Yield Of Cereal Crops Research Articles

Seed row placement relative to the previous crop stubble row can harness systems benefits on water repellent sands

Context Innovations to improve crop establishment are critical to unlocking the full potential of early sown winter cereal cropping systems. Aims The aim of this set of experiments was to evaluate the systems benefits of near-row sowing treatments for surface soil water, crop establishment, crop competition with weeds, root disease infection and cereal crop yield on sandy soils in low-rainfall environments. Methods Six of the 10 site–years evaluated were on water repellent sands with the remainder on sand and loam. A second set of experiments on a water repellent sand evaluated if furrow applied amendments to increase soil fertility in the crop row might generate additional benefits to the near-row sowing effect. Key results Significant grain yield benefits from near-row placement (up to 30%) were measured in 2 site years and these were associated with crop establishment gains, improved access to furrow soil water storage and weed seed reductions, which occurred in 3 site years. In a water repellent sand, near-row placement combined with extra nutrition input generated an additional grain yield benefit (+0.4 t/ha), as did a one-off 22 cm deep furrow tilling treatment designed to bring deeper soil moisture into the seed zone (+0.4 t/ha). Conclusions Near-row placement of crop seeds can provide systems benefits in water repellent sands. The conversion of these benefits to yield benefits occurred in 30% of site-years tested on repellent sand. Implications Further innovation is required to ensure that these seeder-based innovations generate predictable responses and scaled up evaluation is necessary to fully understand the systems and landscape level benefits of improved crop establishment in soils that often suffer low and uneven crop establishment numbers.

Power shortages in Pakistan Causes and Solutions

Load shedding, sporadic power outages, or other disruptions in Pakistan's electrical supply are on the rise. The problem has major ramifications for the nation, particularly in its rural parts. Tariffs had to be raised as a result of the increasing cost of generating electricity as well as the large percentage of line losses, which resulted in losses for the corporations that produce, transmit, and distribute electricity. Power shortages have also made it difficult for the manufacturing sector to add jobs, which has greatly increased Pakistan's unemployment rate. The 42 years at a 10% yearly pace. The government strongly advocated a program of quick electrification in rural regions during this time. Due to this, homes' percentage of overall power usage rose from 12% in 1971–1972 to 47% in 2000–2001. The empirical results demonstrate that load shedding has a hurts hold income, cereal crop yields, and food security levels. Load shedding also led to a rise in poverty levels. According to the findings, a program to lessen load shedding will help increase agricultural output, family income levels, and poverty levels. Farmers in rural Pakistan may find it easier to plan farm management if load shedding is implemented at the right time and for the right amount of time.

The current regime of heat waves and their impact on the yield of cereal crops in Ukraine

Heat waves are one of the most dangerous meteorological phenomena, the manifestations of which have become more frequent in all regions of the globe in recent decades. Due to excessively high temperatures persisting for a long time, heat waves cause heat stress in living organisms and plants, and negatively affect various sectors of the national economy. Although the mechanism of heat wave formation is well known, the question of determining and predicting the intensity and duration of these processes in advance, as well as the areas of their propagation, remains open, including due to the lack of unified concept of a heat wave. This study analyzed the spatiotemporal distribution of extremely warm days and heat waves for the period 1996-2021 in 16 regions of Ukraine, where the production of the main agricultural crops (winter wheat, spring barley, corn) is concentrated. The analysis was performed using the surface skin temperature Ts, which contains information about the temperature of both the canopy and ground surface.
 It was found that during the study period, the number of extremely warm days increased in all regions of the country and in all seasons of the year, with the most significant increase occurring in the last decade in winter and autumn. The warmest year was 2020, when the number of extremely warm days in some regions reached 100-106 per year. The frequency of heat waves at the end of the study period almost doubled compared to the beginning, reaching an average of 8-10 cases per year. The average seasonal frequency of heat waves was 4-5 cases in summer and 2-4 cases in other seasons. The longest heat waves lasting 17-19 days were recorded in all agro-climatic zones in August 2010. In other seasons, the maximum duration of heat waves did not exceed 10-14 days.
 Statistical assessment of the relationship between the seasonal number of extremely warm days and the grain yield crops showed that an increase in these days in the spring leads to decrease in the yield crops of winter wheat and spring barley; in summer this negative impact is observed for corn.

