemical characteristics and mineral composition between mature plants grown from seeds subjected to a one-year spaceflight, belonging to Brassicaceae (Brassica juncea and Eruca sativa), Apiaceae (Anethus graveolens, and Coriandrum sativum), and Asteraceae (Lactuca sativa, six cultivars) families, and non-treated control. Among the studied species, only Brassica juncea and Eruca sativa demonstrated a growth stimulation effect caused by seed spaceflight, while significant growth inhibition was recorded in Apiaceae plants and three cultivars of Lactuca sativa L. No differences in the total antioxidant activity (AOA), polyphenol and ascorbic acid content were detected between ‘space-treated’ and control plants. On the contrary, significant decrease in proline accumulation and increase in malonic dialdehyde and photosynthetic pigments levels were shown by Brassicaceae species. The effect of long-term seed spaceflight on the mineral composition of mature plants was reflected in the inhibition of accumulation of all 24 elements analyzed in Apiaceae plants, except for Se, whose concentration was higher in all ‘space-treated’ plants compared to the control. Spaceflight seed storage increased V levels in lettuce and decreased Na accumulation in all the investigated species. The results reveal species-dependent changes in the accumulation of macro-, micro- and toxic elements in Apiaceae, Brassicacea, and Asteraceae representatives due to spaceflight seed storage. The detected differences in plant elemental composition between ‘space’ treatment and control partly explain the corresponding yield gap and suggest a relationship between mineral status and adaptability. The highest beneficial effect of spaceflight seed storage on yield was recorded in Eruca sativa cultivar, Rusalochka.

Use of interpretive machine learning and a crop model to investigate the impact of environment and management on soybean yield gap

Context Management and environmental conditions are the main factors influencing yield of soybean (Glycine max (L.) Merr.). Despite an increase in average soybean yield in recent years in Iran, a considerable gap remains between actual yield and potential yield. Aims The objective of this study was to identify critical climate and management factors affecting soybean yield in Iran’s major soybean production area. Methods A combination of machine learning approaches (using gradient boosted decision trees, XGBoost) and the SSM-iCrop2 simulation model was used. Critical management factors affecting soybean yield were determined through interpretive machine learning using information collected from 268 soybean fields over a 5-year period. Potential yield and water-limited potential yield at six weather stations were estimated for 30 years via the SSM-iCrop2 simulation model. Water limitation was determined by considering the ratio of water-limited yield potential to potential yield, and heat stress status was quantified as the number of days with maximum temperature &gt;36°C during the soybean growing season. Key results The XGBoost models adequately described the observed changes in soybean yield. Root-mean-square error and Lin’s concordance correlation coefficient values of the calibrated model were 262 kg ha−1 and 0.96, respectively, which indicated that the predictor variables could describe most of the variation in soybean yield for the studied dataset. Conclusions We identified 15 climatic and management variables that affect soybean yield. A large part of the studied area is under high water stress and low heat stress. Implications Optimal planting date and improved irrigation management are the main options for reducing the yield gap in the study area.

On-farm water energy food carbon-footprint nexus index for quantitative assessment of integrated resources management for wheat farming in Egypt

To improve the farming efficiency, Egypt has been struggling to narrow the water, energy, and yield gaps owing to exacerbated water shortage. For quantitative diagnosis of farming performance, the paper presented an on-farm water, energy, food, and carbon-footprint (WEFC) nexus index made up of four equally pillars. The arithmetic average preserved the multi-centric approach and equal importance of the four pillars. The index was applied to test and rank 2,042 wheat-based farmer fields in Egypt representing diverse inputs, agronomic and irrigation practices, soil types, and agroecological conditions. The water metric was the ratio of saved water, difference between maximum water consumption recorded in the country and actual water consumption, to the maximum water consumption. Likewise, the energy metric was obtained. The food metric was the ratio of actual yield to maximum yield in the country. The carbon-footprint metric was the ratio of difference between maximum CO2 emission in the country and actual emission to the maximum emission. The index values showed a wide range from 18.69% to 87.33% with a high standard deviation emphasizing the diversity of farming practices, soil types, and agroecological conditions. The highest ten values were recorded in fields with sandy soils, relatively large area, drip irrigation, recommended seeding and fertilization rates, well drainage, weeds removal, and tillage. The drip irrigation system in 51 out of 52 fields had above average value. The lowest ten values were in fields with clay soils and flood irrigation, where 18.7% of 1,780 fields exceeded the above average value. Raised beds with furrow irrigation in 83.15% of 184 fields exceeded the above average value. Fertilization rates of nitrogen and phosphorus in 61% and 53% of fields respectively exceeded the recommended rates with no significant reflection on the food metric. The low index values in fields with flood irrigation were attributed to high water losses causing high water consumption, energy consumption, and CO2 emission. The index was a good indicative of input resources consumption and output production as it varied inversely with water and energy consumption and CO2 emission and proportionally with yield. Since the high-water consumption was the main entry point for low index values in fields with flood irrigation, changing the irrigation to drip system or revisiting the irrigation scheduling and the estimated applied irrigation water amount were recommended. The index can be utilized to quantify the effectiveness of both recommendations and further new site-specific interventions and to assess their impact at scale. The index also recommended land use consolidation where farmers retain ownership of their lands but with cooperative farming.

