Yield Of Cereal Crops Research Articles

Elucidation of biochemical and physiological modulations in Triticum aestivum induced by green synthesized nitrogen-enriched zinc nano-complexes

This study investigates the efficacy of a green synthesized nitrogen-rich zinc complex (Zn-NC) using quinoline (C9H7N) as the nitrogen-rich substrate to enhance growth and biochemical properties in wheat (Triticum aestivum). The performance of Zn-NC was compared to standard zinc oxide nanoparticles (ZnO-NPs). Both Zn-NC and ZnO-NPs were characterized using scanning electron microscopy (SEM) and X-ray diffraction (XRD), and dynamic light scattering (DLS). Three concentrations (100, 200, and 500 ppm) of each compound, along with a control, were applied to local soil samples (n=3). The physiological (biomass, elongation) and biochemical effects (chlorophyll, carotenoids, flavonoids, and phenols) on wheat were investigated. Potential phytotoxic effects were evaluated to establish the biostimulants' safety thresholds. Plants treated with green Zn-NC showed an average increase in shoot length of 25 % compared to the control group. The chlorophyll content in plants treated with ZnO-NPs increased by 18 %, while those treated with green Zn-NC increased by 12 % compared to control. Application of ZnO-NPs resulted in a 30 % increase in total yield, whereas green Zn-NC treatment led to a 22 % yield increase. The root biomass of plants treated with ZnO-NPs increased by 28 %, and those treated with green Zn-NC saw a 20 % increase compared to controls. Based on the optimization of overall results, the ZnO NPs showed phytotoxic effects at concentrations above 200 ppm, while green Zn-NC exhibited no significant phytotoxicity even at concentrations up to 300 ppm. This study delineates the optimal concentrations of Zn-NC and ZnO-NPs that can enhance nutrient delivery and yield in cereal crops while mitigating phytotoxic risks. The findings provide valuable insights into applying nano-biostimulants in agroecosystems, highlighting their potential to improve productivity and sustainability in agriculture.

Forecasting area and yield of cereal crops in India: intelligent choices among stochastic, machine learning and deep learning techniques

Forecasting area and yield of cereal crops in India: intelligent choices among stochastic, machine learning and deep learning techniques

Does Climate Change and Energy Consumption Affect the Food Security of European Union Countries? Empirical Evidence from a Panel Study

This study aims to provide empirical evidence on whether using renewable and non-renewable energy, CO2 emissions, and the resulting changes in temperature and precipitation can alter cereal yields in European Union countries. To this end, a panel data set covering 1992–2021 has been used to analyse the impact of climate change and economic factors on cereal production in European Union countries. The study employed various analytical techniques to better understand the impact of climate change and economic factors on cereal crop yields. These included using annual average temperature and rainfall to measure climate change, energy consumption, and economic growth to analyse the economic aspects. To achieve the objective, feasible generalised least squares (FGLS) models with robust standard errors and bootstrap and a quantile regression (QR) model with marginal analysis were employed. The Westerlund cointegration test confirmed the presence of cointegration between cereal production and climate variables, economic growth, and energy consumption. The results indicate that increases in temperature and precipitation may contribute to increased cereal production in European Union countries. In contrast, energy consumption, including renewable energy and CO2 emissions, may have a nonlinear effect on cereal production. Quantile regression analysis suggests climate change may impact crop yields most in countries with low and moderate cereal production per hectare. Increased CO2 emissions may increase yields in the initial period, but excessive CO2 may negatively impact cereal production in the long term. It would be advisable for countries with low and moderate crop productivity to consider implementing technological advances and combating global warming by modernising cultivation methods and making greater use of renewable energy sources.

