High-yielding Maize Research Articles

Effects of Different Nitrogen Topdressing Ratios on Soil Nitrate-Nitrogen and Summer Maize Growth

Abstract: The Jianghuai region in China is well known for its high-quality and high-yielding maize production, but there is inadequate analysis about the N management in this region (especially the topdressing ratio). To evaluate the suitable topdressing ratio for maize nitrogen application, the effects of different nitrogen topdressing ratios on soil nitrogen and summer maize growth were studied in 2022–2023. In each treatment, a total of 250 kg N/hm2 was applied, i.e., 50 kg N/hm2 was applied as the base fertilizer, and the rest of the nitrogen fertilizer (200 kg N/hm2) was applied at the jointing and filling stages at different ratios, including 3:7 (60 and 140 kg N/hm2 were applied at the jointing and filling stages, respectively, T1 treatment), 7:3 (T2 treatment), and 1:1 (CK treatment). Compound fertilizer (N: P: K = 18%: 12%: 5%) was used as the base fertilizer, and urea was used as the topdressing fertilizer. The results showed that in 2022 (dry year), compared with values in the T1 treatment, the nitrate-nitrogen accumulation in the 0–100 cm soil layer at maize harvest under the T2 and CK treatments decreased by 33.8% and 14.7%, respectively; compared with values in CK treatment, the T2 treatment could significantly increase the ear length of maize by 9.4%. In 2023 (wet year), compared with values in the T1 treatment, the 100-grain weight, maize yield, N partial factor productivity (NPFP), and N uptake efficiency (NUPE) of T2 treatment significantly increased by 13.4%, 17.2%, 20.1%, and 21.5%, respectively; compared with values in the CK treatment, ear length, maize yield, and NPFP of T2 treatment significantly increased by 6.15%, 14.0%, and 15.8%, respectively. Therefore, for this study, a topdressing ratio of 7:3 between the jointing and filling stages (T2 treatment) was beneficial to reduce nitrogen accumulation in dry years and increase maize yield and nitrogen partial factor productivity in wet years.

Blending of Slow-Release N Fertilizer and Urea Improve Rainfed Maize Yield and Nitrogen Use Efficiency While Reducing Apparent N Losses

Effective nitrogen (N) management practices are essential for achieving efficient and sustainable agricultural production. The purpose of this study was to improve N use efficiency (NUE) and minimize N loss by optimizing the rate and type of N fertilizer application while maintaining a high yield of maize. A two-year field experiment with U (urea), S (slow-release N fertilizer), and SU (blending of S and U) under four N application levels (N1: 90 kg ha−1, N2: 120 kg ha−1, N3: 180 kg ha−1, N4: 240 kg ha−1) was conducted to investigate their effects on ammonia (NH3) volatilization, residual soil nitrate N (), yield, NUE, apparent N losses of rainfed maize. NH3 volatilization in SU and S were 38.46% and 16.57% lower than that in U, respectively. SU and S were found to reduce the apparent N losses by 42.98% and 62.23%. SU decreased leaching in deep soils and increased content in topsoil. Compared with U and S, SU significantly increased yield, plant N accumulation, and NUE. SUN4 achieved the maximum maize yield and plant N accumulation, averaging 7968.36 kg ha−1 and 166.45 kg ha−1. In addition, the high yield and NUE were obtained when the mixing ratio of S and U was 53–58% and the N application rate was 150–220 kg ha−1. The findings highlight that SU effectively reduces N losses while ensuring high yield, which could be used as one of the optimal N fertilization strategies for rainfed maize in Northwest China.

Genome-Wide Identification of the Trihelix Transcription Factor Family and Functional Analysis of ZmTHX15 in Maize.

