Search

This paper proposes a modeling method of maize in threshing. The static friction coefficient and rolling resistance coefficient of the maize grain were measured using the slope method. The maize grain stacking angle test was designed using the central composite design response surface test. A regression model was established based on the simulation results to find the best combination. The results suggested that the modeling method proposed in this paper was effective in improving the accuracy of maize grain simulation compared with previous methods. Furthermore, this paper presents a method to verify the feasibility and reliability of the maize grain cob discrete element model using the distribution of grain in the granary and the final removal rate as the verification method. The results of the actually simulated threshing test were analyzed using a Wilcoxon signed-rank test, heat map analysis, and the Spearman's rank correlation coefficient. It was found that the DEM model of maize cob is suitable for simulating the maize threshing process. This can aid in further research on the subject. [ABSTRACT FROM AUTHOR]

Copyright of Plants, People, Planet is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The study of yield gaps has become more complex, prompting the use of varied approaches to measure yields and a wider range of factors to explain these gaps. In the Global North, the focus is on precision farming, whereas in sub-Saharan Africa (SSA), a broader perspective is necessary due to pronounced variability in farmland conditions. While biogeophysical and management factors have been traditional focal points in yield gap analyses, socio-economic and institutional factors are increasingly recognized as significant, especially in SSA. This review synthesizes research from the past decade in SSA that integrates biogeophysical, management, farm characteristics, and institutional factors in yield gap discussions. The findings indicate a slow shift in including socio-economic factors, with management, particularly nutrient supply and crop management, remaining predominant. However, there is a growing trend towards methodological diversity, such as the adoption of remote sensing and GIS in recent years. Case studies from Kenya and Ghana, utilizing field surveys, interviews, panel data, and spatial analysis, highlight how a multifaceted approach can enhance our understanding of the various elements influencing maize yield gaps in SSA. [ABSTRACT FROM AUTHOR]

Carbon farming has become increasingly popular as it integrates agriculture, forestry, and diverse land use practices, all crucial for implementing European strategies aimed at capturing 310 million tons of carbon dioxide from the atmosphere. These farming methods were proven to reliably increase the amount of carbon stored in the soil. However, there is a lack of discussion and consensus regarding the standards used to report these values and their implications. This article analyzes carbon sequestration rates, calculation methodologies, and communication procedures, as well as potential co-benefits and best practices. The average carbon sequestration rates in major staple crops range from very low values (0–0.5 Mg/ha/yr) to medium values (1–5 Mg/ha/yr). Scientific agricultural experiments in key global staple crops demonstrate positive rates of 4.96 Mg C ha−1 yr−1 in wheat–maize rotations and 0.52–0.69 Mg C ha−1 yr−1 in rice–wheat rotations. In agriculture, carbon sequestration rates are reported using different terms that are not consistent and pose communication challenges. This assessment involves a systematic review of the scientific literature, including articles, reviews, book chapters, and conference papers indexed in Scopus from 2001 to 2022. Specifically, this review focuses on long-term experiments, meta-analyses, and reviews that report an increase in soil carbon stock. The research trends observed, through a VOSviewer 1.6.18 analysis, show a steadily increasing interest in the field of carbon sequestration. [ABSTRACT FROM AUTHOR]

Forage maize is a versatile crop extensively utilized for animal nutrition in agriculture and holds promise as a valuable resource for the production of fermentable sugars in the biorefinery sector. Within this context, the carbohydrate fraction of the lignocellulosic biomass undergoes deconstruction during ruminal digestion and the saccharification process. However, the cell wall's natural resistance towards enzymatic degradation poses a significant challenge during both processes. This so-called biomass recalcitrance is primarily attributed to the presence of lignin and ferulates in the cell walls. Consequently, maize varieties with a reduced lignin or ferulate content or an altered lignin composition can have important beneficial effects on cell wall digestibility. Considerable efforts in genetic improvement have been dedicated towards enhancing cell wall digestibility, benefiting agriculture, the biorefinery sector and the environment. In part I of this paper, we review conventional and advanced breeding methods used in the genetic improvement of maize germplasm. In part II, we zoom in on maize mutants with altered lignin for improved digestibility and biomass processing. [ABSTRACT FROM AUTHOR]

Plant density, the number of plants per unit area, is an important factor in maize production. Plant density exhibits high variability and depends on a number of factors, i.e., the length of the growing period of the hybrid, the morphological characteristics of the plant, the amount and distribution of precipitation during the growing season, the reserve of winter moisture in the soil, the level of soil fertility, the time of sowing, agronomic management practices, and biomass and yield. The objective of this paper was to determine the agronomic optimal plant density for maize in calcareous soil in the semiarid conditions of the South Pannonian Basin. Field experiments were conducted at the experimental field—IFVCNS (two locations: Rimski Šančevi and Srbobran) to evaluate four plant densities (55,000; 65,000; 75,000; and 85,000 plants ha−1). The experimental sites "Rimski Šančevi" and "Srbobran" are located in the typical chernozem zone of the southern part of the Pannonian Basin. On average for all hybrids, the grain yield followed a second-degree polynomial model in response to the increasing planting density, with the highest value at plant density (PD2: 65,000 plants ha−1). To achieve maximum yield, the optimal planting density for corn hybrids of the FAO 200 group should be 57,600 plants ha−1, for the FAO 300 group 64,300 plants ha−1, for the FAO 400 group 68,700 plants ha−1, for the FAO 500 group 66,800 plants ha−1, and for the FAO 600 group 63,500 plants ha−1. "Which–Won–Where" biplot showed that the hybrid H24 from FAO 600 group was the highest yielding in all of the environments. Hybrid H17 from the same FAO group was the most stable across all of the environments. Selected hybrids may further be studied for planting density and nutritional requirements for getting maximum yield. By introducing new maize hybrids with higher genetic yield potential and better agronomic management practices, modern mechanization and agricultural techniques allowed to increase planting densities. [ABSTRACT FROM AUTHOR]

Maize Ustilago maydis is a disease that severely affects maize yield and quality. In this paper, we employed transcriptome sequencing and GWAS analysis to identify candidate genes and reveal disease-resistant germplasm resources, thereby laying the foundation for further analysis of the molecular mechanism of maize Ustilago maydis resistance and genetic improvement. The results of transcriptome sequencing revealed that a considerable number of receptor kinase genes, signal-transduction-related protein genes, redox-response-related genes, WRKYs, and P450s genes were significantly upregulated. There was a wide range of mutations of Ustilago maydis in maize inbred lines. Thirty-two high-resistance maize inbred lines were selected, and 16 SNPs were significantly associated with the disease index. By integrating the results of GWAS and RNA-seq, five genes related to disease resistance were identified, encoding the chitinase 1 protein, fatty acid elongase (FAE), IAA9, GATA TF8, and EREB94, respectively. It provides a certain reference for the cloning of maize anti-tumor smut genes and the breeding of new varieties. [ABSTRACT FROM AUTHOR]

Land use practices face significant pressure due to increased demand and conflicting needs. Several factors contribute to this trend, such as the ever-increasing human population, the increased demand for food production, and the expansion of industrial and agricultural areas. This paper, focused on the cultivation patterns and investigating changes in land use of maize and soybean over time (i.e., both genetically modified and non-genetically modified) in two South African provinces. The objective was to determine whether there was a net increase or decrease in land cover age for these two crops between 2006 and 2017 in the selected study areas. Hence, the study utilized ArcGIS (10.8.1) software to quantify and map the land used for the cultivation of maize and soybean from 2006 to 2017 in Free State and North West provinces. The results show both provinces to have minimal expansion or change in cultivation areas for both maize and soybean between 2006 and 2017. We concluded that both maize and soybean cultivation areas in these provinces, did not expand beyond the current agricultural areas (space), and did not encroach onto new land areas. As a result, both maize and soybean do not currently pose a threat to the surrounding landscape (i.e., natural vegetation) and are not in direct competition with other neighboring land use practices. We recommend that data on the annual planting or cultivation area be consistently gathered, analyzed, and mapped to monitor any alterations that could influence the current findings. This will also assist with any land use planning and management practices. [ABSTRACT FROM AUTHOR]