Perceived Effects of Rainfall and Temperature Variability on Yields of Cereal Crops in the Mion District of Northern Ghana

Climate variability has been a major threat to achieving sustainable food production in many countries, including Ghana. This is attributable to insufficient and erratic rainfall coupled with increasing temperature. This study examined the perceived effects of rainfall and temperature variability on yields of cereal crops in the Mion District of the Northern Region. The study reveals that farmers in the Mion District have experienced changes in climatic conditions evident in high temperatures and low rainfall. The study also reveals that rainfall and temperature variability adversely affect the yields of cereal crops such as rice, maize, and millet. The effect could manifest in either yield reduction or total crop failure of cereals. The study also showed that factors that enable farmers to respond to impacts of rainfall and temperature variability are Agric extension services, application of fertilizer, irrigation farming, use of improved seeds, and favourable government policies such as subsidies and credit facilities. The study, therefore, concludes that yields of cereal crops are adversely affected by rainfall and temperature variability. However, farmers resort to Agric extension services, application of fertilizer, irrigation farming, use of improved variety of seeds, and favourable government policies in response to the impacts of rainfall and temperature variability. The study recommends that government should employ more extension agents and construct more irrigation facilities in the Mion District to reduce the adverse effects of climate variability on yields of cereal crops.

Modelling the impacts of climate change on cereal crop production in East Africa: evidence from heterogeneous panel cointegration analysis.

Climate change has become an issue of concern for sustainable agriculture production. East African nations are heavily reliant on the agriculture sector, which accounts for a substantial amount of their gross domestic product (GDP) and employment. Due to climatic fluctuations, the output of the sector became very unpredictable. Hence, this study investigates the effects of climate change on cereal crop production in nine East African nations between 1990 and 2018. The study implemented pooled mean group (PMG) approach to examine the long-run and short-run dynamic impacts of the varying climatic circumstances on the output of cereal crops. The results reveal that rainfall and carbon emissions have favourable and significant long-run effects on cereal crop output, even though their short-run impacts are negligible. Additionally, cultivated land area and rural population have a constructive role in enhancing agricultural output both in the long-run and short-run. However, average temperatures have negative repercussions on cereal crop production in the long-run and short-run, even though the magnitude of sensitivity is greater in the short-run. Dynamic ordinary least squares (DOLS) and fully modified ordinary least squares (FMOLS) validated the robustness of the long-run findings of the PMG technique. Besides, the Dumitrescu-Hurlin panel causality outcomes indicate that cereal crop output has a bidirectional causality with temperature, carbon emissions, and cropped area. The study further demonstrated unidirectional causation from rural population to cereal crop yield. The study recommends that East African policymakers improve the quality of farm inputs, the adoption of climate-resilient farming practices, the development of water retention facilities and the establishment of crop diversification initiatives.

Identification of QTL underlying the main stem related traits in a doubled haploid barley population.

Lodging reduces grain yield in cereal crops. The height, diameter and strength of stem are crucial for lodging resistance, grain yield, and photosynthate transport in barley. Understanding the genetic basis of stem benefits barley breeding. Here, we evaluated 13 stem related traits after 28 days of heading in a barley DH population in two consecutive years. Significant phenotypic correlations between lodging index (LI) and other stem traits were observed. Three mapping methods using the experimental data and the BLUP data, detected 27 stable and major QTLs, and 22 QTL clustered regions. Many QTLs were consistent with previously reported traits for grain filling rate, internodes, panicle and lodging resistance. Further, candidate genes were predicted for stable and major QTLs and were associated with plant development and adverse stress in the transition from vegetative stage to reproductive stage. This study provided potential genetic basis and new information for exploring barley stem morphology, and laid a foundation for map-based cloning and further fine mapping of these QTLs.

Manipulating GA-Related Genes for Cereal Crop Improvement.

The global population is projected to experience a rapid increase in the future, which poses a challenge to global food sustainability. The "Green Revolution" beginning in the 1960s allowed grain yield to reach two billion tons in 2000 due to the introduction of semi-dwarfing genes in cereal crops. Semi-dwarfing genes reduce the gibberellin (GA) signal, leading to short plant stature, which improves the lodging resistance and harvest index under modern fertilization practices. Here, we reviewed the literature on the function of GA in plant growth and development, and the role of GA-related genes in controlling key agronomic traits that contribute to grain yield in cereal crops. We showed that: (1) GA is a significant phytohormone in regulating plant development and reproduction; (2) GA metabolism and GA signalling pathways are two key components in GA-regulated plant growth; (3) GA interacts with other phytohormones manipulating plant development and reproduction; and (4) targeting GA signalling pathways is an effective genetic solution to improve agronomic traits in cereal crops. We suggest that the modification of GA-related genes and the identification of novel alleles without a negative impact on yield and adaptation are significant in cereal crop breeding for plant architecture improvement. We observed that an increasing number of GA-related genes and their mutants have been functionally validated, but only a limited number of GA-related genes have been genetically modified through conventional breeding tools and are widely used in crop breeding successfully. New genome editing technologies, such as the CRISPR/Cas9 system, hold the promise of validating the effectiveness of GA-related genes in crop development and opening a new venue for efficient and accelerated crop breeding.