Environmental changes impact on vegetables physiology and nutrition – Gaps between vegetable and cereal crops

Projected changes in climate patterns, increase of weather extreme, water scarcity, and land degradation are going to challenge agricultural production and food security. Currently, studies concerning effects of climate change on agriculture mainly focus on yield and quality of cereal crops. In contrast, there has been little attention on the effects of environmental changes on vegetables that are necessary and key nutrition component for human beings, but quite sensitive to these climatic changes. Therefore, we reviewed the main changes of environmental factors under the current scenario as well as the impacts of these factors on the physiological responses and nutritional alteration of vegetables and the key findings based on modelling. The gaps between cereal crops and vegetables were pinpointed and the actions to take in the future were proposed. The review will enhance our understanding concerning the effects of environmental changes on production, physiological responses, nutrition, and modelling of vegetable plants.

FpPEX5 and FpPEX7 are involved in the growth, reproduction, DON toxin production, and pathogenicity in Fusarium pseudograminearum

Fusarium crown rot, caused by Fusarium pseudograminearum, is a devastating disease affecting the yield and quality of cereal crops. Peroxisomes are single-membrane organelles that play a critical role in various biological processes in eukaryotic cells. To functionally characterise peroxisome biosynthetic receptor proteins FpPEX5 and FpPEX7 in F. pseudograminearum, we constructed deletion mutants, ΔFpPEX5 and ΔFpPEX7, and complementary strains, ΔFpPEX5-C and ΔFpPEX7-C, and analysed the functions of FpPEX5 and FpPEX7 proteins using various phenotypic observations. The deletion of FpPEX5 and FpPEX7 resulted in a significant deficiency in mycelial growth and conidiation and blocked the peroxisomal targeting signal 1 and peroxisomal targeting signal 2 pathways, which are involved in peroxisomal matrix protein transport, increasing the accumulation of lipid droplets and reactive oxygen species. The deletion of FpPEX5 and FpPEX7 may reduce the formation of toxigenic bodies and decrease the pathogenicity of F. pseudograminearum. These results indicate that FpPEX5 and FpPEX7 play vital roles in the growth, asexual reproduction, virulence, and fatty acid utilisation of F. pseudograminearum. This study provides a theoretical basis for controlling stem rot in wheat.

Validating APSIM for the Northern Territory of Australia: An environment with challenging weather and soils

AbstractExtreme weather (high rainfall and temperatures) and challenging soils are sources of uncertainties in the use of current crop models that have been developed for more favorable environments. This may limit their applicability to guide and support decision making for the development of new agricultural regions in tropical environments. We evaluated the accuracy of the Agricultural Production Systems Simulator (APSIM) framework in representing yield and development of a range of crops across multiple locations in the Northern Territory of Australia, a tropical region with large potential for agricultural development. Observations of yield, biomass, and phenology for a range of crops from 28 experiments undertaken at three locations were compiled and used to develop simulations undertaken using APSIM version 7.10. Model performance varied with coefficients of determination and concordance correlation coefficients ranging from 0.36 to 0.98 and 0.37 to 0.93, respectively. Instances where model performance was less than ideal were associated with conditions presenting a limited number of observed values. Deviations by the model from yield observations were larger for situations with high‐yielding crops and low daily maximum temperatures during vegetative growth stages. Deviations in phenology were larger for conditions associated with water and N stress. APSIM was capable of representing the yield, biomass, and development of cereal and pulse crops and can be used with confidence to assist the expansion of agriculture in tropical environments such as the Northern Territory of Australia.

Анализ климата и сельскохозяйственных факторов для прогнозирования урожайности основных зерновых культур в Эфиопии: визуальный анализ (1995-2021 гг.)

<p>This paper serves as a foundational exploration into predicting the yields of important cereal crops in Ethiopia. We use a visual analytic approach to identify patterns in annual temperature, precipitation, area harvested, production, and yield data from 1995 to 2021 by integrating climate factors and agricultural practices. By examining these Agricultural variables, we hope to build links between shifting climatic conditions, agricultural decisions, and crop production, providing indispensable insights for stakeholders, farmers, and policymakers.</p>