Background: The root of a plant is a fundamental organ for the multisensory perception of the environment. Investigating root growth dynamics as a mean of their interaction with the environment is of key importance for improving knowledge in plant behaviour, plant biology and agriculture. To date, it is difficult to study roots movements from a dynamic perspective given that available technologies for root imaging focus mostly on static characterizations, lacking temporal and three-dimensional (3D) spatial information. This paper describes a new system based on time-lapse for the 3D reconstruction and analysis of roots growing in hydroponics. Results: The system is based on infrared stereo-cameras acquiring time-lapse images of the roots for 3D reconstruction. The acquisition protocol guarantees the root growth in complete dark while the upper part of the plant grows in normal light conditions. The system extracts the 3D trajectory of the root tip and a set of descriptive features in both the temporal and frequency domains. The system has been used on Zea mays L. (B73) during the first week of growth and shows good inter-reliability between operators with an Intra Class Correlation Coefficient (ICC) > 0.9 for all features extracted. It also showed measurement accuracy with a median difference of < 1 mm between computed and manually measured root length. Conclusions: The system and the protocol presented in this study enable accurate 3D analysis of primary root growth in hydroponics. It can serve as a valuable tool for analysing real-time root responses to environmental stimuli thus improving knowledge on the processes contributing to roots physiological and phenotypic plasticity. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Irrigation & Drainage is the property of Journal of Irrigation & Drainage Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Irrigation & Drainage is the property of Journal of Irrigation & Drainage Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Film-mulched rock outcrops are a proven way to effectively prevent preferential flow at the rock–soil interface in rocky karst areas, but the impact on rainwater redistribution and maize growth in farmland areas has never been studied. This paper used the dye tracer method at a sprinkling intensity of 1 mm min−1 to study the rainwater redistribution in soils for three different treatments: away from rock (AR), close to rock (CR), and close to film-mulched rock (CFMR). The growth situation of maize (Zea mays L.) according to the different treatments was also studied. It was shown in the study that the rainwater gathered by rock outcrops was mainly confined only within a narrow flow path at the rock–soil interface in the CR treatment, with a preferential flow fraction of 35.78~55.54% and dyeing depth of 15.37~20.00 cm across the three dye application amounts (850 mL, 1700 mL, and 3400 mL) in contrast to the uniform distribution of the rainwater in the soil of the AR treatment, with a preferential flow fraction of 12.31~37.15% and dyeing depth of 6.93~14.00 cm. Interestingly, in the CFMR treatment, there was no preferential flow at the rock–soil interface benefiting from the film's blocking action, and the redistribution of rainwater was mainly based on the matrix flow, with a preferential flow fraction of 24.93~39.62% and dyeing depth of 10.27~18.00 cm, indicating that the film-mulched rock outcrops improved the rock's output capability for gathering rainwater into the surrounding soil. In addition, film-mulched rock outcrops can promote the growth of maize, as indicated by the results for plant height, stem diameter, maximum leaf area, SPAD value, and floral development of maize, which increased in order from AR, CR, to CFMR. Our study suggests that film-mulched rock outcrops have important implications for the efficient use of rainwater and the growth of crops in rocky karst areas, as well as in regions with similar geological characteristics. [ABSTRACT FROM AUTHOR]

This paper presents the effects of organic fertilizers on the yield, quality, and fatty acid composition of maize and soybean in 2022 in Southeast Kazakhstan. Maize and soybean yields were improved by commercial organic fertilizers. In general, the yield, quality, and fatty acid (FA) parameters of both crops were influenced by various types of organic fertilizers. The application of HansePlant fertilizer allowed for an increase in the yield of maize seed by 47% and soybean by 31%. Organic fertilizers improved the quality parameters fat, protein, fiber, and starch in maize by 35%, 22%, 14%, and 8%, respectively, compared to control samples. In soybean, the parameters fat, protein, and fiber were improved by 20%, 3%, and 11%, respectively. The FA compositions of maize and soybean were analyzed via gas chromatography and with tandem mass spectrometer using a polarity column. Compared with no fertilization conditions, the omega-6/omega-3 ratio showed the lowest value in maize (22.40–123.96) and soybean (3.26–4.07). A study of the fatty acid composition groups compared with different fertilizer treatments was performed. [ABSTRACT FROM AUTHOR]

The accurate identification of corn leaf diseases is crucial for preventing disease spread and improving corn yield. Plant leaf images are often affected by factors such as complex backgrounds, climate, light, and sample data imbalance. To address these issues, we propose a lightweight convolutional neural network, ICS-ResNet, based on ResNet50. This network incorporates improved spatial and channel attention modules as well as a deep separable residual structure to enhance recognition accuracy. (1) The residual connections in the ResNet network prevent gradient loss during deep network training. (2) The improved channel attention (ICA) and spatial attention (ISA) modules fully utilize semantic information from different feature layers to accurately localize key features of the network. (3) To reduce the number of parameters and lower computational costs, we replace traditional convolutional computation with a depth-separable residual structure. (4) We also employ cosine annealing to dynamically adjust the learning rate, enhancing the network's training stability, improving model convergence, and preventing local optima. Experiments on the corn dataset in Plant Village compare the proposed ICS-ResNet with eight popular networks: CSPNet, InceptionNet_v3, EfficientNet, ShuffleNet, MobileNet, ResNet50, ResNet101 and ResNet152. The results show that the ICS-ResNet achieves an accuracy of 98.87%, which is 5.03%, 3.18%, 1.13%, 1.81%, 1.13%, 0.68%, 0.44% and 0.60% higher than the other networks, respectively. Furthermore, the number of parameters and computations are reduced by 69.21% and 54.88%, respectively, compared to the original ResNet50 network, significantly improving the efficiency of corn leaf disease classification. The study provides strong technical support for sustainable agriculture and the promotion of agricultural science and technology innovation. [ABSTRACT FROM AUTHOR]

To explore the application of seed germination biomechanical event(s) in seed vigour tests, a new procedure for the evaluation of maize seed vigour tests based on pericarp–testa rupture (PR) and coleorhiza rupture (CR) during seed germination was developed. Twenty–four lots of hybrid maize were used to determine the feasibility of the rupture test (RT) as a seed vigour test in Zea mays. The results showed that the physiological quality pattern of 24 maize seed lots assessed through RT was similar to that obtained through analysis with other seed test methods. Correlation and regression analyses revealed that the percentage of CR and percentage of PR + CR at "15 ± 0.5 °C for 120 h ± 1 h" and "20 ± 0.5 °C for 72 h ± 15 min" exhibited positive correlations with the field seedling emergence data (p < 0.01). Hence, the proposed method (the rupture test) is cogent and effective, thus providing an important reference for more crops to select for seed germination event(s) and establishing corresponding new methods for seed vigour tests in the future. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Central European Agriculture is the property of Journal of Central European Agriculture and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Central European Agriculture is the property of Journal of Central European Agriculture and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Since joining the North American Free Trade Agreement, Mexico has increased its meat production and exports and become more dependent on imported feedstuffs such as genetically engineered (GE) corn. Mexico recently banned the use of GE corn in corn‐based foods and called for a gradual substitution away from the use of GE corn for other uses (e.g., feed). This paper considers how a complete ban on GE corn might affect Mexican households using a computable general equilibrium (CGE) model to simulate the impact over the medium run (5 years). Results indicate that Mexico decreases corn imports by 76.9% and increases corn production by 65.6%—an increase that would require 3.3 million hectares more land for corn. The policy leads to a 24.8% increase in Mexico's corn price and up to a 6% increase in the prices of other agricultural products. But Mexico might have difficulty shifting land to corn; as such, we consider an alternative scenario that restricts land movements. We find that impacts are further exacerbated in this scenario—for example, corn prices triple. Our final contribution is to pair these results with a compensating variation calculation based on the almost ideal demand system. We find that Mexican households would need to spend, on average, between 6.7 and 13.9% more on food, depending on the scenario, to compensate for the resulting price escalations. Ultimately, our results show that a move toward greater food sovereignty in Mexico is ultimately borne by consumers via higher food prices. [ABSTRACT FROM AUTHOR]