Small scale biogas technology adoption behaviours of rural households and its effect on major crop yields in East Gojjam Zone of Ethiopia: propensity score matching approach

The aim of the research was to identify and evaluate the main determinants of small-scale biogas technology adoption and its impact on crop yields. The case study is based on cross-sectional data gathered from 335 rural households in Ethiopia’s East Gojjam Zone. This study made use of both primary and secondary data. A questionnaire-based survey was used to collect primary data from 197 biogas adopter (treated) and 138 non-adopter (control) households. Propensity score matching (PSM) methods were used to estimate the determinants and impact of biogas technology adoption on cereal crop yields. According to probit model estimates, the main determinants were cattle head, follow-up and support, extension contact, training access, distance to water sources, and distance to the market. Ethiopian agricultural and rural development policies should consider the impact of household biogas technology adoption behavior when developing policy actions under the Agricultural Transformation Plan.

Impact of recent climate change on corn, rice, and wheat in southeastern USA

Climate change and its impact on agriculture productivity vary among crops and regions. The southeastern United States (SE-US) is agro-ecologically diversified, economically dependent on agriculture, and mostly overlooked by agroclimatic researchers. The objective of this study was to compute the effect of climatic variables; daily maximum temperature (Tmax), daily minimum temperature (Tmin), and rainfall on the yield of major cereal crops i.e., corn (Zea mays L.), rice (Oryza sativa L.), and wheat (Triticum aestivum L.) in SE-US. A fixed-effect model (panel data approach) was used by applying the production function on panel data from 1980 to 2020 from 11 SE-US states. An asymmetrical warming pattern was observed, where nocturnal warming was 105.90%, 106.30%, and 32.14%, higher than the diurnal warming during corn, rice, and wheat growing seasons, respectively. Additionally, a shift in rainfall was noticed ranging from 19.2 to 37.2 mm over different growing seasons. Rainfall significantly reduced wheat yield, while, it had no effect on corn and rice yields. The Tmax and Tmin had no significant effect on wheat yield. A 1 °C rise in Tmax significantly decreased corn (− 34%) and rice (− 8.30%) yield which was offset by a 1 °C increase in Tmin increasing corn (47%) and rice (22.40%) yield. Conclusively, overall temperature change of 1 °C in the SE-US significantly improved corn yield by 13%, rice yield by 14.10%, and had no effect on wheat yield.

Growth models for forecasting the area, production and yield of major cereal crops in Ethiopia

ABSTRACT Although accurate forecasting of the production of major cereal crops is important to make policy decisions related to their supply, demand and import/export, very little work has been done in Ethiopia. Therefore, this study aimed to develop the best performing trend models for area, production, and yield of wheat (Triticum aestivum L.), teff [Eragrostis tef (Zucc.) Trotter], and maize (Zea mays L.) in Ethiopia, and to provide forecasts for 2019 to 2023. For each crop, the best-performing model was selected among linear, quadratic, exponential growth, and S-curve trend models using five performance measures (mean absolute percent error [MAPE], mean absolute deviation [MAD], mean squared deviation [MSD], coefficient of efficiency [E], and index of agreement [d]). Quadratic trend model was the best for area of wheat and teff, production of wheat, teff, and maize, and wheat and maize yields. S-curve and Linear trend models were the best for area of maize and yield of teff, respectively. Forecasts for 2019 to 2023 using the best-performing model revealed that cultivated area for these three cereals will decrease by 3,581 ha in Ethiopia, but their combined total production will increase by 4,896,630 tons, and productivity of wheat, teff, and maize will increase by 20.3%, 13.2%, and 13.8%, respectively, which is slightly higher than the projected population growth (10.9%) during this time. Although these results indicate that Ethiopia is on track to meet the second SDG, government policymakers and other stakeholders can use these findings to ensure sustainable food and nutrition security in Ethiopia.