Genotype and agronomic management interaction to enhance wheat yield and water use efficiency in the Mediterranean rainfed environment of Morocco: I. Field data analysis

Durum wheat (Triticum turgidum subsp. durum), considered better drought tolerant, is the most cultivated wheat in Morocco and in the Middle East and North Africa (MENA) region. The region, including Morocco, predominantly has rainfed production systems, declining water supply, and increasing trends and effects of rainfall variability and climate extremes leading to poor crop yield and yield stability. The objectives of this study were to understand major factors determining wheat yield and water use efficiency (WUE); assess the interaction of genotype × environment × management on crop yield and field- and crop-water use efficiencies; and determine the water-limited yield gaps of genotypes under different agronomic management practices in the Mediterranean climate of Morocco. Four years (2015/16–2018/19) of on-station experiments investigating genotype (ten genotypes including seven advanced line and three commercial varieties), seeding time (17 November vs. 29 December), and water management (rainfed vs. supplementary irrigation), was conducted at Merchouch research station, Morocco. The results showed that durum wheat yield mostly varied due to year (rainfall) by 43%, followed by water management × year (23%), year × seeding time (15%), and genotype (7%), with the highest yield (7.15 t ha−1) observed in 2018 (wet year) and the lowest in 2019 (dry year). Across years, not only the rainfall amount but also its distribution during the crop growing season caused yield variability. In low-rainfall years, supplementary irrigation (28–166 mm) increased yield by 2.12–3.27 t ha−1 compared to rainfed conditions. The significant (p < 0.01) year × seeding time × genotype effect on grain yield and WUEs indicates that the response of genotype and seeding time varied with rainfall amount and distribution as the water-limited yield gap in rainfed conditions appeared to be more than 2 t ha−1. In both supplementary irrigated and rainfed systems, the machine learning model showed the effect of different climatic (rainfall and temperature) and management (seeding time, genotype, and irrigation) factors determining yield, yield attributes, and WUEs. The total rainfall remained the most important factor explaining variation in rainfed wheat yield followed by the temperature at flowering, mid- and early-season rainfall, and genotype in order of importance. Similarly, seasonal rainfall was the most important factor explaining variation in grain yield followed by early-season rainfall, days to flowering, temperature at flowering, irrigation amount, seeding time, and genotype in supplementary irrigated durum wheat. Our study clearly shows that yield is highly related to rainfall in rainfed drylands, and the selection of high WUE variety and crop management practices are the key to improving the resilience and sustainability of durum wheat in Morocco and similar production environments in the MENA region.

Improving Crop Health, Performance, and Quality in Organic Spring Wheat Production: The Need to Understand Interactions between Pedoclimatic Conditions, Variety, and Fertilization