Introduction and Objective: Maize (Zea mays L.) is the third most important cereal after wheat and rice, which accounts for 26% of total cereal cultivated area and 37% of their production. Maize is a valuable raw material for extracting oil, starch, alcohol, glucose, plastic, lactic acid, acetic acid, acetone and paint, and it is possible to made paper, cardboard, and nitrocellulose from its stalks. As an important nutrient, phosphorus plays important role in energy transfer, photosynthetic oxidation-reduction reactions, as well as in biochemical compounds including nucleic acids, structural proteins, enzymes, and signal transmission. Due to the predominance of calcareous soils with high pH in arid and semi-arid agricultural climates, the amount of available phosphorus is limited. In order to increase available phosphorus for plants, large amounts of phosphorus chemical fertilizers are needed regularly. However, a large amount of phosphorus in fertilizers may be converted to insoluble phosphate, immediately by reaction with calcium in the soil after its application. On the other hand, indiscriminate use of phosphorus chemical fertilizers leads to many environmental problems such as surface runoff of phosphorus, eutrophication of aquatic ecosystems, reduction of biodiversity and abnormal changes in soil salt concentration and pH. Breeding cultivars that absorb phosphate or phosphorus more efficiently is one of the solutions to deal with the stress of phosphorus deficiency as a trait with low heredity. The use of selection indices can be an effective method for the indirect selection of traits with complex genetics. Material and Methods: 93 maize genotypes prepared from different research centers were evaluated in terms of agromorphological traits under normal and phosphorus deficit conditions using completely randomized design with three replications in the crop year 2016-2017 in an open area conditions. For this purpose, after analyzing the soil of different regions, soil with low phosphorus content (7.240 mg/kg) was selected and the pots (15 kg) were filled with soil and sand in a ratio of two to one. Usable soil phosphorus was determined by the Olsen method in the soil science laboratory of Urmia University. In both optimal and phosphorus deficit conditions, soil was strengthened with nitrogen fertilizers (in the amount of 9 g/pot (during three stages during the growth period)), potassium sulfate (in the amount of 13.5 g/pot), Sequestrin (1.5 g /pot), manganese sulfate (0.225 g/pot), zinc sulfate (0.99 g/pot), copper sulfate (0.3 g/pot) and boric acid (0.21 g/pot). In optimal conditions, phosphorus fertilizer in the form of triple superphosphate was added to each pot in the amount of 6 g/pot. Phosphorous fertilizer was not added to the soil in the phosphorus deficit conditions. With the beginning of the tasseling stage, various agro-morphological and chemical traits were measured. In the physiological maturity stage, the ears relating to each replication were separated from the plants. Seed yield per plant was determined by separating the seeds on the ears of each plant and weighing it. In order to select the desired genotypes, four selection indexes including Smith-Hazel, Pesek-Baker, Brim and Robinson indices were calculated. In this study, the same weight was considered for the attributes, which is done in this way in most studies. To select the best selection index, different criteria, including the genetic gain of traits (ΔG), expected gain (ΔH) and relative efficiency of selection index (RE) were calculated. Results: According to analysis of variance results, the effect of genotype and stress was significant on all studied traits at the probability level of 1%. Also, the interaction effect of genotype × stress was significant on all studied traits except for flag leaf length (FLL), flag leaf width (FLW), number of leaves (NL), plant height (PH), stem diameter (SD), ear length (EL), number of rows per ear (RpE), number of grain per row (GpR), ear diameter (ED) and 100 seeds weight (HGW). In the normal conditions (without stress) in the Smith-Hazel index (optimal index), the highest coefficient (7.21 and 3.98) was observed in FLW and ear length (EL) traits, respectively, and the lowest ones (-3.03) was observed in RpE trait. In the phosphorus deficit conditions, the highest coefficient (3.91) was observed in EL and the lowest ones (-5.35) was observed in RpE trait. In the Pesak-Baker index, under normal conditions, the highest coefficient (5.64) was observed in GpR trait and the lowest ones (-9.28) was observed in EL. In phosphorus deficit conditions, the highest coefficient (8.49) was seen in FLW trait, followed by EL (4.53) and the lowest ones (-2.17) was observed in RpE. The highest coefficient in Robinson's index under normal conditions was 2.21 for LW, which was -5.91 for that under phosphorus deficit conditions. In this index, the lowest coefficient was seen in RpE (-0.92). In Robinson's index, under phosphorus deficit conditions, the highest coefficient (1.46) was seen in EL, and the lowest ones (-5.92) was seen in FLW, followed by RpE with a value of -2.13. The Smith-Hazel index with expected gain (ΔH) value of 296.306 and 229.374, and relative efficiency of (RE) of 1.0011 and 1.0839 and the Brim with expected gain (ΔH) value of 296.217 and 233.083, and relative efficiency of selection index (RE) of 0.9995 and 1.0836, in normal and phosphorus deficit conditions, respectively, were the best indices. Under both normal and phosphorus deficit conditions, biomass yield, seed yield, and plant height had the highest coefficients for these indices. Based on both indices, genotype with cod number 7 and the genotype with cod number 10 are introduced as superior genotypes under normal and phosphorus deficient conditions, respectively. Conclusion: In general, the results of present investigation showed that in both normal and phosphorus deficit conditions, selection based on the Smith-Hazel and Brim indices will increase the biomass yield, seed yield and plant height due to their highest relative efficiency and expected gain. The selected genotypes after validation at the molecular level with different technologies, such as studying the expression of genes involved in tolerance to phosphorus deficit conditions using Real time PCR, can be used in the production of hybrid varieties as a way to reduce the use of phosphorus fertilizers. [ABSTRACT FROM AUTHOR]

A simple experiment was carried out at three neighboring micro-farms where the owners agreed to implement some proposed technologies in which the influence of differentially applied agricultural works and the influence of some inputs on corn production will be tested. The micro-farms are located in the South-West part of Olt county in the vicinity of Dolj county. Conventional works and minimum tillage were executed. For the conventional works, the farmers continued to use their knowledge of corn cultivation. For the proposed technologies, they received nitrogen 70 kg ha-1, phosphorus 90 kg ha-1 and NPK 8.15.15 + 3%CaO+ 9%S 200 kg ha-1. In the short run, it has been observed that employing minimum tillage alongside soil fertility management technologies proves more beneficial in boosting maize yield under conditions of limited rainfall compared to conventional tillage methods. [ABSTRACT FROM AUTHOR]

Earhead worm Autoba silicula (Swinhoe, 1897) (Lepidoptera: Erebidae) is recorded for the first time in India on maize. Larvae were found feeding on maturing grains and silk, fully fed matured larvae pupates under a dome shaped or elongated galleries made of silk inside the cob. Roving survey conducted during 2019 and 2020 recorded on an average 0.40 and 0.45 larvae per plant, respectively, which is below the economic threshold. In the present study, information on species diagnosis with illustrations, occurrence, nature and symptoms of damage are provided. [ABSTRACT FROM AUTHOR]

This study aimed at alleviating the problems of unsatisfactory inversion accuracy and weak model stability in LAI remote sensing quantitative inversion. The properties and complex scattering mechanism of SAR data specify the polarization combinations and frequencies. This paper proposes an improved water cloud model combined with a deep neural network (MWCMLAI-Net) for high-precision inversion. The polarized GF-3 (C-band) and Lutan (L-band) were used to investigate the potential of SAR images to estimate LAI, a strong indicator of crop productivity. The study selected xiangfu district in the eastern part of Kaifeng City, Henan Province, as the test area and investigated the LAI of maize and rice. The RVIFreeman Model, backward scattering coefficient extracted by the modified cloud and water model (MWCM), and LAI obtained by the inversion of the MWCM were used as the inputs, and the MWCMLAI-Net inversion of the LAI was constructed. The results showed that the model's inverted LAI fitting accuracies of maize and rice for the three fertility periods were better than the other models, with R² above 0.8516 and RMSE below 0.3999 m²/m². The addition of noise did not affect the results. [ABSTRACT FROM AUTHOR]