The trihelix transcription factor, which is a plant-specific family, play a critical role in plant growth and development and stress responses. Drought is the main limiting factor affecting yield of maize (Zea mays). However, the identification and characterization of this gene family in maize and its biological functions in response to drought stress have not been reported. Here, 46 Zea mays trihelix genes (ZmTHXs) were identified in the genome. Phylogenetic analysis of the ZmTHXs revealed that the genes were clustered into five subfamilies: GT-1, GT-2, GTγ, SH4, and SIP1. Chromosomal localization analysis showed that the 46 ZmTHXs were unevenly distributed across 10 chromosomes in maize. Cis-acting elements related to abiotic stress in ZmTHXs were found. Most ZmTHXs genes showed significant changes in expression levels under drought treatment. In addition, ZmTHX15-overexpressing Arabidopsis exhibited stronger drought tolerance with less secondary oxidative damage and higher photosynthetic rate. These findings could serve as a basis for future studies on the roles of ZmTHXs and the potential genetic markers for breeding stress-resistant and high-yielding maize varieties.

Unraveling Genetic Variation and Inheritance Patterns in Newly Developed Maize Hybrids for Improving Late Wilt Disease Resistance and Agronomic Performance Under Artificial Inoculation Conditions.

Late wilt disease caused by the fungal pathogen Magnaporthiopsis maydis represents a major threat to maize cultivation in the Mediterranean region. Developing resistant hybrids and high-yielding offers a cost-effective and environmentally sustainable solution to mitigate yield losses. Therefore, this study evaluated genetic variation, combining abilities, and inheritance patterns in newly developed twenty-seven maize hybrids for grain yield and resistance to late wilt disease under artificial inoculation across two growing seasons. The results indicated highly significant variations among assessed hybrids for all measured traits. Combining ability analysis identified IL-306, IL-304, and IL-303 as excellent combiners for grain yield and late wilt resistance, positioning them as superior candidates for hybrid development. Additionally, IL-302 was identified as a strong general combiner for earliness, and IL-307 and IL-309 demonstrated potential for producing short-statured hybrids critical for improving lodging tolerance and maximizing yield. Specific combining ability effects indicated promising earliness, yield, and disease-resistance hybrids, including IL-303×T2 and IL-306×T1. GGE biplots presented optimal line×tester combinations, offering strategic guidance for hybrid development. The principal component analysis demonstrated strong associations between grain yield, late wilt resistance, and key agronomic traits, such as ear length and kernel number. The observed robust positive association between grain yield, late wilt resistance, and yield attributes suggests selection potential for improving maize productivity. Moreover, the genotypic correlations revealed that earlier silking, taller plants, and higher kernel counts were strongly linked to enhanced yield potential. Genetic parameter estimates indicated a predominance of non-additive genetic effects for most traits, with moderate to high broad-sense heritability suggesting substantial genetic contributions to phenotypic variance. This research provides valuable insights to support the development of disease-resistant and high-yielding maize hybrids addressing critical food security challenges.

Film mulching can alleviate soil quality decrease and produce high maize yield under different irrigation strategies

Plastic film mulching (PM) combined with irrigation is widely adopted to improve crop yields, water and nitrogen efficiency, especially in arid farming areas. Despite its benefits, the effects of this method on soil quality and its subsequent impact on crop productivity and resource efficiency have not been thoroughly investigated. In this study, we formulated a soil quality indicator (SQI) from five years of field experiments in the Hetao Irrigation District (HID) of Northwestern China. The treatments included border irrigation as the control treatment (CK), CK combined with PM (BI_PM), and three water level drip irrigation treatments combined with PM. Three threshold values of soil matric potential for drip irrigation were −10 kPa (HDI_PM), −30 kPa (MDI_PM), and −50 kPa (LDI_PM). We then examined the SQI changes based on measured multiple soil properties and assessed their implications for maize yield, irrigation water productivity (IWP), and partial factor productivity of nitrogen (PFPN). We found: (1) from 2016 to 2020, HDI_PM achieved the highest average yield (15.77 t ha–1), IWP (3.73 kg m–3), and PFPN (63.18 kg kg–1), showing increases of 54.77 %, 84.90 %, and 96.93 % over the control treatment, respectively; (2) no significant variations in the SQI were observed for HDI_PM in 2020 in the topsoil (0–30 cm) and subsoil (30–60 cm) compared to the initial condition. However, CK, BI_PM, MDI_PM, and LDI_PM showed reductions in SQI in both soil layers, primarily due to decreased soil organic carbon (SOC) and structural stability, along with increased sand content and soil salinity; (3) according to the linear mixed-effects model, a low SQI (< 0.43), elevated temperatures, and drought indices negatively impact yield. Hence, we advocate for HDI_PM to maximize yield and PFPN. To enhance soil quality, identifying agronomic practices that increase SOC and reduce soil salinity in the HID is crucial.

