Maize Crop Research Articles

First Report of <i>Metarhizium Rileyi</i> Infecting Fall Army Worm <i>Spodoptera Frugiperda</i> (J E Smith) From Nepal

The fall army worm (FAW) Spodoptera frugiperda (Noctuidae: Lepidoptera) is an invasive polyphagous pest that prefers maize crop in the newly invaded regions like Africa, Asia, Australasia, and some Pacific Islands and was recorded in Nepal in the year 2019. Surveys were conducted in the maize fields to collect various natural enemies for utilization in the management of FAW. Several larvae infected with an unidentified fungus were collected and subjected to morphological and molecular analysis for identification as Metarhizium rileyi. In bioassay studies we observed percent larval mortality at 1x108 conidia/ml suspension. This is the first report of M. rileyi infecting S. frugiperda from Nepal.

The Effects of Harvesting Period and Inoculant on Second-Crop Maize Silage Fermentative Quality

Southern Europe’s mutating weather conditions and the European environmental agenda have suggested the cropping of maize (Zea mays L.) after winter cereal cultivation, even if shortening the growing period could result in an immature harvesting stage, limiting its silage quality. The experimental design investigated the effects of four harvesting dry matter (DM) classes (DMvl, 23.9%; DMl, 25.3%; DMm, 26.2%; DMh, 30.4%) in two inoculant types (heterofermentative (HE) vs. homofermentative (HOM) on fermentative quality, DM losses, and aerobic stability. The early harvested DMvl and DMl classes had the lowest silage density (<130 kg m−3) and resulted in an organic acids profile lowering the fermentative quality and increasing the DM losses, while no differences were detected following the use of the inoculants. The aerobic stability was more susceptible to further adverse fermentation via opportunistic microorganisms in the DMm and DMh classes, probably due to the lower moisture content, but the use of both HE and HOM lactic acid bacteria seemed to contain this silage surface damage. In summary, a shortening of the maize growing period might limit the achievement of the maturity stage ideal for high-quality silage, hampering the positive effects of both HOM and HE inoculants in the ensiling process of early harvested maize.

Bio-Priming of Seed with Trichoderma sp. and Bacillus sp. Leads to Improved Morpho-Physiological Parameters Related to Drought Tolerance in Maize

Maize (Zea mays L.) holds an important position as a major grain crop in Pakistan flourishing across a diverse range of environmental conditions. The maize crop encounters various severe abiotic challenges with drought being the most concerning factor leading to diminished plant growth and yield. Seed priming a well-established and widely adopted technique serves as an effective mechanism to alleviate drought stress ultimately boosting both growth and grain yield. The primary objective of this study was to evaluate the impact of diverse seed priming methods on the growth and development of maize plants. Additionally, the study sought to assess the potential of various seed priming techniques in mitigating drought stress in maize. A pot experiment was conducted using a completely randomized design under natural conditions. The aim was to scrutinize the influence of different priming agents on morpho-physiological traits associated with water deficit conditions in maize. The gathered data underwent ANOVA analysis revealing variations in all parameters for both maize varieties at a 5% probability level. Specifically, the Pak-Afgoi variety displayed notable responsiveness to the seed priming approach in alleviating drought stress in maize. Furthermore, the findings underscored the evident and substantial impact of seed priming on both maize varieties across a range of studied characteristics under drought stress conditions. In conclusion, the present study suggests that seed priming holds the potential to enhance drought tolerance in maize.

Exploring the impact of organic and inorganic amendments, with foliar application of iron nanoparticles, on cadmium stabilization and growth of maize in wastewater irrigated-soil

ObjectivesThis study addresses the critical issue of Cd contamination in agricultural soils, posing substantial risks to crop productivity and food safety. While prior pot experiment has undertook this issue on a small scale, this study aims to evaluate the efficacy of selected best soil amendments, at a large-scale field experiment. MethodologyPress mud and humic acid were applied at 0.5%, while gypsum and Fe2O3 were applied at 5 mg/kg alone and with foliar application of Fe nanoparticles at 5 mg/L. AnalysisComparative analysis with control revealed the immobilization efficiency of all amendments in descending order of effectiveness as follows: 100, 102, 104, 104, 105, 102, 105, and 105% for PM, HA, GYP, Fe, PM + Fe Nps, HA + Fe Nps, GYP + Fe Nps, and Fe + Fe Nps. Additionally, reduced growth, photosynthetic activities, and elevated levels of malondialdehyde and hydrogen peroxide, indicative of oxidative damage in control plant. FindingsApplication of these amendments with foliar spraying of Fe Nps effectively mitigates Cd toxicity in maize crops, leading to improved growth, biomass, photosynthetic pigments, and antioxidant enzyme activities. Novelty/ImprovementThese findings highlight the significance of exploring innovative approach of combining different amendments with foliar application of nanoparticles to mitigate Cd contamination and enhance soil health, thereby contributing to global efforts in ensuring food safety and security.