Introduction Agriculture is the largest consumer of fresh water in the whole world. Currently, almost 11% of the Earth’s total land surface is arable, which is expected to reach 13% by 2050. Roughly 17% of these lands are subject to modern form of irrigation management, which constitutes about 30-40% of the gross agricultural output. Reducing water consumption and increase water productivity in agriculture, requires a correct understanding of the biological response of crop to water. The ever-increasing growth of the population and the limitation of fresh water resources have led irrigation experts to new and efficient approaches in making decision to increase water productivity. The lack of scheduling in irrigation or their incompatibility with weather conditions, soil, irrigation system, agricultural restrictions and different phenological stages of crop, has caused severe losses in irrigated fields. Crop modeling and field data measurement can help irrigation experts improve irrigation scheduling in field and reduce water losses. Coupling in-situ measurement and crop modeling during the growing season is one of the useful solutions to improve irrigation scheduling in different farm conditions. In this paper, AquaCrop was calibrated for maize (Zea mays L.) in research farm of Ferdowsi University of Mashhad with comprehensive dataset. Variations of soil water content at different depths and also different growth indices was monitored during one growing season. The main novelty of this research is the targeted use of AquaCrop software to reduce water consumption by knowing the phenologically sensitive stages. Materials and Methods In-situ and in-lab measurements along with plant modeling, have been the two main parts of this research. First, the input files of the AquaCrop software were prepared and calibrated for maize during one growing season. The outputs of software including variations of moisture, biomass produced during the growing season and final yield were compared with the values measured in the field. After ensuring the accuracy of calibrated software, an improved irrigation scheduling was investigated. Subsequently, by means of crop modeling, the sensitive intervals of the crop to soil water stress as well as the thresholds of yield reduction in different stages of growing season were determined with the aim of improving irrigation scheduling in maize field. Biomass reduction, dry yield production, and the changes in water use efficiency during the growing season were investigated according to different amounts of moisture reduction in root zone, and irrigation scheduling was fulfilled by applying stress to less sensitive stages. The software was first run in Net Irrigation Requirement mode. Then, different amounts of drought stress were applied to each of the growth stages of the crop, and the other stages were kept constant in non-stressed condition. Dry yield and biomass reduction as well as water productivity changes were obtained for each stage. According to the threshold values and the amount of yield reduction at each stage, it is possible to fine-tune the time and amount of applying stress to crop. Furthermore, according to the moisture profile of the root zone, the drained water was significantly reduced in field. In this research, in order to increase accuracy in moisture measurement and prevent errors, an equation was developed to convert the mV output of sensor to volumetric moisture. At each moisture measurement, the PR2 sensor reports a number in mV for each depth, which is converted to volumetric moisture using device's conversion equation. This equation can vary according to field and soil condition. To develop the conversion equation, six same pots with a height of 40 cm and diameter of 30 cm were filled with the desired field soil, and the access tubes were placed horizontally inside them. The soil inside these pots was completely saturated and exposed to air for drying. During the drying period of the pots, the soil moisture was measured regularly using PR2 sensor and at the same time by weight method. After these measurements, calibration curves for PR2 sensor were obtained using the alpha mixing method for different depths. Results and Discussion The Pearson correlation coefficient for measured and simulated moisture by software, was 0.84 and the root mean square error was 12 mm. Also, the value of Pearson correlation coefficient for measured and simulated values of biomass was equal to 0.99 and mean square root of error was 1.3 ton/ha. The results showed that the vegetative stage of crop was sensitive to drought stress and caused a significant yield reduction at the end of the growing season. The stage of germination and flowering were less sensitive, such that the decrease of moisture up to 12.3% compared to the Net Irrigation Requirement mode would not change the final yield of the crop. The improvement made in the field resulted in no change in the amount of biomass and dry yield (0.38% increase in biomass and 0.52% increase in dry yield), at the same time 26.6% decrease in depth of irrigation water, 85.6% decrease In drainage and increasing the efficiency of evapotranspirated water, it has increased from 4.66% to 4.67% kg/m3 compared to condition before modify. Before modify, the farm was managed in traditional way. Conclusion More research in the field of irrigation scheduling and providing comprehensive instructions to farmers in different weather conditions and different irrigation systems, taking into account different management approaches in allocating water to different parts of the farm along with investigating the effects of saline water irrigation, can be topics for the next research should be for experts in this field. [ABSTRACT FROM AUTHOR]

This paper proposes a modeling method of maize in threshing. The static friction coefficient and rolling resistance coefficient of the maize grain were measured using the slope method. The maize grain stacking angle test was designed using the central composite design response surface test. A regression model was established based on the simulation results to find the best combination. The results suggested that the modeling method proposed in this paper was effective in improving the accuracy of maize grain simulation compared with previous methods. Furthermore, this paper presents a method to verify the feasibility and reliability of the maize grain cob discrete element model using the distribution of grain in the granary and the final removal rate as the verification method. The results of the actually simulated threshing test were analyzed using a Wilcoxon signed-rank test, heat map analysis, and the Spearman’s rank correlation coefficient. It was found that the DEM model of maize cob is suitable for simulating the maize threshing process. This can aid in further research on the subject.

In January 2021, the new Horizon 2020 project “Promoting SMART agricultural WATER management in Bosnia and Herzegovina” (SMARTWATER) was launched. It was the first time that an academic institution from Bosnia and Herzegovina implemented a Horizon 2020 project as Coordinator. The main objective of SMARTWATER is to reinforce networking, research and S&T cooperation capacities of the University of Banja Luka (UNI-BL), the University of Sarajevo (UNSA) and other connected national institutions, in the field of sustainable agricultural water management and to increase their competency and fund-raising skills for a successful participation in the European Union Research Programs. Main project topics include: 1) cloud-based smart technologies, 2) new generation of satellite remote sensing data, 3) water-energy-food nexus and 4) climate change impact on agriculture. At two locations in BiH (Aleksandrovac and Butmir) 3-year field experiments on maize (Zea mays L.), hybrid BL 43 (from FAO 400 group) were completed. The Randomized Complete Block design included two factors, irrigation (3 irrigation regimes) and fertilization (2 nitrogen levels). During the project implementation, our scientific teams published several academic papers in peer-reviewed international Journals and Proceedings and these documents are available in open access on Zenodo platform [1]. The project consortium is preparing additional scientific papers. The project outputs are: 3 advanced training courses, 3 summer schools, joint research activities (experiments) at 2 locations in BiH, 3 stakeholders’ meetings (roundtables), 3 post-graduate MSc courses, 13 mutual staff exchanges, 3 hands-on workshops on R&I, the development of 2 smart water management tools and the organization of an international conference in BiH at the end of the project. So far (period 2021-2023) most of these activities were finished. All project reports were prepared and sent to the EC. All info about the project is being disseminated, on a regular basis, and for this purpose social media profiles were used: Facebook, Twitter/X, LinkedIn and YouTube as well as the SMARTWATER website [2]. The dissemination of SMARTWATER achievements is an ongoing process. SMARTWATER project officially ends in June 2024. The remaining activities in 2024 include the organization of academic exchanges in Portugal and Italy, the 3rd stakeholders' meeting, the completion of the scientific publishing and the organization of an international conference in Trebinje (BiH) in May. We ask all interested stakeholders to visit our sites, to attend our events and to join the SMARTWATER network. [ABSTRACT FROM AUTHOR]

BACKGROUND AND OBJECTIVES: To meet the needs of the global population (9.7 billion people) until 2050, a 45 percent increase in corn production is required. Efforts to enhance corn production may be informed, among others, by precise nitrogen management. The objective of this study is to investigate nitrogen dynamics and accurate nitrogen nutrient management in corn farming through the utilization of a leaf chlorophyll meter and nitrogen response assessments in order to forecast corn yield in tropical upland acid soils. METHODS: The current study was conducted in an Ultisol and verified in an Oxisol. The trial was arranged in a randomized completely block design with eight treatments: 0, 45, 90, 135, 180, 225, 270, and 315 kilograms of nitrogen per hectare, repeated three times. The chlorophyll content of corn leaves was measured at 45 and 60 days after planting, using a chlorophyll meter. An analysis was conducted on the vegetative growth and yield, along with the nitrogen content in the soil, leaf, and grains. FINDINGS: The study found that the application of nitrogen fertilizer at the rate of 180 kilograms per hectare can alter nitrate concentrations in soil and significantly increase nitrogen uptake, growth, and corn yield. The nitrogen fertilizer application reached its peak at 274.5 kilograms per hectare, resulting in chlorophyll meter readings of 52.8 and a corn yield of 8.58 tons per hectare. The corn yield at the rate of maximum nitrogen fertilizer (8.58 tons per hectare) was not significantly different from that at the rate of 180 kilogrammes nitrogen per hectare (8.54 tons per hectare). A robust relationship was observed between corn yields and chlorophyll meter values, exhibiting a correlation coefficient 0.92. CONCLUSION: The study revealed that applying nitrogen fertilizer at the medium rate of 180 kilograms per hectare can increase in nitrogen uptake, growth, and corn yield on tropical upland acid soils. The corn yield did not show a notable variance between the nitrogen fertilization rate of 180 kilograms per hectare and the highest rate of 274.5 kilograms per hectare. In terms of sustainable agriculture management, the medium rate of 180 kilograms of nitrogen is recommended for maximizing crop yield on the upland acid soils and minimizing potential environmental impacts associated with the excessive use of fertilizers. A significant relationship exists between leaf chlorophyll meter measurements and corn yield, indicating that the chlorophyll meter can be utilized as a dependable instrument in the research area for establishing the most effective fertilizer levels. [ABSTRACT FROM AUTHOR]