Integrated Nutrient Management for Enhancing Cereal Crop Production: A Review

Integrated Nutrient Management (INM) is a holistic approach that aims to optimize nutrient use efficiency in cereal crop production by combining various sources of nutrients, including organic and inorganic fertilizers. The integration of organic materials, such as crop residues and manures, with chemical fertilizers is emphasized to enhance soil fertility, improve nutrient availability, and promote sustainable agricultural practices. The synergistic effects of combining different nutrient sources contribute to balanced nutrition, reduced environmental impact, and increased resilience to changing climatic conditions. This abstract highlights the significance of integrated nutrient management as a comprehensive strategy for achieving higher cereal crop yields while addressing the challenges of nutrient management and environmental sustainability in modern agriculture. Integrated Nutrient Management not only boosts the growth, yield attributes, overall yield, and quality parameters of cereal crops but also fosters soil health, thereby fostering long-term agricultural sustainability.

Cereal yield forecasting in semi-arid region of Algeria using MODIS-NDVI

The prediction of cereals yields today is very important for global food security and helps decision-makers in the import-export operations of countries, especially with the rise world population. The advent of remote sensing technologies in precision farming systems has made cereal yield predictions possible, providing valuable insights into the temporal and spatial variations in cereal conditions across both large and small-scale crop lands. Among the various vegetation indices used to analyze these conditions, the normalized difference of vegetation index (NDVI) has emerged as a key indicator. The main objective of this study is to evaluate the possibility of using MODIS-NDVI data to forecast the yield of cereal crops (wheat and barley) in semi-arid region of Algeria (Setif). Additionally, identify the optimal timing for reliable and accurate crop yield forecasts. The remote sensing data utilized in this study covered the growing seasons from February to June, from 2002 to 2022. The results indicated a strong correlation between cereal grain yield and NDVI from late February to mid-March, with R² values ranging from 0.55 to 0.82 for the two cereal species. The RMSE of the NDVI based prediction model ranged from 0.01 t ha-1 to 0.276 t ha-1. The approximate average increase in the grain yield of barley and wheat lies between 0.659 to 0.746 t ha-1 with an increase of 0.1 in NDVI value. These results demonstrate the effectiveness of using MODIS-NDVI data for cereal yield forecasting in semi-arid region of Algeria, offering valuable predictions two to three months before the harvest.

Benefitting productivity and the environment: Current and future maize cropping systems improve yield while reducing nitrate load.

Increases in cereal crop yield per area have increased global food security. "Era" studies compare historical and modern crop varieties in controlled experimental settings and are routinely used to understand how advances in crop genetics and management affect crop yield. However, to date, no era study has explored how advances in maize (Zea mays L.) genetics and management (i.e., cropping systems) have affected environmental outcomes. Here, we developed a cropping systems era study in Iowa, USA, to examine how yield and nitrate losses have changed from "Old" systems common in the 1990s to "Current" systems common in the 2010s, and to "Future" systems projected to be common in the 2030s. We tested the following hypothesis: If maize yield and nitrogen use efficiency have improved over previous decades, Current and Future maize systems will have benefits to water quality compared to Old systems. We show that not only have maize yield and nitrogen use efficiency (kg grain kg-1 N), on average, improved over time but also yield-scaled nitrate load + soil nitrate was reduced by 74% and 91% from Old to Current and Future systems, respectively. Continuing these trajectories of improvement will be critical to meet the needs of a growing and more affluent population while reducing deleterious effects of agricultural systems on ecosystem services.

Transcription factors WOX11 and LBD16 function with histone demethylase JMJ706 to control crown root development in rice.

Crown roots are the main components of root systems in cereals. Elucidating the mechanisms of crown root formation is instrumental for improving nutrient absorption, stress tolerance, and yield in cereal crops. Several members of the WUSCHEL-related homeobox (WOX) and lateral organ boundaries domain (LBD) transcription factor families play essential roles in controlling crown root development in rice (Oryza sativa). However, the functional relationships among these transcription factors in regulating genes involved in crown root development remain unclear. Here, we identified LBD16 as an additional regulator of rice crown root development. We showed that LBD16 is a direct downstream target of WOX11, a key crown root development regulator in rice. Our results indicated that WOX11 enhances LBD16 transcription by binding to its promoter and recruiting its interaction partner JMJ706, a demethylase that removes histone H3 lysine 9 dimethylation (H3K9me2) from the LBD16 locus. In addition, we established that LBD16 interacts with WOX11, thereby impairing JMJ706-WOX11 complex formation and repressing its own transcriptional activity. Together, our results reveal a feedback system regulating genes that orchestrate crown root development in rice, in which LBD16 acts as a molecular rheostat.