Modeling the Effects of Sowing Dates on Maize in Different Environments in the Tropical Area of Southwest China Using DSSAT

Maize yield is affected by meteorological conditions and cultivation management. Sowing date adjustment is one of the most commonly used cultivation management methods for achieving a high maize yield in the tropical area of Southwest China. This study conducted field experiments involving five maize cultivars with different sowing dates in Yunnan Province from 2012 to 2015. The parameters of the CERES model in the decision support systems for agrotechnology transfer (DSSAT) were calibrated, and its adaptability was validated. The model was applied to simulate and analyze the maize growing period and yield with different sowing dates over 12 years (2012–2023) in the tropical area of Southwest China. The results show that the DSSAT-Maize model demonstrates good adaptability in the southwestern region of China. The model predictions for maize flowering, maturity, and yield were compared with the measured values, yielding R2 values of 0.62, 0.64, and 0.92, d-index values of 0.86, 0.87, and 0.97, and normalized root-mean-square errors (nRMSEs) of 4.53%, 2.92%, and 6.37%, respectively. The verified model was used to assess the effects of different sowing dates on the maize growing period and yield. Sowing between 15 May and 29 May resulted in relatively higher yields with lower coefficients of variation. The whole growing season was shortened by 1.13 days, and the yield was decreased by 3% every 7 days ahead of the sowing date before early May. A delayed planting date after June had a positive effect on maize yields, with an average yield increase of 4% per 7 days of delay. The maize yield was significantly positively correlated with rainfall during the vegetative period and solar radiation during the reproductive period; meanwhile, it was significantly negatively correlated with solar radiation and the maximum temperature during the vegetative period and rainfall during the reproductive period. This study concluded that the sowing date significantly influenced maize’s growth period and yield in the tropical area of Southwest China. Delaying sowing after 15 May can help achieve higher yields, mainly because early sowing leads to insufficient rainfall in the vegetative period, while delayed sowing ensures adequate rainfall and higher total solar radiation.

Single plant segmentation and growth parameters measurement of maize seedling stage based on point cloud intensity

Maize growth parameters are key pieces of information describing the growth, development and yield of plants, and they are of great significance for high quality and high yield maize breeding. Plants counting, row spacing, and plant spacing are closely related to maize sowing quality and yield. Plant height is closely related to maize photosynthetic rate and biomass. The main problem with measuring phenotypic parameters during the maize seedling stage is that maize plants are small, making it difficult to segment maize plant point clouds from ground point clouds, and there is a lack of automatic methods for measuring growth parameters. A point cloud intensity segmentation and improved Euclidean clustering method for single plant segmentation was proposed based on terrestrial laser scanning (TLS) technical, and an automatic measuring method of growth parameters of maize seedling stage was realized. First, TLS was used to scan maize plants at two planting densities at V1 (first leaf is fully expanded) and V2 (second leaf is fully expanded) stages. Second, the segmentation based on point cloud intensity method and the improved Euclidean clustering single plant segmentation method were used to achieve the segmentation of a single maize plant. Finally, the automatic measurement of maize plants counting, row spacing, plant spacing, and plant height were realized. When plants counting of maize, the percentage error was lower than 1.70%. In the measurement of row spacing, plant spacing and plant height of maize plants, the mean absolute percentage error (MAPE) were lower than 1.50%, 5.50% and 3.10%, respectively. These results demonstrate that the point cloud intensity segmentation and growth parameters measurement method is feasible for maize V1 and V2 stages and different planting densities. The automatic measurement values of the number of maize plants, row spacing, plant spacing and plant height has high measurement accuracy and small error. This study provides a rapid, automatic and accurate measurement method for researchers to measure maize growth parameters.