Synthesis of Radiolabeled [14C]Rimsulfuron and Stable Isotope Labeled Rimsulfuron-[M + 3] to Support Crop Metabolism Studies for Reregistration.

Rimsulfuron is a sulfonylurea herbicide that controls grass and broadleaf weeds in maize, potatoes, fruits, nuts, and other crops. It can also be used as a burndown herbicide to clear invasive weed species along roadsides and other nonagricultural land. Rimsulfuron acts as an acetolactase synthase (ALS) inhibitor, blocking the synthesis of essential amino acids required for plant growth. As is common practice, rimsulfuron has been subject to periodic reviews by regulatory agencies for reregistration since its introduction into the market in the early 1990s. The goal of these reviews is to ensure that the herbicide carries out its intended use without creating adverse side effects to humans and the environment. Since scientific methods are continually evolving and being developed, global regulatory agencies can require additional studies to address data gaps for pesticide renewals. During this reregistration process for rimsulfuron, a new confined rotational crop study was required to address a data gap requested by the European Food Safety Authority (EFSA). Consequently, the corresponding pyridine and pyrimidine radiolabeled [14C]rimsulfuron and [M + 3] stable isotopes of rimsulfuron were synthesized for this study to support the reregistration process.

Maize leaf disease image enhancement algorithm using TFEGAN

Maize leaf diseases have a profound impact on maize crop yield. However, due to practical constraints, gathering a substantial number of maize disease images is time-consuming and labor-intensive. Furthermore, low-light conditions and noise interference in maize leaf disease images present significant challenges for image generation. Therefore, this paper proposes TFEGAN, a novel algorithm designed to generate maize leaf disease images. TFEGAN leverages a Two-Way Extraction Module (TWEM) to enhance the perceptual domain of the model and effectively reuse maize leaf disease features. The algorithm employs two well-trained Generative Adversarial Networks (GANs) to enhance low-light and noisy maize leaf disease images. The low-light enhancement component utilizes a double discriminator and self-regularization to balance global and local enhancement while constraining the distance between the input image and the denoising component. Moreover, the denoising part employs a strong coordinated attention mechanism and an environmental encoder to learn noise regions and their surrounding structures, thus generating better local images and enabling more accurate evaluation by the discriminant network. The generators of both networks are encapsulated by two discriminators and combined with a bi-directional feature extraction structure to generate normal maize leaf disease images. Experimental evaluations demonstrate the effectiveness of TFEGAN in improving the quality of maize leaf disease images under low-light and noisy conditions, showcasing its potential for practical applications. Overall, this paper presents a promising solution to the challenges of low-light and noise interference in maize leaf disease images, utilizing bidirectional feature extraction and GANs.

Boron Impact on Maize Growth and Yield: A Review

Maize (Zea mays L.) is a vital crop, contributing significantly—at least 30%—to global dietary energy intake and biofuels and ethanol production. This review article delves into the dynamic interplay between boron (B) and maize growth, yield, and agricultural sustainability. Boron, a crucial micronutrient, is pivotal in essential physiological processes such as root development, leaf expansion, and cob formation. These processes are fundamental for ensuring the vigour and productivity of maize crops. Conversely, boron deficiency manifests as thinner leaves with reduced chlorophyll content, compromising plant health, and hindering yield potential. Maintaining adequate boron levels, particularly during reproductive stages, is critical for mitigating the risk of abnormal ears and maximizing the quantity and quality of maize production. Emerging research underscores the significance of foliar boron application at various growth stages of maize, which stimulates growth, facilitates cell wall development, and increases leaf area. This translates to improved light interception and photosynthetic efficiency, ultimately contributing to increased plant vigour and biomass accumulation. Furthermore, exploring innovative approaches for sustainable boron management is crucial. This includes precision fertilization techniques and biofortification strategies to ensure optimal maize production while minimizing environmental impacts. By gaining a deeper understanding of the complex relationship between boron and maize, farmers can develop customized fertilization plans that utilize strategic foliar boron application. This approach unlocks maize's full yield potential and contributes to sustainable agricultural practices, supporting global food security.