Decoding the gene regulatory network of endosperm differentiation in maize

The persistent cereal endosperm constitutes the majority of the grain volume. Dissecting the gene regulatory network underlying cereal endosperm development will facilitate yield and quality improvement of cereal crops. Here, we use single-cell transcriptomics to analyze the developing maize (Zea mays) endosperm during cell differentiation. After obtaining transcriptomic data from 17,022 single cells, we identify 12 cell clusters corresponding to five endosperm cell types and revealing complex transcriptional heterogeneity. We delineate the temporal gene-expression pattern from 6 to 7 days after pollination. We profile the genomic DNA-binding sites of 161 transcription factors differentially expressed between cell clusters and constructed a gene regulatory network by combining the single-cell transcriptomic data with the direct DNA-binding profiles, identifying 181 regulons containing genes encoding transcription factors along with their high-confidence targets, Furthermore, we map the regulons to endosperm cell clusters, identify cell-cluster-specific essential regulators, and experimentally validated three predicted key regulators. This study provides a framework for understanding cereal endosperm development and function at single-cell resolution.

Millets for food and health security: A review

Millets are small sized cereal food crops that are mostly native to Asia, especially India. The nutritional composition of these small grained crops has earned them the name of ‘Nutri-cereals’. These belong to ‘Pseudo’ cereals and are a member of the family ‘Poaceae’. In the field, these crops can withstand conditions generated by climate change and off-field their nutritional content helps them fight hunger and other health conditions thereby providing positive effects on health. Millets are rich in both macro and micronutrients, however, their health benefits are more pronounced due to the presence of micronutrients including vitamins, minerals, antioxidants, flavonoids, and polyphenols. The present world is struggling for food. Both, growing food and feeding the population is the biggest challenge, the whole world is facing today. Adverse climatic conditions are continuously challenging the productivity and yield of cereal crops and at the same time hidden hunger, malnutrition, obesity, and other degenerative diseases are affecting a large portion of the population due to unhealthy and non-nutritious food. Millets are a suitable answer to these problems. The present review is an attempt to explore the nutritional aspects of millets which makes it a suitable food option for the world’s population. The benefits of its nutritional composition to support a normal healthy human life are also attempted to discuss health security.

Climate Change Impact on Cereal Production and Food Security in Hebron Governorate: An Analytical Approach

Cereal crop failures result from climate shocks, which are caused by the climate\'s variables fluctuation and represent a complex system of interrelated elements. This study aims to explore the effects of climate change, especially precipitation and temperature fluctuations on cereal cultivation and food security in the Hebron Governorate. By utilizing a range of statistical methods, including the autoregressive distributed lag (ARDL) bounds testing approach, and incorporating qualitative insights from local agricultural experts, this research provides a thorough analysis of climate dynamics and their potential consequences on cereal cultivation and food security. \nThe analysis results uncover a prominent causal connection between these climatic elements and agricultural production, emphasizing the negative impacts of heightened carbon levels, temperature, and unpredictable rainfall events and patterns, on cereal crop yields. Furthermore, the research highlights the intricate interrelationship between non-climatic factors like energy usage, workforce, and financial growth in influencing agricultural performance. Of course, this in turn affects the fragile food security at the Hebron governorate level.