The Roles of Arbuscular Mycorrhizal Fungi in Influencing Plant Nutrients, Photosynthesis, and Metabolites of Cereal Crops—A Review

Arbuscular mycorrhizal (AM) fungi are one of the important microbiota involved in a relationship with plant roots in which the plants and fungi both share and exchange nutrients and shelter. Cereal crops are the most essential sources of carbohydrates, dietary protein, and vitamin B for humans, and they supply the most fundamental diets. AM fungi are introduced as the optimal approach for real agricultural systems for increasing growth and productivity. According to a study from the previous decade, AM fungi were shown to promote crop growth and production, particularly in cereal crops. The AM fungi symbiosis provides a pleasant environment for microorganisms in the root and soil system, which promotes plant nutrition and water availability. AM fungi increase nutrient uptake and assimilation and also increase photosynthetic activity, which is directly associated with plant growth. Furthermore, AM fungi increase the primary and secondary metabolites, as well as soluble proteins and carbohydrates, in cereals crops. AM fungi have been shown to improve plant biomass, yield, and productivity in cereal crops. Additionally, the use of AM fungi enhances plants’ stress tolerance against various environmental stresses. In this review, we integrate the recent findings regarding the effects of AM fungi application on soil, root systems, nutrient availability and uptake, photosynthesis, metabolites, plant growth, and productivity. Furthermore, a large number of studies have been reviewed, and several limitations and research gaps have been identified that must be addressed in future studies.

“Famine Foods” and the Values of Biodiversity Preservation in Israel-Palestine

This essay considers the preservation of prickly alkanet, a wild plant that is a constituent of Palestinian cuisine. While tracking the dominant practices of biodiversity preservation that justify the documentation and collection of plants in national and international systems, it ultimately suggests recipes rather than seeds as targets of preservation. For, in seed saving oriented toward community control of resources, knowledge of the plant begins with the ability to prepare it for the table, not with the ability to analyze it in a lab or cultivate it in a field. As a logic of biodiversity preservation, cooking thus serves as an expression of community solidarity and a counter-hegemonic form of knowledge, prioritizing the local sharing of resources and rituals above floristic nationalisms and the extractive complex of international food security. Such an approach calls into question the orientation of modern agricultural development, which has prioritized increasing yield in primary cereal crops.

Enhancing Smallholder Wheat Yield Prediction through Sensor Fusion and Phenology with Machine Learning and Deep Learning Methods

Field-scale prediction methods that use remote sensing are significant in many global projects; however, the existing methods have several limitations. In particular, the characteristics of smallholder systems pose a unique challenge in the development of reliable prediction methods. Therefore, in this study, a fast and reproducible new approach to wheat prediction is developed by combining predictors derived from optical (Sentinel-2) and radar (Sentinel-1) sensors using a diverse set of machine learning and deep learning methods under a small dataset domain. This study takes place in the wheat belt region of Ethiopia and evaluates forty-two predictors that represent the major vegetation index categories of green, water, chlorophyll, dry biomass, and VH polarization SAR indices. The study also applies field-collected agronomic data from 165 farm fields for training and validation. According to results, compared to other methods, a combined automated machine learning (AutoML) approach with a generalized linear model (GLM) showed higher performance. AutoML, which reduces training time, delivered ten influential parameters. For the combined approach, the mean RMSE of wheat yield was from 0.84 to 0.98 ton/ha using ten predictors from the test dataset, achieving a 99% confidence interval. It also showed a correlation coefficient as high as 0.69 between the estimated yield and measured yield, and it was less sensitive to the small datasets used for model training and validation. A deep neural network with three hidden layers using the ten influential parameters was the second model. For this model, the mean RMSE of wheat yield was between 1.31 and 1.36 ton/ha on the test dataset, achieving a 99% confidence interval. This model used 55 neurons with respective values of 0.1, 0.5, and 1 × 10−4 for the hidden dropout ratio, input dropout ratio, and l2 regularization. The approaches implemented in this study are fast and reproducible and beneficial to predict yield at scale. These approaches could be adapted to predict grain yields of other cereal crops grown under smallholder systems in similar global production systems.

Blocking Rice Shoot Gravitropism by Altering One Amino Acid in LAZY1.