Sustainable irrigation water management is achievable only when irrigation scheduling is optimized to conserve water and soil resources in an agricultural setting. This study evaluated the use of remote sensing–based algorithms for determining actual crop evapotranspiration (ETa) mapping to update crop coefficients (kc) of an irrigation scheduler software (WISE). The scheduler's kc values are based on the FAO-56 approach for crop evapotranspiration (ETc) determination. A surface-irrigated (furrow) maize (Zea mays L.) field in Fort Collins, Colorado, was used from July to September 2020 and 2021. An eddy covariance energy balance system (ECSEBS) installed on a tower at 3.5 m above the ground surface was used to determine hourly and daily maize ETa data. These EC-based ETa data were used to evaluate the performance of three approaches for maize ETa estimation and the FAO-56–based ETc predictions from WISE. Microsatellite PlanetScope multispectral imagery, at a 3-m-pixel spatial resolution, provided surface reflectance in the red and near-infrared bands for input in the remote sensing of ETa algorithms. On-site micrometeorological data were measured at the exact location of the ECSEBS tower. Optimization of kc values was done using an ordinary least-squares regression approach. The optimized kc values were calculated for the maize midseason growth stage. Results indicated that using remote sensing of ETa algorithms has excellent potential to improve irrigation scheduling by integrating optimized crop coefficients. WISE overestimated daily maize ETc predictions by as much as 26%. When remote sensing-based optimized kc values were introduced, the overestimation of daily maize ETc was reduced significantly, by 18% to 75%, depending on the remote sensing of the ETa algorithm used. The research findings support the combined use of remote sensing data and the FAO-56 approach for irrigation scheduling to improve agricultural water management at the farm level. [ABSTRACT FROM AUTHOR]

A fundamental assumption in plant science posits that leaf air spaces remain vapor saturated, leading to the predominant view that stomata alone control leaf water loss. This concept has been pivotal in photosynthesis and water-use efficiency research. However, recent evidence has refuted this longstanding assumption by providing evidence of unsaturation in the leaf air space of C3 plants under relatively mild vapor pressure deficit (VPD) stress. This phenomenon represents a nonstomatal mechanism restricting water loss from the mesophyll. The potential ubiquity and physiological implications of this phenomenon, its driving mechanisms in different plant species and habitats, and its interaction with other ecological adaptations have. In this context, C4 plants spark particular interest for their importance as crops, bundle sheath cells' unique anatomical characteristics and specialized functions, and notably higher water-use efficiency relative to C3 plants. Here, we confirm reduced relative humidities in the substomatal cavity of the C4 plants maize, sorghum, and proso millet down to 80% under mild VPD stress. We demonstrate the critical role of nonstomatal control in these plants, indicating that the role of the CO2 concentration mechanism in CO2 management at a high VPD may have been overestimated. Our findings offer a mechanistic reconciliation between discrepancies in CO2 and VPD responses reported in C4 species. They also reveal that nonstomatal control is integral to maintaining an advantageous microclimate of relatively higher CO2 concentrations in the mesophyll air space of C4 plants for carbon fixation, proving vital when these plants face VPD stress. [ABSTRACT FROM AUTHOR]

Heavy metal contamination and potential risks to human health related to consuming major food crops near Iringa Municipal dumpsite are presented. Soil samples, maize (Zea mays L.) and common beans (Phaseolus vulgaris L.) were collected downslope around the dumpsite during wet season. Soil samples were analyzed using Energy-Dispersive X-Ray Fluorescence (EDXRF) while crop (maize and beans) samples were analyzed using Flame Atomic Absorption Spectrophotometer (FAAS). The potential health risks associated with human exposure to heavy metals in maize and common beans was evaluated according to the method prescribed by the United States Environmental Protection Agency. The concentrations Cd (3.25–10.78 mg/kg), As (1.84–10.98 mg/kg) and Ni (71.74–55.10 mg/kg) in soil samples exceed the maximum allowable limits set by Tanzania Bureau of Standards (TBS). The average heavy metal concentration in food crops followed the trend Cd, As < Cr, Pb < Ni < Cu < Mn < Zn with Pb in maize (0.96 mg/kg) and common beans (0.81 mg/kg) above FAO/WHO regulatory standards of 0.3 mg/kg. This implied health concerns to consuming food crops grown in the vicinity of the dumpsite. Further, lifetime–incremental cancer risk (ILCR) assessment suggest that consuming maize and common beans from the study area could increase the risk of both cancer and non-cancerous diseases in both adults and children. However, the degree of ILCR in children was noticeably higher (1.0 × 10–2) than in adults (5.10. × 10–6) for Pb in common beans. Therefore sustainable waste management should be stressed and continuous monitoring of environments around dumpsites is crucial to mitigate the negative impacts on public and environments. [ABSTRACT FROM AUTHOR]

Plant-growth-promoting rhizobacteria (PGPR), in addition to their well-known direct effects on plant growth and development, have been reported to be effective in plant abiotic (trace metal, drought, etc.) and biotic (phytopathogens, insects, etc.) stress management. PGPRs are involved in shaping the fate of trace metals in the rhizosphere and plants and thus may also reduce trace metal stress in plants. The aims of our study were to isolate and select indigenous trace-metal-resistant PGP strains and investigate their effects on maize germination and early development. The roles of the two selected strains, Pseudomonas koreensis and Serratia liquefaciens isolated from trace-metal-contaminated soil were investigated to mitigate trace metal stress in 21-day-old Zea mays seedlings. In the present study, 13 bacterial strains were isolated and screened for PGP traits under normal and trace metal stress conditions. The effect of two selected strains was further studied on plant experiments. The germination process, plant growth parameters (length, weight, dry matter content), photosynthetic activity, GPOX activity, trace metal accumulation, and translocation in microbes inoculated Cd (0.5 mM), Zn (1 mM), and Cd + Zn (0.1 + 0.5 mM) treated maize plants was studied. Our results revealed that trace metal toxicity, in terms germination and growth parameters and antioxidant enzyme activity, was enhanced upon inoculation with Pseudomonas koreensis BB2.A.1. Chlorophyll content and accumulation studies showed enhanced results following inoculation with Serratia liquefaciens BB2.1.1. Therefore, both bacterial strains possessed beneficial traits that enabled them to reduce metal toxicity in maize. [ABSTRACT FROM AUTHOR]

Root system architecture is pivotal for the acquisition of water and nutrients in maize, serving as an essential foundation for achieving high and stable yields. Identification of the genetic components and natural variations determining root traits may facilitate molecular breeding of maize varieties with better root traits. Melatonin plays an important role in plant physiology and development. In this study, nine melatonin biosynthesis genes were re-sequenced in 348 inbred lines, 68 landraces, and 32 teosintes to investigate variations related to maize root traits. The analysis of nucleotide diversity suggested that these genes may have undergone selection, particularly within their promoter regions. Marker–trait association analysis identified 26 variants significantly associated with six root traits. Five variations within the ZmTDC4 promoter were significantly correlated with both total root length (TRL) and lateral root length (LRL). Among these, SNP-1784 explained the most phenotypic variation of root traits, including TRL and LRL, that has undergone selection throughout maize domestication and improvement. Furthermore, knockout of ZmTDC4 in maize resulted in a pronounced reduction in root length, underscoring its critical role in root development. Collectively, these findings elucidate the role of melatonin synthesis genes in root development and identified favorable alleles, thus providing key loci for breeding maize varieties with superior root systems. [ABSTRACT FROM AUTHOR]

The objective of this study is to assess the suitability of the AquaCrop model for growing maize using brackish water irrigation in Northwest China. Additionally, this study aims to examine how maize utilizes water in various soil layers when irrigated with varying water qualities. The AquaCrop model was calibrated and verified using experimental data from the years 2022 and 2023 in this research. (1) The findings indicated that the AquaCrop model effectively simulated the canopy cover, biomass, and yield of maize when irrigated with brackish water. The validation year's R2, MAPE, and RMSE values for canopy cover, biomass, and yield of maize were 0.95, 5.36%, and 4.77%, respectively. For biomass, the R2, MAPE, and RMSE values were 0.91, 16.61%, and 2.12 t·hm−2, respectively. For yield, the R2, MAPE, and RMSE values were 0.84, 3.62%, and 0.42 t·hm−2, respectively. (2) Irrigation with water of high mineral content, measured at 1.6 ds/m, as well as with fresh water over the whole reproductive period, resulted in an increased reliance on groundwater for maize cultivation. There was no notable disparity in the usage of various soil layers between the irrigation with alternating freshwater and brackish water. (3) The AquaCrop model simulated the effects of seven different irrigation water quality treatments. It was shown that using water with mineralization levels of 0.5 and 0.8 ds/m resulted in decreased freshwater use without causing a substantial decrease in maize yield and biomass. [ABSTRACT FROM AUTHOR]