Organic wheat production systems have lower yields compared with intensive conventional production and often do not achieve the grain protein content and quality thresholds set by millers and bakers. In contrast, organic production methods were reported to result in higher concentrations of nutritionally desirable micronutrients and lower concentrations of the toxic metal Cd in wheat grain and wholegrain flour. However, although N-availability and variety characteristics are known to affect both gain yields and bread-making quality, the exact reasons for the yield gap and differences in grain processing and nutritional quality between organic and conventional spring wheat production in the UK are poorly understood. The overall aim of this study was therefore to determine to what extent changes in variety choice and fertilization regimes may reduce the yield gap and improve processing quality without affecting nutritional quality in organic spring wheat production. To achieve this aim, we compared crop health, yield, grain processing, and nutritional quality parameters in spring wheat produced using (i) six contrasting spring wheat varieties grown with a standard fertilization regime and (ii) one variety widely used by organic farmers (Paragon) with nine different fertilization regimes in (iii) three UK sites/farms with contrasting pedoclimatic conditions. Significant differences in foliar disease severity, grain yield, and quality parameters were detected between six contrasting spring wheat varieties when grown under organic management regimes. Specifically, the varieties Paragon and Tybalt were identified as the best-performing varieties with respect to foliar disease resistance and grain yield under organic farming conditions and also produced high processing and nutritional quality across the three UK sites. However, the highest grain yields were obtained by Paragon at the Gilchester site and Tybalt at the Sheepdrove and Courtyard sites, while the highest protein contents were produced by Tybalt at the Gilchester site and Paragon at the Sheepdrove and Courtyard sites, which suggests that there is a need for site-specific wheat variety selection in the UK organic sector. Although organic fertilizer input type and level also affected wheat performance, differences between fertilization regimes were smaller than those observed between the five contrasting varieties, which suggests that improvements in spring wheat breeding/selection have a greater potential for increasing crop yield and quality in the organic sector compared with changes to fertilization practices. Overall, results suggest it is feasible to breed/select spring wheat varieties that combine high protein, vitamin E, and micronutrients with low toxic metal (Cd, Pb) concentrations when produced under organic farming conditions. These findings also support the hypothesis that differences in variety choice by organic and conventional farmers have contributed to the differences in nutritional quality between organic and conventional wheat products reported in previous studies.

Wheat Yield Estimation at High Spatial Resolution through the Assimilation of Sentinel-2 Data into a Crop Growth Model

Monitoring crop growth and estimating crop yield are essential for managing agricultural production, ensuring food security, and maintaining sustainable agricultural development. Combining the mechanistic framework of a crop growth model with remote sensing observations can provide a means of generating realistic and spatially detailed crop growth information that can facilitate accurate crop yield estimates at different scales. The main objective of this study was to develop a robust estimation methodology of within-field winter wheat yield at a high spatial resolution (20 m × 20 m) by combining a light use efficiency-based model and Sentinel-2 data. For this purpose, Sentinel-2 derived leaf area index (LAI) time series were assimilated into the Simple Algorithm for Yield Estimation (SAFY) model using an ensemble Kalman filter (EnKF). The study was conducted on rainfed winter wheat fields in southern Sweden. LAI was estimated using vegetation indices (VIs) derived from Sentinel-2 data with semi-empirical models. The enhanced two-band vegetation index (EVI2) was found to be a useful VI for LAI estimation, with a coefficient of determination (R2) and a root mean square error (RMSE) of 0.80 and 0.65 m2/m2, respectively. Our findings demonstrate that the assimilation of LAI derived from Sentinel-2 into the SAFY model using EnKF enhances the estimation of within-field spatial variability of winter wheat yield by 70% compared to the baseline simulation without the assimilation of remotely sensed data. Additionally, the assimilation of LAI improves the accuracy of winter wheat yield estimation by decreasing the RMSE by 53%. This study demonstrates an approach towards practical applications of freely accessible Sentinel-2 data and a crop growth model through data assimilation for fine-scale mapping of crop yield. Such information is critical for quantifying the yield gap at the field scale, and to aid the optimization of management practices to increase crop production.

Quantification of hormones and profiling of metabolites from vegetative to reproductive growth phase shift in Lagenaria siceraria (Molina) Standl

In the world of agricultural research, there has been a lot of emphasis on increasing insight into the decline of crop yield gap levels. Metabolomics is a relatively recent approach that aims to better understand the metabolic networks and is extensively being applied to agricultural research for its divergent growth and productivity by enhancing the behavior of plants under various stress. Lagenaria siceraria (Bottle gourd – Salad variety) has commonly been used because of its enormous nutritional, commercial, and medicinal benefits. The purpose of this investigation was to quantify the level of endogenous hormones and metabolites profiling at the vegetative and reproductive phase from various tissues of L. siceraria by liquid chromatography-tandem mass spectrometry (LC-MS/MS) and gas chromatography-mass spectrometry (GC–MS). The field-grown plant samples such as vegetative, male, and female flower-initiated parts including leaf, stem, tendril, and shoot apex were used for this study. The vegetative tissues had the highest level of trans zeatin and indole-3-acetic acid whereas indole-3-propanoic acid, trans zeatin, and gibberellic acid-3 were seen highest in the male flower-initiated tissues, and the level of IPA alone was found highest in the female flower-initiated tissues quantified by LC-MS/MS method. Additionally, N-Methyl-N-trimethylsilyl-trifluoroacetamide derivatized tissues showed the presence of astaxanthin and 1H-Indole, 2,3,5-trimethyl-1-(trimethylsilyl)- in vegetative tissues. On the contrary, kaur-16-ene-(8β,13β), an intermediate of GAs synthesis, gibberellic acid, and fumaric acid were recorded in reproductive tissues by GC–MS analysis. The first principal component analysis (PCA) biplot revealed two principal components that together accounted for 34.59 % and 22.96 % of the variance in the tissues of vegetative and reproductive phases respectively. In the second PCA biplot, the male and female flower-initiated tissues showed principal component levels of 42.94 % and 26.48 %, respectively. Also, the heat map analysis showed the fluctuation of phytohormone levels during both phases.