Tiller angle is an important trait that determines plant architecture and yield in cereal crops. Tiller angle is partially controlled during gravistimulation by the dynamic re-allocation of LAZY1 (LA1) protein between the nucleus and plasma membrane, but the underlying mechanism remains unclear. In this study, we identified and characterized a new allele of LA1 based on analysis of a rice (Oryza sativa L.) spreading-tiller mutant la1G74V, which harbors a non-synonymous mutation in the predicted transmembrane (TM) domain-encoding region of this gene. The mutation causes complete loss of shoot gravitropism, leading to prostrate growth of plants. Our results showed that LA1 localizes not only to the nucleus and plasma membrane but also to the endoplasmic reticulum. Removal of the TM domain in LA1 showed spreading-tiller phenotype of plants similar to la1G74V but did not affect the plasma membrane localization; thus, making it distinct from its ortholog ZmLA1 in Zea mays. Therefore, we propose that the TM domain is indispensable for the biological function of LA1, but this domain does not determine the localization of the protein to the plasma membrane. Our study provides new insights into the LA1-mediated regulation of shoot gravitropism.

SCREENING OF THIRD FILIAL (F3) SEGREGATING POPULATION FOR SALT TOLERANCE IN CEREAL: A REVIEW

Cereal crops such as maize, wheat, rice, and others are cultivated in every part of the world. However, cereals crop cultivation globally has been affected by salinity stress. Salinity stress causes a reduction in the growth, yield and productivity of cereal crops. Hence, to overcome the problem related to salinity stress, several plans are made to develop a salinity tolerance cereal variety. Therefore, various strategies, from phenotypic and molecular screening, have been introduced to develop salinity tolerance cereal varieties. Salinity tolerance is a crucial trait that must be inserted into cereal crops to maximize the yield productivity of cereals crops. The objective of this review is to undergo screening for salinity tolerance in the third filial (F3) segregating population of cereals to identify the large amounts of lines correlated with salt tolerance which were further used in the breeding process. Besides, the selection process of F3 and other populations of the cereals is conducted on yield and yield components and the correlation between traits linked with salt tolerance. Thus, this review study will focus on the screening and selection process of the F3 and other generations on salinity-tolerant and high-yielding cereals developments.

Soybean Crops Penalize Subsequent Wheat Yield During Drought in the North China Plain.

Contemporary wisdom suggests that inclusion of legumes into crop rotations benefit subsequent cereal crop yields. To investigate whether this maxim was generically scalable, we contrast summer soybean–winter wheat (SW) with summer maize–winter wheat (MW) rotation systems in an extensive field campaign in the North China Plain (NCP). We identify heretofore unseen interactions between crop rotation, synthetic N fertilizer application, and stored soil water. In the year with typical rainfall, inclusion of soybean within rotation had no effect on wheat ear number and yield, while N fertilization penalized wheat yields by 6–8%, mainly due to lower dry matter accumulation after anthesis. In contrast, in dry years prior crops of soybean reduced the rate and number of effective ears in wheat by 5–27 and 14–17%, respectively, leading to 7–23% reduction in wheat yield. Although N fertilization increased the stem number before anthesis in dry years, there was no corresponding increase in ear number and yield of wheat in such years, indicating compensating reduction in yield components. We also showed that N fertilization increased wheat yield in MW rather than SW as the former better facilitated higher dry matter accumulation after flowering in dry years. Taken together, our results suggest that soybean inclusion reduced soil available water for subsequent wheat growth, causing yield penalty of subsequent wheat under drought conditions. We call for more research into factors influencing crop soil water, including initial state, crop water requirement, and seasonal climate forecasts, when considering legumes into rotation systems. Graphical Response of wheat population and yield to soybean inclusion under limited-irrigation.

Persistence versus dynamical seasonal forecasts of cereal crop yields.

Climate change is expected to have impacts on the balance of global food trade networks and food security. Thus, seasonal forecasts of precipitation and temperature are an essential tool for stakeholders to make timely choices regarding the strategies required to maximize their expected cereal yield outcomes. The availability of state-of-the-art seasonal forecasts such as the European Centre for Medium-Range Weather Forecasts (ECMWF) system 5 (SEAS5) may be an asset to help decision making. However, uncertainties and reduced skill may hamper the use of seasonal forecasts in several applications. Hence, in this work, we aim to understand the added value of such dynamical forecasts when compared to persistent anomalies of climate conditions used to predict the production of wheat and barley yields. With that in mind, empirical models relating annual wheat and barley yields in Spain to monthly values of precipitation and temperature are developed by taking advantage of ECMWF ERA5 reanalysis. Then, dynamical and persistence forecasts are issued at different lead times, and the skill of the subsequent forecasted yield is verified through probabilistic metrics. The results presented in this study demonstrate two different outcomes: (1) wheat and barley yield anomaly forecasts (dynamical and persistent) start to gain skill later in the season (typically from April onwards); and (2) the added value of using the SEAS5 forecast as an alternative to persistence ranges from 6 to 16%, with better results in the southern Spanish regions.