Soil Dynamics in Carbon, Nitrogen, and Enzyme Activity Under Maize–Green Manure Cropping Sequences

The diversification of cropping sequences has a positive impact on soil organic carbon, while improving nutrient cycling and crop yields. The objective of this research was to assess amylase, cellulase, C and N dynamics, and maize yield on a low fertility oxisol in the Brazilian Cerrado. The experiment was conducted under field conditions during three maize crop succession cycles. The treatments consisted of cultivating maize during the summer, after sorghum and lablab cropped as green manure and fallow during the winter. Higher maize yields were achieved by sorghum–maize succession compared to monocropping, due to higher N fertilizer and biomass inputs to topsoil. Sorghum–maize succession also provided a higher proportion of stable C and N compared to other successions. Maize yields declined as tropical soil fertility intrinsically decreased along three crops succession cycles. Cellulase activity decreased over time, whereas amylase activity increased as the plant residues were already in advanced stages of decomposition. The sorghum–maize crop succession stood out compared to lablab and fallow as it provided the highest maize yields, while maintaining higher C and N levels, and amylase activity. This better performance was likely due to larger amounts of incorporated biomass and better mineral N fertilizer management.

Cowpea (Vigna unguiculata (L.) - maize (Zea mays L.) intercropping and fertilizer application affected maize yield and yield components in Guinea Savannah agro-ecological zone of Ghana

ABSTRACT Field studies were conducted to evaluate the effects of compost, NPK fertilizer and maize-cowpea intercropping on maize grain yield during the 2021 and 2022 cropping seasons at Botanga and Golinga in the Northern Region of Ghana. Five levels of spatial row arrangements and three levels of fertilizer types were evaluated as a 5 × 3 factorial in a randomized complete block design with three replications. Data were subjected to ANOVA using GenStat statistical package, 13th edition, and means were separated using least significant difference and Duncan multiple range test at 95% confidence level and presented in tables. The interaction between maize-cowpea intercropping and fertilizer application had significant (p < 0.05) effects on maize grain yield. Maize grain yields were relatively increased by 1M1C intercropping pattern grown with NPK fertilizer at Botanga in 2021 (4194 kg ha−1) and 2022 (4207 kg ha−1) and at Golinga in 2021 (3933 kg ha−1) and 2022 (4001 kg ha−1) with a significant difference between the two experimental locations. It was observed that the role of cowpea in soil enrichment, high plant densities and yield components largely contributed to the high grain yield of maize in the 1M1C intercropping pattern, which could be recommended to farmers.

Maize Morphophysiological Changes Modulated by Cover Crops Rotation in Northeast Brazil

Cover crops have gained attention due to their potential benefits for the soil and physiological performance of subsequent crops. This study aimed to evaluate the physiological and productive aspects of maize grown in succession to cover crops in northeastern Brazil. A randomized complete block design with four repetitions was employed, in which the treatments consisted of the following cover crops: sunn hemp, spectabilis, pigeon pea, Brachiaria sp., jack bean, millet, and fallow. Physiological aspects and production components of maize were evaluated at the tasseling (VT) and smooth grain (R3) phenological stages. Millet cover increased carotenoid content in maize leaves by up to 78% at R3. Maize grown after pigeon pea, millet, and Brachiaria sp. showed up to 42% greater CO2 assimilation efficiency compared to jack bean. Carboxylation efficiency increased by up to 34% in maize grown after millet and Brachiaria sp., while water use efficiency improved by up to 76% in maize after sunn hemp and pigeon pea at R3. Sunn hemp, spectabilis, and jack bean reduced soil temperature by 2 °C compared to fallow. The highest maize yield was observed after jack bean, with an 8% increase over fallow. These findings demonstrate the benefits of incorporating cover crops into maize cultivation systems in the semi-arid region of Brazil.