Model-based scenarios for achieving net negative emissions in the food system

Most climate mitigation scenarios point to a combination of GHG emission reductions and CO2removal for avoiding the most dangerous climate change impacts this century. The global food system is responsible for ~1/3 of GHG emissions and thus plays an important role in reaching emission targets. Consumers, technology innovation, industry, and agricultural practices offer various degrees of opportunity to reduce emissions and remove CO2. However, a question remains as to whether food system transformation can achieve net negative emissions (i.e., where GHG sinks exceed sources sector wide) and what the capacity of the different levers may be. We use a global food system model to explore the influence of consumer choice, climate-smart agro-industrial technologies, and food waste reductions for achieving net negative emissions for the year 2050. We analyze an array of scenarios under the conditions of full yield gap closures and caloric demands in a world with 10 billion people. Our results reveal a high-end capacity of 33 gigatonnes of net negative emissions per annum via complete food system transformation, which assumes full global deployment of behavioral-, management- and technology-based interventions. The most promising technologies for achieving net negative emissions include hydrogen-powered fertilizer production, livestock feeds, organic and inorganic soil amendments, agroforestry, and sustainable seafood harvesting practices. On the consumer side, adopting flexitarian diets cannot achieve full decarbonization of the food system but has the potential to increase the magnitude of net negative emissions when combined with technology scale-up. GHG reductions ascribed to a mixture of technology deployment and dietary shifts emerge for many different countries, with areas of high ruminant production and non-intensive agricultural systems showing the greatest per capita benefits. This analysis highlights potential for future food systems to achieve net negative emissions using multifaceted “cradle-to-grave” and “land-to-sea” emission reduction strategies that embrace emerging climate-smart agro-industrial technologies.

Genetic response of hybrid maize line to downy mildew caused by Peronosclerospora spp. infection

Maize is the second staple food commodity in Indonesia. Apart from being the main source of carbohydrates and protein, the production of maize continues to increase along with the escalation of population growth and animal feed requirements in the last few years. The potential to increase the national production of maize is still feasible because of the yield gap between the potential yields of new superior varieties and the level of yields obtained by farmers. The yield gap caused by biotic stress in maize is mainly caused by pathogens such as downy mildew due to Peronosclerospora spp. Downy mildew distribution is sporadic that can infect a wide area. In Indonesia, it spreads widely and significantly reduces yields in the areas of maize production centres in East Java, Central Java, South Sulawesi, North Sulawesi, Gorontalo, Lampung, and Sumatera. These obstacles can be overcome by integrated pest and disease control technology. One strategy is to discover downy mildew-resistant varieties that can be combined with other control treatments. The phenomenon of resistance to downy mildew infection of several hybrid maize strains began to be detected in the vegetative growth phase, with symptoms beginning at 14 days after planting (DAP), increasing with plant age, and reaching its peak after 28-35 DAP and then the symptoms will gradually disappear until no infection after 42 HST. This study analyses the resistant maize varieties from 2020 to 2022. The data showed the susceptible comparison variety (Anoman) was infected with 88.94% to 100%. In 2020, BMD73 showed a resistant reaction to Philippinensis species, other strains were classified as susceptible in P. maydis except BMD 76. All strains showed highly susceptible and susceptible reactions. In 2021, in P. philippinensis all strains FCP10-FCP16 showed a resistant reaction, but line FCP10-FCP16 had a resistance response that was classified as moderately resistant to P. maydis. The incidence of genetic response in 2022, except BMD86, strains BMD81-BMD85 were classified as resistant, as well as in the P. maydis endemic area all strains showed the same reaction.