Role of neonicotinoid preparations for spike grain crop seedlings protection against click beetle and Frit fly larvae in Belarus

Recently, in winter and spring grain crops for pre-sowing seed treatment among the assortment of insecticides the preparations of insecticidal and insectofungicidal action based on neonicotinoids: acetamiprid, imidacloprid, clothianidin and thiamethoxam have been widely used. At the current stage of chemical method development of plant protection against harmful arthropods, neonicotinoids are rapidly developing and promising group of neurotoxic insecticides and having a fundamentally different mechanism of action on insects – they inhibit nicotine-acetylcholine receptors. Pre-sowing seed material treatment with insecticides protects the sown seeds, hypocotyls and aboveground plant organs against soil and intrastem pests. It is revealed that during the growing seasons of 2019–2021 in the experimental field, economically significant phytophages are lined click beetle (Agriotes lineatus L.) and Frit flies of autumn and spring generations (Oscinella spp.), indicating the study of their larvae number and harmfulness and measures allowing to control the vital activity of insects in agrocenoses conditions. Plants damaged by them lag behind in growth and die. Improving the range of effective preparations with different active substances used by the method of pre-sowing treatment of grain crop seeds to protect plants during germination against phytophages is an obligatory link in the technology of crops cultivation and one of the factors of their number effective control, what has determined the relevance of the choice of our research topic. Pre-sowing winter and spring cereals seed treatment with neonicotinoid preparations based on imidacloprid (Coyote, SC, Sidoprid, FSC, Tabu, WSC), acetamiprid (Leatrin, SC, Bagrets Plus, SC, Vershina Plus, SC) and thiamethoxam (Questor Forte, SC) have provided plant seedlings high protection against click beetle and Frit fly larvae damage. The results of studies conducted in 2019–2021 have shown that the effectiveness of preparations have varied by years depending on weather conditions and pests number before sowing and at seedlings stage. The indicators of winter grain crops plant damage reduction by wireworms have made 78,8–91,1 %, Frit flies 60,0–85,0 %, spring cereals – 80,0–91,6 % and 80,7–91,1 %, respectively. Through years of research the insecticides for seed treatment have helped to increase the stored grain yield of cereal crops, on the average, from 0,7 to 6,2 cwt/ha, or 1,0–13,5 %. The data obtained will serve as a basis for justifying protective measures to reduce the number and harmfulness of soil-dwelling and terrestrial pests in order to improve the phytosanitary situation in the agrocenoses of cereals.

The quest for optimal plant architecture.

Changes in plant architecture can improve cereal crop yield.

Decomposing crop model uncertainty: A systematic review

Crop models are essential tools for analysing the effects of climate variability, change on crop growth and development and the potential impact of adaptation strategies. Despite their increasing usage, crop model estimations have implicit uncertainties which are difficult to classify and quantify. Failure to address these uncertainties may result in poor advice to policymakers and stakeholders for the development of adaptation strategies. Since the 1990s, the number of crop model uncertainty assessments that consider different sources of model uncertainty (model structure, model parameters and model inputs such as climate, soil, and crop management practices) has increased significantly. We present the outcomes of a systematic review focused on uncertainty assessments of crop model outputs (mainly grain yield) and crop model uncertainty decomposition. We reviewed 277 articles from 1991 to 2019 which included studies conducted in 82 countries (460 locations) across all continents. 57% of the articles have been published between 2015 and 2019. 52% of the studies focus on input uncertainty assessments with climate change projections as the most frequently considered source of input uncertainty. Only 28% and 20% of the studies, respectively, dealt with uncertainties related to model parameters and model structure. The latter was mainly quantified using multi-model ensembles. Over half the studies were carried out in European and Asian countries, 34% and 23%, respectively. Most articles estimated model uncertainty focusing on the grain yield of major cereal crops (wheat > maize > rice) using the Decision Support System for Agrotechnology Transfer (DSSAT) model. Sensitivity analysis was the most used technique to quantify the contribution of different sources of uncertainty although the range of approaches for uncertainty quantification was wide. There is a need for standard procedures to estimate crop model uncertainty and evaluate estimates. We discuss the challenges of quantifying the components of uncertainty within crop models and identify research needs to better understand sources of uncertainty and thus improve the accuracy of crop models.