Mean Performance and Heterotic Pattern of Maize (Zea mays L.) Inbred Lines Adapted to Sub-humid Central Highland of Ethiopia

In spite of abiotic and biotic stresses and low availability of high-yielding cultivars restrict potential production of maize, it is a major food crop in Africa. To overcome this production barrier, promising germplasm must be chosen, combining ability must be understood, and heterotic groups must be formed in order to generate high-yielding maize varieties. The study set out to evaluate plant height, ear height, ear diameter, thousand seed weight, kernel per row, kernel row per ear, and number of ear per plant in order to assess the performance evaluation and heterotic pattern of inbred lines. In 2019, twenty-six inbred lines and two single cross testers were crossed using a line by tester mating design to create fifty-two three way cross F1 hybrids. The experiment, which used an alpha lattice design with two replications, was conducted at the Ambo and Kulumsa Agricultural Research Centers during the 2020 cropping season. Analyses of variance revealed that among the parameters with significant mean squares arising from crosses and lines both within and across locations were grain yield, anthesis date, silking date, plant height, ear height, kernel row per ear, and number of ears per plant. Because of the lines, testers, and crossings for grain yield, anthesis date, silking date, plant height, ear height, kernel row per ear, and number of ear per plant, the line x tester ANOVA results revealed significant mean squares. Due to line x site, line x tester, tester x site, and line x tester x site, there was a noticeable difference in plant height, ear height, and the number of ears per plant. This proved that different environment have different selection criteria for materials and different performance levels. This genetic study Categorized, L1, L22, and L24 under heterotic group A (CEL08008/CEL08047), while L8, L10, L14, L17, L20, and L26 were placed under heterotic group-B (CEL08024/CML561).

Plastic mulching enhances maize yield and water productivity by improving root characteristics, green leaf area, and photosynthesis for different cultivars in dryland regions

Uneven precipitation during the growing season and frequent seasonal droughts on the Loess Plateau in Northwest China adversely affect crop production and water use efficiency. While plastic mulching (PM) has been used to alleviate water stress, few studies have examined the traits maize cultivars need to adapt to the altered water environment under PM and achieve high yields. A two-year field experiment was conducted to assess the root characteristics and aboveground growth traits of three widely used high-yielding maize cultivars—Zhengdan 958 (ZD), Huanong 138 (HN), Heboshi 122 (HBS)—under no mulching (NM) and PM conditions. Among the three cultivars, HBS had the highest root system indices—root length density (RLD), root surface area density (RSD), and root biomass—in the topsoil (0–40 cm), followed by ZD and HN under both NM and PM conditions. Under NM, HBS_NM treatment exhibited strong water absorption, improving photosynthesis and yield, making it suitable for drought conditions. Under PM, topsoil moisture increased significantly, with root system indices increasing by 22.5–36.1 % for RLD, 30.2–36.1 % for RSD, and 25.2–36.5 % for root biomass across the cultivars compared to NM. While ZD_PM did not have the highest root system indices under PM, it exhibited higher green leaf area index (4.5–7.5 %), chlorophyll content (2.8–8.6 %), and photosynthetic rate (6.0–14.5 %), resulting in the highest aboveground biomass and yield among the treatments. These findings suggest ZD is better adapted to the enhanced soil moisture under PM. Future research should focus on breeding genotypes that thrive under PM conditions, emphasizing traits such as larger leaf areas and higher photosynthetic rates to boost crop productivity in rainfed areas.

Selectivity of new generation herbicide ‘Tembotrione’ under conservation agriculture-based maize (&lt;i&gt;Zea mays&lt;/i&gt;) in maize-wheat-mungbean cropping system