Fine-tuning the CROPGRO-Sunflower model and its application to the quantification of crop responses to environmental and management variables

The Decision Support System for Agrotechnology Transfer (DSSAT) contains a sunflower model based on CROPGRO. This model assumes some parameters values out of the crop species variability. Besides, this model has not been assessed for simulating grain yield and grain oil content in contrasting environments. The main goal of this study was to generate and test a revised CROPGRO-Sunflower model. In addition, we used the revised CROPGRO-Sunflower to quantify crop responses to environmental and management variables. Three sunflower models: a revised CROPGRO-Sunflower, the original CROPGRO-Sunflower and the OILCROP-SUN were calibrated and evaluated across contrasting environments. We compared the revised CROPGRO-Sunflower with the original CROPGRO-Sunflower and OILCROP-SUN in terms of ability to simulate crop development, growth, grain yield and grain oil content. Crop responses to soil depth, sowing date, and El Niño-Southern Oscillation (ENSO) effects were quantified using the revised CROPGRO-Sunflower in combination with climatic records for 37 growing seasons to simulate yield in two contrasting environments of Argentina: Balcarce and Reconquista. Crop growth, grain yield and grain oil content were better simulated by the revised CROPGRO-Sunflower than by OILCROP-SUN. Simulated yield had a root mean square error (RMSE) of 48 g m-2 with revised CROPGRO-Sunflower and of 119 g m-2 with OILCROP-SUN. Moreover, RMSE for simulated grain oil concentration was 2% for revised CROPGRO-Sunflower and 11% for OILCROP-SUN. Deep soils and late sowing dates resulted in higher grain yield at Balcarce. Sowing date did not affect grain yield at Reconquista. An effect of the ENSO phases on sunflower grain yield was found. "La Niña" phase was associated with the lowest grain yields at both sites. Modifications made to the original CROPGRO-Sunflower improved model performance. The revised CROPGRO-Sunflower model can be utilized to simulate crop phenology, growth, grain yield and grain oil concentration over a wide range of environmental conditions. This calibrated and evaluated crop simulation model will allow to advance in the quantification of yield gaps and to study the impact of other management practices on sunflower crop production.

An Appraisal of Technological Interventions on Mustard Crop under Cluster Front Line Demonstrations

Aims: To boost production and profitability, The current study's evaluation of technical interventions focused on a cluster front line demonstration on mustard crop, which was carried out in the KVK's operational territory in district Bhadohi of Uttar Pradesh.&#x0D; Study Design: Yield gap analysis under cluster front line demonstration.&#x0D; Place and Duration of Study: The present study was conducted by ICAR-IIVR - Krishi Vigyan Kendra, Bhadohi on mustard at farmer’s field in different blocks of Bhadohi district under cluster front line demonstration during the period 2016-17 to 2020-21.&#x0D; Methodology: From 2016-17 through 2020-21, 374 demonstrations were carried out on farmer fields totaling 153 hectares under cluster front line demonstration, with farmer practice acting as the comparison control. KVK scientists collected yield, production expenses, and return data from farmers' practice plots (control plots) and front-line demonstration plots. Finally, the extension gap, technology gap, and technology index were calculated using the methods describe in Samui et al. [1].&#x0D; Results: The five-year study's findings show that the demonstration plots' average annual yield was 24.20 q/ha in compared to the traditional agricultural plots' average annual yield of 17.26 q/ha. This higher yield of 4.85 q/ha and the 40.12% rise in mustard productivity over the previous five years may be enough to meet the state's current needs for oilseeds. The five-year averages for the technology gap, extension gap, and technology index were found to be 5.8 q/ha, 6.8 q/ha, and 19.35%, respectively. The finding unequivocally shows that CFLDs have advantages over conventional practices. The technology gap, extension gap, and technology index five-year averages were determined to be 5.8 q/ha, 6.8 q/ha, and 19.35%, respectively. Under the demonstration plot, the Benefit Cost Ratio was shown to be greatest (3.0) during the study year 2017-18 and lowest (2.24) during the study year 2019-20, but it averaged 2.65 during the five-year study period. As a result, positive benefit-cost ratios established the economic sustainability of the interventions and persuaded farmers in the Uttar Pradesh area of Bhadohi of their worth.&#x0D; Conclusion: According to the findings of the five-year study, the demonstration plots' pooled five-year average production was 24.20 q/ha as opposed to the traditional farmer practices plots' 17.26 q/ha. This enhanced yield of 4.85 q/ha and the 40.12% rise in mustard productivity over the previous five years, may be helpful meet to the state's current needs for oilseeds. The finding unequivocally shows that CFLDs have advantages over conventional practices. During the years of investigation, it was shown that the benefit-cost ratio was higher when agricultural practices were demonstrated. According to the result it is concluded that the yield and net profit may be increase using HYV RH-749 with the recommended packages of practices in mustard crop.