Maize leaf disease recognition using PRF-SVM integration: a breakthrough technique

The difficulty of collecting maize leaf lesion characteristics in an environment that undergoes frequent changes, suffers varying illumination from lighting sources, and is influenced by a variety of other factors makes detecting diseases in maize leaves difficult. It is critical to monitor and identify plant leaf diseases during the initial growing period to take suitable preventative measures. In this work, we propose an automated maize leaf disease recognition system constructed using the PRF-SVM model. The PRFSVM model was constructed by combining three powerful components: PSPNet, ResNet50, and Fuzzy Support Vector Machine (Fuzzy SVM). The combination of PSPNet and ResNet50 not only assures that the model can capture delicate visual features but also allows for end-to-end training for smooth integration. Fuzzy SVM is included as a final classification layer to accommodate the inherent fuzziness and uncertainty in real-world image data. Five different maize crop diseases (common rust, southern rust, grey leaf spot, maydis leaf blight, and turcicum leaf blight along with healthy leaves) are selected from the Plant Village dataset for the algorithm’s evaluation. The average accuracy achieved using the proposed method is approximately 96.67%. The PRFSVM model achieves an average accuracy rating of 96.67% and a mAP value of 0.81, demonstrating the efficacy of our approach for detecting and classifying various forms of maize leaf diseases.

Cellular dynamics of host − parasitoid interactions: Insights from the encapsulation process in a partially resistant host

Cotesia typhae is an eastern African endoparasitoid braconid wasp that targets the larval stage of the lepidopteran stem borer, Sesamia nonagrioides, a maize crop pest in Europe. The French host population is partially resistant to the Makindu strain of the wasp, allowing its development in only 40% of the cases. Resistant larvae can encapsulate the parasitoid and survive the infection. This interaction provides a very interesting frame for investigating the impact of parasitism on host cellular resistance. We characterized the parasitoid ovolarval development in a permissive host and studied the encapsulation process in a resistant host by dissection and histological sectioning compared to that of inert chromatography beads. We measured the total hemocyte count in parasitized and bead-injected larvae over time to monitor the magnitude of the immune reaction. Our results show that parasitism of resistant hosts delayed encapsulation but did not affect immune abilities towards inert beads. Moreover, while bead injection increased total hemocyte count, it remained constant in resistant and permissive larvae. We conclude that while Cotesia spp virulence factors are known to impair the host immune system, our results suggest that passive evasion could also occur.

Drip-tape irrigation depth: water use efficiency, yield and forage quality in maize

Objective: to evaluate the effect of the drip-tape irrigation depth on the efficiency of water use, yield, nutritional quality and profitability of forage maize, a study was established by installing drip-tape at a depths 0.05, 0.15 and 0.30 meters. Design/ Methodology/ Approach: a randomized block experimental design was used. Treatments evaluated consisted of the installation of drip-tape at three depths 0.05, 0.15 and 0.30 m; each treatment in three replicates. The experimental unit was a 15 m2 surface (comprising four 5m-long furrows, with a 0.76 m separation between furrows). Results: results showed that with the drip-tape installed at a depth of 0.15 m, the highest biomass production and water use efficiency were obtained, without modifying the bromatological quality of the forage. However, the best benefit-cost ratio corresponded to the drip-tape installed at 0.3 m, recovering $1.27 for each MXN peso invested in crop production. Limitations/ Implications of the study: water scarcity in arid and semi-arid regions is a global problem, so it is necessary to use irrigation methods that make water use more efficient without reducing crop yield. Findings/conclusions: the installation of the drip-tape at a depth of 0.15 m is recommended, due to the improvement in yield and water use efficiency without affecting nutritional quality of the forage or profitability of maize crop.