An experiment was conducted at the ICAR-Indian Agricultural Research Institute in New Delhi during the rainy (Kharif) seasons of 2021–22 and 2022–23. The study aimed to evaluate the weed control efficiency of low dose new generation herbicide: tembotrione (34.4% SC) as a component of integrated weed management (IWM), on zero-till (ZT) and conventional till (CT) maize (Zea mays L.). The treatments were comprised of conventional tillage maize (M1: CT-M), conventional tillage maize with green manure from preceding green gram (M2: CT-M+GM), zero tillage maize with residue retention at 3 t/ha (M3: ZT-M+R), zero tillage maize with Sesbania co-culture as brown manuring (cover crop) (M4: ZT-M+BM) in the main plot and five weed control treatments, viz S1: Un- weeded check, S2: Pre +1 HW, S3: Pre + Post (tembotrione) @120g/ha, S4: Pre+ Post (Premix of Mesotrione+ Atrazine) @120 g/ha, S5: Weed free check (WFC) in the sub-plots were evaluated in split-plot design. It was ob- served that ZT-M+BM caused a considerable reduction in the population of broad-leaf weed, narrow leaf weed with sedges and total weeds (28.4% reduction at 60 days after sowing) compared to M1. The results also revealed that the sequential application of atrazine @750g/ha+pendimethalin @750g/ha(pre) followed by (fb.) tembotrione (34.4% SC) @120 g/ha (post) among the herbicide options reduced the weeds population (78.5%) and dry weight (81.3%) significantly than the un-weeded control (UWC). Maize yield attributes were higher in ZT with Sesbania co-culture (ZT-M+BM) than conventional-tilled treatments (CT-M). The application of atrazine @750g/ ha+pendimethalin @750g/ha (pre) fb. tembotrione @120 g/ha (post) combined with ZT-M+BM resulting in higher maize yield (6.88 t/ha) which was comparable with that in weed-free check (WFC). The post emergence (PoE) ap- plication of tembotrione (34.4% SC) @120 g/ha recorded highest weed control efficiency (86.2%), weed control in- dex (88.1%) and lowest value of weed index (7.04) when applied in the ZT-maize with sesbania as a cover crop. Therefore, combining zero tillage (ZT) with brown manure (Sesbania), along with atrazine and pendimethalin (@750g/ha each) as pre-emergence herbicides, and tembotrione (@120g/ha) as a post-emergence herbicide is recommended for effective weed control and high maize productivity in the North-Western Indo-Gangetic plains (IGP).

Rapid and Sensitive On-site Nucleic Acid Detection of Three Main Fusarium Pathogens of Maize Stalk Rot Based on RPA-CRISPR/Cas12a.

Maize stalk rot is a soil-borne disease that poses a serious threat to maize production worldwide, with the most significant cause being fungal stalk rot. The development of a visual and rapid detection method for the maize stalk rot pathogen is significant for its prompt and accurate identification, enhancing agricultural production efficiency, and implementing timely preventive measures. These measures will help safeguard the maize yield and quality, ultimately reducing agricultural losses. In this study, we aimed to develop an efficient method to detect maize stalk rot pathogens. We focused on three pathogenic fungi commonly found in maize-producing regions worldwide: Fusarium verticillioides, Fusarium proliferatum, and Fusarium graminearum. Based on TEF-1α, we developed a rapid detection technique using RPA-CRISPR/Cas12a, combined with test strips to develop an on-site rapid visual detection test for these pathogens. The method showed detection sensitivity for F. verticillioides, F. proliferatum, and F. graminearum within 20 min at concentrations of 7.8 pg/μL, 0.11 ng/μL, and 0.13 ng/μL, respectively. The sensitivity increased with increasing reaction time. Testing of field disease samples indicated that the method is effective in detecting nucleic acids obtained through crude extraction methods. In conclusion, we developed a visually rapid detection technology that does not rely on complex instruments and equipment for the on-site early detection of F. verticillioides, F. proliferatum, and F. graminearum in the field to implement effective control measures, ensuring stable and high maize yields.