DnaJ proteins, also known as HSP40s, play a key role in plant growth and development, and response to environmental stress. However, little comprehensive research has been conducted on the DnaJ gene family in maize. Here, we identify 91 ZmDnaJ genes from maize, which are likely distributed in the chloroplast, nucleus, and cytoplasm. Our analysis revealed that ZmDnaJs were classified into three types, with conserved protein motifs and gene structures within the same type, particularly among members of the same subfamily. Gene duplication events have likely contributed to the expansion of the ZmDnaJ family in maize. Analysis of cis-regulatory elements in ZmDnaJ promoters suggested involvement in stress responses, growth and development, and phytohormone sensitivity in maize. Specifically, four cis-acting regulatory elements associated with stress responses and phytohormone regulation indicated a role in adaptation. RNA-seq analysis showed constitutive expression of most ZmDnaJ genes, some specifically in pollen and endosperm. More importantly, certain genes also responded to salt, heat, and cold stresses, indicating potential interaction between stress regulatory networks. Furthermore, early responses to heat stress varied among five inbred lines, with upregulation of almost tested ZmDnaJ genes in B73 and B104 after 6 h, and fewer genes upregulated in QB1314, MD108, and Zheng58. After 72 h, most ZmDnaJ genes in the heat-sensitive inbred lines (B73 and B104) returned to normal levels, while many genes, including ZmDnaJ55, 79, 88, 90, and 91, remained upregulated in the heat-tolerant inbred lines (QB1314, MD108, and Zheng58) suggesting a synergistic function for prolonged protection against heat stress. In conclusion, our study provides a comprehensive analysis of the ZmDnaJ family in maize and demonstrates a correlation between heat stress tolerance and the regulation of gene expression within this family. These offer a theoretical basis for future functional validation of these genes. [ABSTRACT FROM AUTHOR]

The Fall armyworm (FAW), Spodoptera frugiperda (J. E. Smith), is a highly destructive lepidopteran pest known for its extensive feeding on maize (Zea mays L.) and other crops, resulting in a substantial reduction in crop yields. Understanding the metabolic response of maize to FAW infestation is essential for effective pest management and crop protection. Metabolomics, a powerful analytical tool, provides insights into the dynamic changes in maize's metabolic profile in response to FAW infestation. This review synthesizes recent advancements in metabolomics research focused on elucidating maize's metabolic responses to FAW and other lepidopteran pests. It discusses the methodologies used in metabolomics studies and highlights significant findings related to the identification of specific metabolites involved in FAW defense mechanisms. Additionally, it explores the roles of various metabolites, including phytohormones, secondary metabolites, and signaling molecules, in mediating plant–FAW interactions. The review also examines potential applications of metabolomics data in developing innovative strategies for integrated pest management and breeding maize cultivars resistant to FAW by identifying key metabolites and associated metabolic pathways involved in plant–FAW interactions. To ensure global food security and maximize the potential of using metabolomics in enhancing maize resistance to FAW infestation, further research integrating metabolomics with other omics techniques and field studies is necessary. [ABSTRACT FROM AUTHOR]

All major ear rots (F. graminearum, F. verticillioides, and Aspergillus flavus) and their toxins are present in maize of preharvest origin in Hungary. Resistance can be an important tool in reducing the infection and toxin contamination from these rots in maize. Previous results identified resistance differences in maize hybrids that were suitable for use in evaluating their risk from toxigenic fungi and their toxins. During the tests, two methodical improvements were achieved: the use of three isolates of the fungus secured and a more precise estimation of resistance to ear rots and their resistance to toxin accumulation or overproduction. The improvement in sampling and the tests of subsamples made the evaluation for the statistics much more exact. This way, we were able to reduce the Within value, providing a statistically more reliable method of evaluation. Earlier data had confirmed that toxin contamination could not be predicted well from visual ear rot severity data. Contradictory results for hybrid ranking were often identified between isolates. The resistance to disease and toxin contamination is not generally valid. The new suggested methodology compares the performance of hybrids in a large number of epidemic situations to identify adaptable hybrids that can respond to diverse conditions; therefore, the stability of resistance and toxin response is decisive information to evaluate risk analyses. The increased number of disease toxin data allowed for lower LSD 5% values for toxins, a much finer analysis of toxin overproduction and underproduction, and a wider database for stability analyses. This way, we obtained important additional separated information about resistance to accumulation of toxins and about maize resistance to these pathogens that is suitable to provide much more reliable testing than was possible until now. Globally, about 50–100 million metric tons can be saved by excluding susceptible hybrids from commercial production. [ABSTRACT FROM AUTHOR]

Agricultural waste is underutilized, and sometimes burning them has a negative impact on the environment and human health. This research investigates the untapped potential of extracts from maize, wheat and sunflower waste as natural materials for cutaneous, specifically, cosmetic application. The possibility of incorporating lipid and ethanol extracts from wheat, maize, and sunflower into creams was investigated together with their potential contribution to the structural and functional properties of the topical formulations. Results of the physicochemical characterization show that investigated extracts can be successfully incorporated into creams with satisfactory stability. All extracts showed a desirable safety profile and good antimicrobial activity against various microorganisms. Lipid extracts have proven to be promising structural ingredients of the oil phase, contributing to the spreadability, occlusivity, and emollient effect. Ethanol extracts influenced washability and stickiness of the formulation and could be considered as prospective ingredients in self-preserving formulations. The extracts affected the sensory properties of the creams, mainly the smell and color. These results suggest that the extracts from wheat, maize, and sunflower waste could be used as multifunctional natural ingredients for cosmetic formulations which can replace less sustainable raw materials. This also represents a valorization of waste and is in line with broader sustainability goals. [ABSTRACT FROM AUTHOR]

Summary: Seed vigour, including rapid, uniform germination and robust seedling establishment under various field conditions, is becoming an increasingly essential agronomic trait for achieving high yield in crops. However, little is known about this important seed quality trait. In this study, we performed a genome‐wide association study to identify a key transcription factor ZmRap2.7, which regulates seed vigour through transcriptionally repressing expressions of three ABA signalling genes ZmPYL3, ZmPP2C and ZmABI5 and two phosphatidylethanolamine‐binding genes ZCN9 and ZCN10. In addition, ZCN9 and ZCN10 proteins could interact with ZmPYL3, ZmPP2C and ZmABI5 proteins, and loss‐of‐function of ZmRap2.7 and overexpression of ZCN9 and ZCN10 reduced ABA sensitivity and seed vigour, suggesting a complex regulatory network for regulation of ABA signalling mediated seed vigour. Finally, we showed that four SNPs in ZmRap2.7 coding region influenced its transcriptionally binding activity to the downstream gene promoters. Together with previously identified functional variants within and surrounding ZmRap2.7, we concluded that the distinct allelic variations of ZmRap2.7 were obtained independently during maize domestication and improvement, and responded separately for the diversities of seed vigour, flowering time and brace root development. These results provide novel genes, a new regulatory network and an evolutional mechanism for understanding the molecular mechanism of seed vigour. [ABSTRACT FROM AUTHOR]

Summary: Background: The composition of the root microbiome affects the host's growth, with variation in the host genome associated with microbiome variation. However, it is not known whether this intra-specific variation of root microbiomes is a consequence of plants performing targeted manipulations of them to adapt to their local environment or varying passively with other traits. To explore the relationship between the genome, environment and microbiome, we sampled seeds from teosinte populations across its native range in Mexico. We then grew teosinte accessions alongside two modern maize lines in a common garden experiment. Metabarcoding was performed using universal bacterial and fungal primers to profile their root microbiomes. Results: The root microbiome varied between the two modern maize lines and the teosinte accessions. We further found that variation of the teosinte genome, the ancestral environment (temperature/elevation) and root microbiome were all correlated. Multiple microbial groups significantly varied in relative abundance with temperature/elevation, with an increased abundance of bacteria associated with cold tolerance found in teosinte accessions taken from high elevations. Conclusions: Our results suggest that variation in the root microbiome is pre-conditioned by the genome for the local environment (i.e. non-random). Ultimately, these claims would be strengthened by confirming that these differences in the root microbiome impact host phenotype, for example, by confirming that the root microbiomes of high-elevation teosinte populations enhance cold tolerance. [ABSTRACT FROM AUTHOR]