Study the Socioeconomic Characteristics of Maize Grower in Aurangabad District of Maharashtra, India

The present study was designed to study the socioeconomic characteristics in Aurangabad district has been purposively selected for the study because Vaijapur and Gangapur tehsils having highest area under maize crop as compared to other tehsils in the Aurangabad district. The average age of the maize grower was 30 -40 years. This indicated that, maize growers were in adult age group. The educational status was evaluated which shows 5 per cent maize growers were illiterate. It is revealed that, 25 per cent were primary school level, 11.67 per cent were at college level, 11.67 per cent at SSC level, 46.66 per cent at HSC level. This indicated that the maize growers in the study area were educated, upto college level. In case of maize growers, that in case of maize growers, 95 per cent of the farmers sole occupation was Agriculture. While 1.66 per cent farmers were involved in both Agriculture and Business, and 3.34 per cent were involved in agriculture and service. In case of kharif maize growers, it was seen that, 35.02 per cent male, 31.91 per cent female, and 33.07 per cent of children. The maize growers had livestock within their farm. About 31.15 per cent had one bullock pair, 33.96 per cent of buffalo, 34.89 per cent of cow respectively. In case of maize growers, 33.34 per cent of the sample farmers had less than 2 hectares of land holding and 48.33 per cent of the farmers had 2 to 4 hectares of land while 18.33 per cent of the sample farmers had more than 4 hectare of land holding. The means majority of the farmers having 2 to 4 ha farmers. The proportionate irrigated area was 94.19 per cent. Net sown area was 100 per cent. While Gross cropped area was 100 per cent and cropping intensity was 143.21. The proportionate area under maize crop was 17.80 per cent. Followed by cotton, onion and wheat was 23.40, 14.11, 11.21, per cent. This indicated that, the cropping pattern of the maize growers was dominated by maize alone. The cropping intensity 143.21.

Assessment of nutrient flows in maize-based farming system by smallholder farmers for sustainable production in Ikara, Kaduna State

Nutrient depletion is one of the major causes of decreased crop yield, and a threat to food security and sustainable crop production. NutMon- toolbox was used to determine nutrient flows and partial nutrient balances of maize-based smallholders’ farming system. Data was collected using structured questionnaire from 15 randomly selected farmers, with five farmers each in three villages. Composite soil samples were also taken from each of the three plots. At crop maturity, samples of crop products and residues were randomly taken from the selected fields. Nitrogen, P and K contents in soil and crop material was used to calculate nutrient flows and partial balances. Results obtained revealed that mineral fertilizer flow, averaged 349.20kg N yr-1 and 81.45kg K yr-1 and were lower than 376.65kg N yr-1 and 431.44kg K yr-1 organic input. However, phosphorus in mineral fertilizer (55.78kg P yr-1) was higher compared to phosphorus (51.06 kg P ha-1 yr-1) in organic input. Nitrogen, phosphorus and potassium for maize seeds and crop residue were all negative. The partial nutrient balances were positive 53.45kg N ha-1 yr-1 and 79.40kg K ha-1 but negative 1.10kg P ha-1 yr-1. Harvesting of crops for food, without incorporation of crop residue into the soil, were the most important sources of nutrient mining in smallholder production system. Integrated soil fertility management practices that favour the buildup of soil organic matter and use of animal manure should be encouraged through effective extension services at Ikara, Kaduna State, Nigeria.

Machine learning-based potential loss assessment of maize and rice production due to flash flood in Himachal Pradesh, India.

Flash floods in mountainous regions like the Himalayas are considered to be common natural calamities. Their consequences often are more dangerous than any flood event in the plains. These hazards not only put human lives at threat but also cause economic deflation due to the loss of lands, properties, and agricultural production. Hence, assessing the impact of such hazards in the existing agricultural system is of utmost importance to understand the probable crop loss. In this paper, we studied the efficiency of the remotely sensed microwave data to map the croplands affected by the flash flood that occurred in July 2023 in Himachal Pradesh, a mountainous state in the Indian Himalayan Region. The Una, Hamirpur, Kangra, and Sirmaur districts were identified as the most affected areas, with about 9%, 6%, 5.74%, and 3.61% of the respective districts' total geographical area under flood. Further, four machine learning algorithms (random forest, support vector regressor, k-nearest neighbor, and extreme gradient boosting) were evaluated to forecast maize and rice crop production and potential loss during the Kharif season in 2023. A regression algorithm with ten predictor variables consisting of the cropland area, two vegetation indices, and seven climatic parameters was applied to forecast the maize and rice production in the state. Amongst the four algorithms, random forest showed outstanding performance compared to others. The random forest regressor estimated the production of maize and rice with R2 more than 0.8 in most districts. The mean absolute error and the root mean squared error obtained from the random forest regressor were also minimal compared to the others. The maximum production loss of maize is estimated for Solan (54.13%), followed by Una (11.06%), and of rice in Kangra (19.1%), Una (18.8%) and Kinnaur (18.5%) districts. This indicated the utility of the proposed approach for a quick in-season forecast on crop production loss due to climatic hazards.