Spatiotemporal dynamics of the foxtail millet transcriptome during grain filling

AbstractFlag leaf, stem, and grain are all important for endosperm development (grain filling) in cereal crops. However, joint analysis of these three tissues during grain filling is limited. Hence, we employed RNA‐seq to compare the transcription dynamics in flag leaf, stem, and grain at different stages during grain filling. The differentially expressed genes (DEGs) between different tissues and stages were identified. The number of DEGs was increased from stage 2 to stage 4 in leaf and grain, while the number of DEGs was decreased in the stem. Through WGCNA analysis, genes associated with photosynthesis were specifically changed in flag leaves during grain filling. Lignin and branched chain amino acid synthesis‐related genes were specifically expressed in stem and grain, respectively. The phytohormone signal transduction and sucrose‐starch conversion pathway in stem and grain together promoted the offloading of assimilates from stem to grain and the assimilate accumulation in grain. These results provide new insights for further investigations on molecular regulatory mechanisms among different tissues of grain filling, and also provide a new idea for improvement of yield and quality in cereal crops.

Investigation of the conditions for the formation of moisture deficiency in Northern Kazakhstan using the method of hydrological and climatic calculations

The article investigated the conditions for the formation of moisture deficiency in the forest-steppe and steppe zones of northern Kazakhstan. The growth of moisture deficiencies affects the yield of grain crops. The work used statistical, cartographic, analytical, and analogy methods. The hydrological and climatic calculation method developed by V.S. Mezentsev and tested in Western Siberia and adjacent territories of Kazakhstan was used as the main method for obtaining the calculated heat and water balance characteristics of the studied territory. Meteorological data obtained at meteorological stations in agricultural areas was used as initial data. Using the regression equation, the dependence of cereal crop yield on humidification in the Akmola region and the estimated yield schedule for 2024 were built. On the territory of Northern Kazakhstan, quite close dependencies between the yield and the degree of humidification have been identified. The yield of grain crops in the Akmola region was influenced by a lack of moisture for 54%. In general, during the warm period of the average year, the soil moisture resources of the studied area are not able to provide favorable conditions for the appropriate growth and development of crops.

PREDICTION SYSTEM FOR THE INFLUENCE OF PHOSPHORUS ON WHEAT YIELD: OPTIMAL HYPERPARAMETER SELECTION

Modern studies in the application of machine learning in agrotechnology have showcased significant advancements in accurate crop yield forecasting and agricultural production optimization. This study aimed to select optimal hyperparameters for a neural network designed to forecast the impact of phosphorus on the yield of spring wheat. Tasks to achieve this goal included the selection of optimal neural network hyperparameters and deployment of the prediction model into forecasting system, ensuring accessibility and user convenience. Input dataset consisted of year, region, climatic indicators (temperature of the soil surface, precipitation, humidity), applied phosphorus, and the target variable is the yield of spring wheat. To select the optimal hyperparameters, GridSearchCV was utilized and integrated into the experiment, enabling the achievement of more precise and impactful forecasting outcomes. Experiments aimed at hyperparameter tuning identified an optimal network configuration (3 layers, 32 neurons, 300 epochs, 32 batches). Results from training showcased that this network configuration achieved the best performance, demonstrating minimal mean squared error (MSE). These results introduced a novel scientific approach in training data using this neural network model for forecasting the yield of cereal crops. Developing the prediction system's interface relied on the Streamlit, allowing the creation of an intuitive and user-friendly interface. The visualization derived from this model empowers users to evaluate crop yield and receive recommendations for optimal phosphorus application to enhance spring wheat yield. These results highlighted practical significance of this prediction system, based on neural network utilizing optimal hyperparameters that are ready for practical implementation by system developers.