High-concentration phosphorus (P) fertilizers are crucial for crop growth. However, fertilizers with lower P concentrations, such as calcium magnesium phosphate (CMP) and single super phosphate (SSP), can also serve as efficient P sources, especially when blended with high-concentration P fertilizers like diammonium phosphate (DAP) or monoammonium phosphate (MAP). In this study, we conducted a 48-day pot experiment to explore how blending low-P fertilizers could optimize maize P utilization, using CMP to replace DAP in acidic soil, and SSP to replace MAP in alkaline soil, with five SSP+MAP and CMP+DAP mixtures tested. Key metrics such as shoot and root biomass, shoot P uptake, root length, and soil P bioavailability were measured. We found that maize biomass and P uptake with 100% DAP were comparable to those with 50% CMP and 50% DAP in acidic soil. Similar results were observed for 100% MAP compared to 50% SSP and 50% DAP in alkaline soil. Root biomass and length were largest with 100% MAP in acidic soil and at 100% DAP in alkaline soil, with no significant differences at 50% SSP or CMP substitutions for MAP and DAP, respectively. Furthermore, 50% SSP or CMP substitutions for MAP and DAP increased the content and proportion of the labile inorganic P (Pi) pool (H2OPi and NaHCO3-Pi), had a direct and positive effect on Olsen-P. Our findings reveal that 1:1 blends of SSP and MAP in acidic soil, and CMP and DAP in alkaline soil, effectively meet maize's P requirements without relying solely on highconcentration P fertilizers. This indicates that strategic blending of fertilizers can optimize P use, which is crucial for sustainable agriculture. [ABSTRACT FROM AUTHOR]

Introduction: Improving photosynthetic use efficiency in dryland agroecosystems to sustain high agricultural yields is a key responsibility for ensuring food security. Methods: This study was conducted in the regions on the semiarid Loess Plateau of China during 2018-2020. Dryland maize of Xianyu 335 comprised four modes: basic yield input (CK, plastic film mulching, 37500 plant.ha-1 of plant density and unfertilized), farmer input (FP, plastic film mulching, 45000 plant.ha-1 of plant density and inorganic nitrogen(N) and phosphate(P) fertilizer were 150kg.ha-1 and 90kg.ha-1), high yield and high-efficiency input (HH, full plasticfilm mulching on double furrow, 67500 plant.ha-1 of plant density and N, P and organic manure(M) fertilizer were 230kg.ha-1, 140kg.ha-1 and 1500kg.ha-1), and super high yield input (SH, full plastic-film mulching on double furrow, 9000 plant.ha-1 of plant density and N, P and organic M fertilizer were 300kg.ha-1, 180kg.ha-1 and 7500kg.ha-1). The effects of different cultivation modes on yield, WUE, net photosynthetic rate(Pn), leaf area index(LAI), chlorophyll index(SPAD value) and root index were studied. Results: The results showed that the value average of yield and WUE for CK were 7790kg and 17480kg.ha-1 in three years. SH, HH and FP cultivation modes of yield and WUE was significant higher compared with CK cultivation mode (P<0.05). SH, HH and FP cultivation modes of yield and WUE increased by 34.01%, 48.68%, 56.39% and 34.34%, 47.99%, 57.99%, compared than CK cultivation mode. These differences were observed during the seedling stage, jointing stage, silking stage and filling stage. Year to year variation in performance of applied treatment, this improved in CK cultivation mode significantly enhanced SPAD value, Pn, LAI and the root index than SH, HH and FP cultivation modes. The yield exhibited a positive correlation with the WUE, SPAD value, Pn, LAI. The SH cultivation mode was the highest yields. Discussion: The results indicated that maize yield and WUE could be increased through integrating and optimizing cultivation techniques in maize production on the semiarid western Loess Plateau of China. The SH cultivation mode was the highest yields. The primary factor contributing to the increase in yield and WUE of maize due to increased density, increased fertilizer and covering measures is the augmentation of Pn, LAI, SPAD value, and root index. [ABSTRACT FROM AUTHOR]

This study aims to address the challenges of climate change, which has led to extreme temperature events and reduced rainfall, using Internet of Things (IoT) technologies. Specifically, we monitored the effects of drought on maize crops in the Republic of Croatia. Our research involved analyzing an extensive dataset of 139,965 points of weather data collected during the summer of 2022 in different areas with 18 commercial sensor nodes using the Long-Range Wide Area Network (LoRaWAN) protocol. The measured parameters include temperature, humidity, solar irradiation, and air pressure. Newly developed maize-specific predictive models were created, taking into account the impact of urbanization on the agrometeorological parameters. We also categorized the data into urban, suburban, and rural segments to fill gaps in the existing literature. Our approach involved using 19 different regression models to analyze the data, resulting in four regional models per parameter and four general models that apply to all areas. This comprehensive analysis allowed us to select the most effective models for each area, improving the accuracy of our predictions of agrometeorological parameters and helping to optimize maize yields as weather patterns change. Our research contributes to the integration of machine learning and AI into the Internet of Things for agriculture and provides innovative solutions for predictive analytics in crop production. By focusing on solar irradiation in addition to traditional weather parameters and accounting for geographical differences, our models provide a tool to address the pressing issue of agricultural sustainability in the face of impending climate change. In addition, our results have practical implications for resource management and efficiency improvement in the agricultural sector. [ABSTRACT FROM AUTHOR]

Estimating the latent heat flux (λET) accurately is important for water-saving irrigation in arid regions of Northwest China. The Penman-Monteith model is a commonly used method for estimating λET, but the parameterization of canopy resistance in the model has been a difficulty in research. In this study, continuous observation of λET during the growing period of maize and grassland in Northwest China was conducted based on the Bowen ratio energy balance (BREB) method and the Eddy covariance system (ECS). Two methods, Katerji-Perrier (K-P) and Garcıá-Santos (G-A), were used to determine the canopy resistance in the Penman-Monteith model and the estimation errors and causes of the two sub-models were explored. The results indicated that both models underestimated the λET of grassland and maize. The K-P model performed relatively well (R² > 0.94), with the root mean square errors (RMSE) equaled 37.3 and 28.1 W/m² for grass and maize, respectively. The accuracy of the G-A model was slightly lower than that of the K-P model, with the determination coefficient (R²) equaled 0.90 and 0.92, and the RMSE equaled 46.2 W/m² (grass) and 42.1 W/m² (maize). The vapor pressure deficit (VPD) was the main factor affecting the accuracy of K-P and G-A sub-models. The error of two models increased with the increasing in VPD for both crops. [ABSTRACT FROM AUTHOR]

High salinity reduces agriculture production and quality, negatively affecting the global economy. Zinc oxide nanoparticles (ZnO-NPs) enhance plant metabolism and abiotic stress tolerance. This study investigated the effects of 2 g/L foliar Zinc oxide NPs on Zea mays L. plants to ameliorate 150 mM NaCl-induced salt stress. After precipitation, ZnO-NPs were examined by UV–visible spectroscopy, transmission electron microscopy, scanning transmission electron microscopy, energy dispersive X-ray, and particle size distribution. This study examined plant height, stem diameter (width), area of leaves, chlorophyll levels, hydrolyzable sugars, free amino acids, protein, proline, hydrogen peroxide, and malondialdehyde. Gas chromatographic analysis quantified long-chain fatty acids, and following harvest, leaves, stalks, cobs, seeds, and seeds per row were weighed. The leaves' acid and neutral detergent fibers were measured along with the seeds' starch, fat, and protein. Plant growth and chlorophyll concentration decreased under salt stress. All treatments showed significant changes in maize plant growth and development after applying zinc oxide NPs. ZnO-NPs increased chlorophyll and lowered stress. ZnO-NPs enhanced the ability of maize plants to withstand the adverse conditions of saline soils or low-quality irrigation water. This field study investigated the effect of zinc oxide nanoparticles on maize plant leaves when saline water is utilized for growth season water. This study also examined how this foliar treatment affected plant biochemistry, morphology, fatty acid synthesis, and crop production when NaCl is present and when it is not. [ABSTRACT FROM AUTHOR]

Multi-parent populations (MPPs) are attractive for genetic and breeding studies because they combine genetic diversity with an easy-to-control population structure. Most methods for mapping QTLs in MPPs focus on the detection of QTLs in single environments. Little attention has been given to mapping QTLs in multienvironment trials (METs) and to detecting and modeling QTL-byenvironment interactions (QEIs). We present mixed model approaches for the detection and modeling of consistent versus environment-dependent QTLs, i.e., QTL-by-environment interaction (QEI). QTL effects are assumed to be normally distributed with variances expressing consistency or dependence on environments and families. The entries of the corresponding design matrices are functions of identity-by-descent (IBD) probabilities between parents and offspring and follow from the parental origin of offspring DNA. A polygenic effect is added to the models to account for background genetic variation. We illustrate the wide applicability of our method by analyzing several public MPP datasets with observations from METs. The examples include diallel, nested association mapping (NAM), and multi-parent advanced inter-cross (MAGIC) populations. The results of our approach compare favorably with those of previous studies that used tailored methods. [ABSTRACT FROM AUTHOR]