Economic impact of front line demonstrations on maize crop

Economic impact of front line demonstrations on maize crop

Enhanced efficiency nitrogen fertilizers (EENFs) can reduce nitrous oxide emissions and maintain high grain yields in a rain-fed spring maize cropping system

ContextEnhanced efficiency nitrogen fertilizers (EENFs) have provided opportunities for the simultaneous mitigation of nitrous oxide (N2O) emissions and increases in crop productions. However, the practice of combining EENFs with optimal fertilization under conditions of misaligned water and fertilizer inputs in rain-fed spring maize systems remains inadequately understood. ObjectiveThis study aims to determine the factors controlling N2O emissions under the soil climatic conditions in rain-fed plastic mulching cropping systems treated with different nitrogen (N) fertilization rates and EENFs, and to determine the most effective N fertilization measure to reduce N2O emissions while maintaining crop yields. MethodsA 3-year field experiment was conducted in a spring maize system located in the semiarid rain-fed region of the Loess Plateau, applying two types of EENFs: a nitrification inhibitor dicyandiamide (DCD) and a slow-release fertilizer (SRF). It comprised five fertilization treatments: unfertilized (CK), conventional N rate (CON, 200 kg N ha−1), optimal N rate (OPT, 160 kg N ha−1), OPT with the addition of DCD (OPT+DCD), and OPT using SRF (OPT-SRF). ResultsThe average annual cumulative N2O emissions over the 3-year experimental period ranged from 0.74 to 1.87 kg N2O-N ha–1. Fertilizer N contributed 26−60% to annual N2O emissions. The highest N2O fluxes (50–161 μg N2O-N m–2 h–1) typically occurred within the initial 10 days following fertilization, likely induced by strong nitrification processes, constituting 12–19% of the annual N2O emissions during this brief period. In comparison to the CON treatment, the OPT, OPT+DCD, and OPT-SRF treatments resulted in significant reductions in annual N2O emissions of 24%, 46%, and 34%, respectively, without causing any significant decrease in maize grain yields. The application of DCD led to increased ammonium (NH4+-N) concentrations while reducing nitrate (NO3–-N). Conversely, using SRF resulted in a decrease in both NH4+-N and NO3–-N concentrations. ConclusionsUsing EENFs at the ideal fertilization rate significantly curtailed yearly N2O emissions without adversely affecting maize yields in a rain-fed plastic mulching spring maize system prevalent in the Loess Plateau. Most N2O emissions occurred post-fertilization, with rainfall events further influencing these emissions. ImplicationsOur findings recommend the incorporation of nitrification inhibitors, such as DCD, as the most effective fertilizer measure for reducing N2O emissions in the rain-fed region of the Loess Plateau.

Genomic, climatic, and cultural diversity of maize landraces from the Himalayan Kingdom of Bhutan

Societal Impact StatementBhutan is an ancient kingdom in the Himalayan range and one of the most rugged, geodiverse, and mountainous agricultural countries in the world. Historically secluded and geographically isolated, Bhutan is a hotspot for Himalayan agrobiodiversity where small‐scale agriculture supports the livelihoods of a large share of the resident population. Here, Bhutanese maize agrobiodiversity is explored to unlock its adaptation potential using genomics and participatory variety selection in combination with climate research. We show that Bhutanese traditional farmers maintain a wealth of diversity that may support the sustainable intensification of maize cropping in the Himalayas and beyond.Summary Bhutan, an ancient kingdom enshrouded in the Himalayas, hosts largely untapped agrobiodiversity that may harness genetic variation useful for adaptation to local climates and user needs. Here, we genotyped‐by‐sequencing 351 pooled samples of local maize (Zea mays L.) landraces, the entire collection of the Bhutan National Gene Bank, comparing their genomic diversity with maize from other countries in the Himalayan range. We reconstructed the adaptation of Bhutanese maize to historical and projected climates, identifying areas of future maladaptation. We then run a common garden experiment involving local smallholder farmers in a participatory evaluation of landraces' performance, aiming at the identification of quantitative trait nucleotides (QTNs) contributing to adaptation, performance, and farmers' choice. We found that Bhutanese maize agrobiodiversity is unique in the Himalayan range, and a locus on Chromosome 5 supports the differentiation of three distinct genetic clusters. We found that a portion of current genomic diversity can be associated with the Bhutanese landscape and that maize cultivation in the southwest of the country may be negatively impacted by projected climates. We also found that Bhutanese maize agrobiodiversity is large and may contribute to adaptation and improvement. A genome‐wide association study identified 117 QTNs for climatic adaptation, agronomic performance, and farmers' preferences. Our results show that Bhutanese maize landraces are a unique source of genetic agrobiodiversity for local adaptation. We found that the integration of genomics, climate science, and participatory methods can speed up the identification of genetic factors contributing to the sustainable intensification of maize cultivation in the Himalayas and beyond.