Non-destructive detection of fusarium head blight in wheat kernels and flour using visible near-infrared and mid-infrared spectroscopy

Fusarium head blight (FHB) is one of the most severe fungal diseases that reduces yield of cereal crops and degrades kernel quality with mycotoxins, which are harmful to human and animal health. The majority of FHB identification at post-harvest stage is through lab-based analysis, whilst effective it is a time consuming, expensive, and laborious process. Hence, a non-destructive, rapid, accurate, and robust method is required for FHB detection at post-harvest. This study explores the potential of visible near-infrared (vis-NIR) in the wavelength range from 400 to 1700 nm and the mid-infrared (MIR) in the wavenumber range from 4000 to 650 cm−1 to predict FHB infection of wheat kernels and flour. A total of 143 ear samples (93 infected, and 50 healthy) were collected from an inoculated trial covering several winter wheat varieties. The collected spectral data was analysed with two different machine learning algorithms, namely, random forest (RF) and linear discriminant analysis (LDA). Both models produced a higher test accuracy of 96.6 % and 100 %, respectively, for the flour samples than that (e.g., 93.1 %) for the kernels, using the MIR spectroscopy. Recursive feature elimination (RFE) demonstrated notable improvements in accuracy of the vis-NIR for the kernels, with LDA model providing 100 % classification accuracy. While RFE failed to improve the accuracy of MIR-LDA models. The results highlight the effectiveness of vis-NIR and MIR spectroscopy with RFE and machine learning for classifying FHB in wheat kernel and flour samples.

Role of silica nanoparticles in enhancing drought tolerance of cereal crops

Cereal crops are essential for providing essential nutrients and energy in the daily human diet. Additionally, they have a crucial role as a significant constituent of cattle feed, hence enhancing meat production. Drought, being an abiotic stressor, adversely affects the growth and yield of numerous crops on a global scale. This issue poses a significant and pressing obstacle to maintaining global cereal crop production and ensuring food security. Nanoparticles have become a valuable resource for improving cereal crop yield and productivity under ongoing rapid climate change and escalating drought conditions. Among these, silica nanoparticles (SiNPs) have demonstrated their potential for agricultural applications in regions with limited water availability. Drought stress has detrimental effects on cereal crops, impacting their growth, metabolic, and physiological processes, hampering water and nutrient absorption, disrupting cellular membranes, damaging the photosynthetic apparatus, and reducing antioxidant activities by altering gene expression. SiNPs help preserve cellular membranes, regulate water balance, and improve water and nutrient absorption, resulting in a substantial enhancement in plant growth under water-deficit conditions. SiNPs also protect the photosynthetic system and enhance its efficiency, facilitate the accumulation of phenolics, hormones, osmolytes, antioxidant activities, and gene expression, thus empowering plants with increased resistance to drought stress. Moreover, SiNPs decrease leaf water loss by promoting stomatal closure, primarily by fostering the accumulation of abscisic acid (ABA) and mitigating oxidative stress damage by activating the antioxidant defence system and reducing reactive oxygen species (ROS). However, a limited number of studies examine the role of SiNPs in cereal crops under drought stress conditions. In this review, we highlighted the promising potential of SiNPs to improve cereal crop resilience by changing morpho-histological traits, antioxidant properties, and gene expression to maintain food security in drought-prone areas. This study will aid researchers in using SiNPs as an environmentally benign way to improving drought resistance in cereal crops in order to fulfill global food supply needs.

The Role of Glutamine Synthetase (GS) and Glutamate Synthase (GOGAT) in the Improvement of Nitrogen Use Efficiency in Cereals.

Cereals are the most broadly produced crops and represent the primary source of food worldwide. Nitrogen (N) is a critical mineral nutrient for plant growth and high yield, and the quality of cereal crops greatly depends on a suitable N supply. In the last decades, a massive use of N fertilizers has been achieved in the desire to have high yields of cereal crops, leading to damaging effects for the environment, ecosystems, and human health. To ensure agricultural sustainability and the required food source, many attempts have been made towards developing cereal crops with a more effective nitrogen use efficiency (NUE). NUE depends on N uptake, utilization, and lastly, combining the capability to assimilate N into carbon skeletons and remobilize the N assimilated. The glutamine synthetase (GS)/glutamate synthase (GOGAT) cycle represents a crucial metabolic step of N assimilation, regulating crop yield. In this review, the physiological and genetic studies on GS and GOGAT of the main cereal crops will be examined, giving emphasis on their implications in NUE.