This study documented the contribution of precise positioning involving a global navigation satellite system (GNSS) and a real-time kinematic (RTK) system in unmanned aerial vehicle (UAV) photogrammetry, particularly for establishing the coordinate data of ground control points (GCPs). Without augmentation, GNSS positioning solutions are inaccurate and pose a high degree of uncertainty if such data are used in UAV data processing for mapping. The evaluation included a comparative assessment of sample coordinates involving RTK and an ordinary GPS device and the application of precise GCP data for UAV photogrammetry in field crop research, monitoring nitrogen deficiency stress in maize. This study confirmed the superior performance of the RTK system in providing positional data, with 4 cm bias as compared to 311 cm with the non-augmented GNSS technique, making it suitable for use in agronomic research involving row crops. Precise GCP data in this study allow the UAV-based Normalized Difference Red-Edge Index (NDRE) data to effectively characterize maize crop responses to N nutrition during the growing season, with detailed analyses revealing the causal relationship in that a compromised optimum canopy chlorophyll content under limiting nitrogen environment was the reason for reduced canopy cover under an N-deficiency environment. Without RTK-based GCPs, different and, to some degree, misleading results were evident, and therefore, this study warrants the requirement of precise GCP data for scientific research investigations attempting to use UAV photogrammetry for agronomic field crop study. [ABSTRACT FROM AUTHOR]

Trichoderma afroharzianum, a ubiquitous soil-borne fungus found on plant roots and decaying residues, displays competitive traits and mycoparasitic behavior against diverse microorganisms. Selected strains of this fungus are known in agriculture for their beneficial effects on plant growth and as bio-fungicides. However, recent findings have pinpointed Trichoderma afroharzianum as the causal agent behind maize ear rot disease in Europe since 2018, notably impacting maize cobs in Germany, France, and Italy. This study aims to evaluate the severity of Trichoderma ear rot disease on maize fresh matter content and specific quality parameters under semi-field conditions. Two distinct maize varieties were artificially inoculated with a pathogenic Trichoderma isolate at the flowering stage using needle pin or silk channel methods. Disease severity was assessed visually at the time of harvest based on the percentage of infected kernels according to EPPO Guidelines (PP 1/285). Fresh matter content and quality parameters such as alpha-amylase activity, C/N ratio, water, and sugar content were analyzed. Results showed that needle pin inoculation led to higher disease severity (60%) compared to silk channel inoculation (39%). Cob weight decreased significantly at the highest disease severity level by up to 50% compared to control plants. In both varieties, alpha-amylase activity increased significantly with higher Trichoderma disease severity, resulting in starch degradation and increased glucose release. The germination rate was severely affected by the infection, with only 22% of grains germinating, and the seedlings showed shortened and deformed growth. This is the first report on Trichoderma ear rot infection and its effect on fresh matter content and quality parameters in maize after artificial inoculation under field conditions. The results address an important knowledge gap and provide valuable insights into the infection pathway and impact on maize quality. [ABSTRACT FROM AUTHOR]

Background: In the face of contemporary climatic vulnerabilities and escalating global temperatures, the prevalence of maydis leaf blight (MLB) poses a potential threat to maize production. This study endeavours to discern marker-trait associations and elucidate the candidate genes that underlie resistance to MLB in maize by employing a diverse panel comprising 336 lines. The panel was screening for MLB across four environments, employing standard artificial inoculation techniques. Genome-wide association studies (GWAS) and haplotype analysis were conducted utilizing a total of 128,490 SNPs obtained from genotyping-by-sequencing (GBS). Results: GWAS identified 26 highly significant SNPs associated with MLB resistance, among the markers examined. Seven of these SNPs, reported in novel chromosomal bins (9.06, 5.01, 9.01, 7.04, 4.06, 1.04, and 6.05) were associated with genes: bzip23, NAGS1, CDPK7, aspartic proteinase NEP-2, VQ4, and Wun1, which were characterized for their roles in diminishing fungal activity, fortifying defence mechanisms against necrotrophic pathogens, modulating phyto-hormone signalling, and orchestrating oxidative burst responses. Gene mining approach identified 22 potential candidate genes associated with SNPs due to their functional relevance to resistance against necrotrophic pathogens. Notably, bin 8.06, which hosts five SNPs, showed a connection to defense-regulating genes against MLB, indicating the potential formation of a functional gene cluster that triggers a cascade of reactions against MLB. In silico studies revealed gene expression levels exceeding ten fragments per kilobase million (FPKM) for most genes and demonstrated coexpression among all candidate genes in the coexpression network. Haplotype regression analysis revealed the association of 13 common significant haplotypes at Bonferroni ≤ 0.05. The phenotypic variance explained by these significant haplotypes ranged from low to moderate, suggesting a breeding strategy that combines multiple resistance alleles to enhance resistance to MLB. Additionally, one particular haplotype block (Hap_8.3) was found to consist of two SNPs (S8_152715134, S8_152460815) identified in GWAS with 9.45% variation explained (PVE). Conclusion: The identified SNPs/ haplotypes associated with the trait of interest contribute to the enrichment of allelic diversity and hold direct applicability in Genomics Assisted Breeding for enhancing MLB resistance in maize. [ABSTRACT FROM AUTHOR]

Struvite (MgNH4PO4·6H2O), a mineral with low water solubility that can be recovered from industrial wastewater, has the potential to be used as a slow-release phosphorus (P) fertilizer. However, the effect of struvite on the yield and P uptake efficiency of different crops remains unclear. In this study, the effects of struvite, diammonium phosphate (DAP), and a mixed fertilizer consisting of struvite + DAP (MIX) on biomass, P uptake, and soil P fractions of Chinese cabbage, cowpea, and maize were investigated in pot experiments. The results showed that compared to DAP, the mixed fertilizer reduced the biomass of Chinese cabbage by 47%, while there was no difference in the biomass of cowpea and maize under P fertilizer application. There was no difference in total P concentration in Chinese cabbage and cowpea plants between DAP and MIX, while total P concentration in maize under mixed fertilizer treatment decreased by 16.73% compared to DAP treatment. Compared to DAP, the MIX treatment reduced total P uptake in Chinese cabbage and maize by 45.82% and 33.41%, respectively, with no direct difference in cowpea. Soil Olsen-P and CaCl2-P concentrations were highest in DAP among the different treatments. The MIX treatment significantly increased the water-soluble P in Chinese cabbage and cowpea by 5.87% and 5.23%, respectively, while the water-soluble P in maize was lower in the mixed fertilizer treatment than in the DAP treatment. In addition, mixed fertilizer significantly increased soil pH and soil phosphatase activity compared to DAP. This result suggested that among the three treatments of struvite, DAP, and MIX, struvite had the weakest effect on crop growth. In addition, among the three crops, Chinese cabbage, cowpea, and maize, the compatibility between struvite and maize was the highest. These results provide valuable insights for the future application of struvite in agricultural production for achieving stable yields while mitigating environmental risks. [ABSTRACT FROM AUTHOR]

Plant–microbe interactions are key to nutrient-use efficiency. Root microbes are influenced by rhizosphere soil and plant cultivars. The impact of cultivar-by-nitrogen (N) interactions on the maize-root microbiome remains unclear, yet it is crucial for understanding N use efficiency in maize. This study evaluated the effects of maize cultivars and N forms, along with their interactions, on the diversity and composition of root bacteria and fungi. Additionally, we examined correlations between soil microbes and root metabolites. The maize cultivar Zhengdan 958 (ZD958) showed a positive response to the mixture of nitrate and ammonium N, resulting in increased in biomass, grain yield, shoot N content, grain N content, and root area. In contrast, the cultivar Denghai605 (DH605) did not exhibit a similar response. The diversity and composition of root bacteria and fungi differed between ZD958 and DH605. The N form primarily affected the community structure of rhizospheric fungi in ZD958 and rhizospheric bacteria in DH605, rather than endophytic microbes. A mixed N supply increased the relative abundance of Basidiomycota, which was positively correlated with ZD958 yield. For DH605, a mixed N treatment enhanced nitrification functions involving Bacteroidetes and Proteobacteria, while it reduced the effects of ammonium N supply. The dominant rhizospheric microbes in DH605 showed a stronger response to changes in root metabolites compared to those in ZD958. A mixed N supply increased the content of palmitoleic acid in ZD958 root exudates, facilitating the recruitment of beneficial rhizospheric microbes, which promotes maize growth. In DH605, a mixed N supply decreased the concentration of sphinganine, which is significantly correlated with Acidobacteria (negatively), Proteobacteria (negatively), Bacteroidetes (positively), and TM7 (positively). Our findings suggest that different maize cultivars respond differently to N forms, causing distinct rhizospheric microbial effects, and that root metabolites send metabolic signals to regulate and recruit key bacterial and fungal communities. [ABSTRACT FROM AUTHOR]