Effect of establishment methods in rainy season (kharif) and tillage practices in winter season (rabi) on yield and economics of rice (Oryza sativa)–maize (Zea mays) cropping system under coastal saline ecosystem

A field experiment was carried out during 3 consecutive rainy seasons (kharif) June–November and winter (rabi) December–May seasons of 2013–16 at Canning Town, West Bengal to evaluate 3 rice (Oryza sativa L.) es tablishment methods, viz. dry direct seeding (DSR), unpuddled transplanting (UNPT) and puddled transplanting (PT), followed by 3 tillage practices for sowing rabi maize (Zea mays L.), viz. zero tillage (ZT), conventional tillage (CT) and raised bed sowing (RBS). The DSR was done in the last week of May when the soil salinity was higher (12–15 dS/m); however, it reduced to 4–5 dS/m in the month of June due to leaching of salts by monsoon rain. The transplanting in the UNPT and PT plots was done during the first week of July using 40 days old seedlings. Submergence caused by the heavy rain, affected the transplanted rice (PT and UNPT) but not the DSR, as the plants with DSR were sufficiently above the standing water due to higher plant height. The mean grain yields in 3 establishment methods of rice (5,117; 4,477 and 4,740 kg/ha in PT, UNPT and DSR respectively) were statistically at par. However, net returns ( 36,000/ha) and benefit: cost ratio (2.2) were the highest in DSR owing to 24% re duction in cost of cultivation than PT rice. The positive effects of DSR also observed on the succeeding rabi maize crop in terms of 7.4 ha-cm less irrigation water requirement and 27% higher irrigation water productivity. Maize gave the highest yield (5,600 kg/ha), net returns ( 37,910/ha) and benefit: cost ratio (BCR) 1.86 with RBS tillage practices. The system rice-equivalent yield, net returns and BCR were 11,659 kg/ha, 77,470/ha and 2.05, re spectively, for dry direct-seeded rice-raised bed sown maize with higher mean irrigation water productivity (79 kg/ ha-cm) and energy productivity (461 kg/GJ) of rabi maize.

Long-term fertilization and manuring effects on the nexus between sulphur distribution and SOC in an Inceptisol over five decades under a finger millet–maize cropping system

Our investigation revealed that alterations in sulphur (S) pools are predominantly governed by soil organic carbon (SOC), soil nitrogen (N), microbial biomass, and soil enzyme activities in sandy clay loam (Vertic Ustropept) soil. We employed ten sets of nutrient management techniques, ranging from suboptimal (50% RDF) to super-optimal doses (150% RDF), including NPK + Zn, NP, N alone, S-free NPK fertilizers, NPK + FYM, and control treatments, to examine the interrelation of S with SOC characteristics. Fourier-transform infrared (FT-IR) spectroscopy was utilized to analyze the functional groups present in SOC characterization across four treatments: 100% NPK, 150% NPK, NPK + FYM, and absolute control plots. Principal component analysis (PCA) was then applied to assess 29 minimal datasets, aiming to pinpoint specific soil characteristics influencing S transformation. In an Inceptisol, the application of fertilizers (100% RDF) in conjunction with 10 t ha−1 of FYM resulted in an increase of S pools from the surface to the subsurface stratum (OS > HSS > SO42−–S > WSS), along with an increase in soil N and SOC. FT-IR spectroscopy identified cellulose and thiocyanate functional groups in all four plots, with a pronounced presence of carbohydrate—protein polyphenol, sulfoxide (S=O), and nitrate groups specifically observed in the INM plot. The PCA findings indicated that the primary factors influencing soil quality and crop productivity (r2 of 0.69) are SOC, SMBC, SMBN, SMBS, and the enzyme activity of URE, DHA, and AS. According to the study, the combined application of fertilizer and FYM (10 t ha−1) together exert a positive impact on sulphur transformation, SOC accumulation, and maize yield in sandy clay loam soil.

Deficit irrigation interacting with biochar mitigates N2O emissions from farmland in a wheat–maize rotation system

Biochar application to agricultural fields is an effective carbon sequestration measure that has the potential to reduce N2O emissions and increase soil water holding capacity. However, the interaction mechanisms of biochar under deficit irrigation on N2O emissions remain unclear. A two-year field experiment is conducted in the Guanzhong Plain, China, in order to quantify the effects of biochar and deficit irrigation on N2O emissions from winter wheat–summer maize crop rotation and to investigate the potential mechanisms of nitrification and denitrification. According to the combination of biochar application and actual evapotranspiration-based irrigation scheduling, four treatments are designed (B1W100: biochar 30 t·ha−1 + ET; B1W80: biochar 30 t·ha−1+ 0.8 ET; B0W100: no biochar + ET; B0W80: no biochar + 0.8ET). The soil N2O flux, soil physical and chemical properties, and key functional gene abundance related to N2O emissions in nitrification and denitrification at different growth stages are investigated and discussed. Results show that the interaction between deficit irrigation and biochar significantly reduces soil N2O emissions. During the wheat and maize season, the application of biochar reduces the N2O emissions by an average of 12.9% and 15.2%, respectively. Deficit irrigation also reduces the N2O emissions by an average of 17.4% and 15.5%, respectively. Pearson correlation analysis shows that soil N2O is significantly correlated with soil water-filled pore space during the phase with intense N2O emissions. Soil functional gene abundance is determined at different growth stages for both wheat and maize. Maximum soil denitrification functional gene abundance is observed at the time when wheat and maize enter the stage of their peak growth at the jointing stage. With biochar addition and deficit irrigation, the abundance of nirK and nosZ genes increases and AOB amoA genes decreases. These results suggest that biochar with deficit irrigation is a better solution to reduce N2O emissions from agricultural soils.

The Relationship between Changes in Hydro-Climate Factors and Maize Crop Production in the Equatorial African Region from 1980 to 2021

Agricultural production across the African continent is subjected to various effects of climate variability. One of the main staple foods in Sub-Saharan Africa is maize. However, limited scientific research has recently focused on understanding the possible effects of hydro-climatic variability on maize production. The aim of the present work was to contribute to policy and climate adaptation, thus reducing the vulnerability of maize production to climate change over Equatorial Africa. This study firstly examined long-term trends of precipitation (PRE), soil moisture (SM), actual evapotranspiration (E), and potential evapotranspiration (Ep), as well as surface air temperatures, including the minimum (TMIN) and maximum (TMAX). Secondly, the relationship between maize production and these climate variables was quantified for 18 Equatorial African countries (EQCs) over 1980−2021. To assess the linear trends, Mann–Kendall and Sen’s slope tests were used to quantify the magnitude of the hydro-climatic variable trends at the 5% significance level, and Pearson’s correlation coefficient was used to evaluate the relation of these climate parameters with the maize production. The annual mean PRE declined at 0.03 mm day−110a−1. Other climate variables increased at different rates: SM at 0.02 mmday−110a−1, E at 0.03 mm day−110a−1, Ep at 0.02 mm day−1 10a−1, TMIN and TMAX at 0.01 °C day−110a−1. A regional analysis revealed heterogeneous significant wet–dry and warm–cool trends over the EQCs. While, spatially, dry and warm climates were observed in the central to eastern areas, wet and warm conditions dominated the western regions. Generally, the correlations of maize production with the E, Ep, TMAX, and TMIN were strong (r > 0.7) and positive, while moderate (r > 0.45) correlations of maize production with PRE and SM were obvious. These country-wide analyses highlight the significance of climate change policies and offer a scientific basis for designing tailored adaptation strategies in rainfed agricultural regions.