Multivariate Analysis of Grain Yield and Main Agronomic Traits in Different Maize Hybrids Grown in Mountainous Areas

Inconsistent reports exist on the relationships between key agronomic traits and maize yield. We performed a multivariate analysis of yield and 10 agronomic traits in 59 hybrids to explore maize yields in mountainous areas. The yield per plant (YP) was significantly and positively correlated with kernel weight (KW), growth period (GP), and kernel row number (KRN). KW and KRN had positive effects on YP, whereas kernel rows per ear (KRE) had a negative effect. GP indirectly affected YP. GP, KW, KRN, and ear length (EL) showed the highest grey relational degree with YP. The first four principal components cumulatively accounted for 73.36% of variation. EL, KW, plant height (PH), ear height (EH), GP, KRN, and YP contributed positively to the variation, whereas KRE, shelling percentage (SP), bald-tip length (BTL), and ear girth (EG) contributed negatively. Based on trait similarity, the 59 maize hybrids were classified into two clusters, Clusters I and II. A total of 11 traits were grouped into four clusters, Clusters A–D. Cluster D included KW, GP, KRN, EL, EH, PH, and YP, and the 22 maize hybrids in Cluster I performed better in these traits. These results provide a theoretical basis for the breeding of high-yield maize varieties in mountainous areas.

Maize/soybean intercropping with nitrogen supply levels increases maize yield and nitrogen uptake by influencing the rhizosphere bacterial diversity of soil.

Intercropping practices play a crucial role in enhancing and maintaining the biodiversity and resiliency of agroecosystems, as well as promoting stable and high crop yields. Yet the relationships between soil nitrogen, microbes, and yield in maize cultivated under maize/soybean intercropping systems remain unclear. To fill that knowledge gap, here we collected maize rhizosphere soil at the staminate stage after 6 consecutive years of maize/soybean intercropping, to investigate how intercropping and nitrogen application rates affected nitrogen utilization by crops and soil microbial community composition and function. We also examined correlations of those responses with yields, to clarify the main ways that yield is enhanced via intercropping and by nitrogenous fertilizer gradient changes generated by different nitrogen application rates. The amount of applied fertilizer was 240 kg N ha-1 was best for obtaining a high maize yield and also led to the greatest nitrogen-use efficiency and bacterial diversity. Under the same N application rate, intercropping increased the maize yield by 31.17% and soil nitrogen (total, ammonium and nitrate nitrogen) by 14.53%, on average, in comparison to monocropping. The enrichment of Gemmatimonas and Bradyrhizobium significantly increased the soil nitrogen content, and a greater relative abundance of Sphingomonas and Gemmatimonas increased the maize yield, whereas enrichment of Candidatus_Udaeobacter and Bradyrhizobium decreased it. The benefits of intercropping mainly arise from augmenting the abundance of beneficial microorganisms and enhancing the efficiency of N use by crop plants. This study's findings are of key importance to bolster the stability of agro-ecosystems, to guide the scientific rational use of nitrogen fertilizers, and to provide a sound theoretical basis for achieving the optimalmanagement of intensive crop-planting patterns and green sustainable development.

Selection of Maize Hybrids Resulting from Line × Tester Crossing Tolerant to Drought Stress

Efforts to enhance maize productivity in regions like Madura Island, Indonesia, plagued by low yields due to drought stress, necessitate the development of resilient and high-yielding maize hybrids. Employing the line x tester method represents a promising approach to breed varieties tolerant to drought stress. This study aims to identify drought-tolerant maize hybrids derived from line x tester crosses. The research utilized a Randomized Complete Block Design (RCBD) with 40 genotypes replicated three times, totaling 120 experimental units. Drought stress was imposed following the CIMMYT method, wherein irrigation was provided at field capacity from 0 to 40 days after planting (DAP) at 10-day intervals, while drought stress commenced from 50 DAP until harvest. Under optimal conditions, irrigation occurred every 10 days until 80 DAP. Key observation parameters included plant height, days to 50% tasselling, harvest age, ear height, ear length, ear diameter, kernel weight per plant, 1000-kernel weight, and production per hectare. Results indicated several adaptive hybrid maize genotypes for both normal and drought conditions, as discerned by the Stress Tolerance Index (STI), including G2, G12, G13, G14, and G15. Moreover, hybrids G2, G18, G19, G21, and G24 exhibited notable drought tolerance based on the Stress Susceptibility Index (SSI). These findings underscore the potential of employing the line x tester method in breeding resilient maize hybrids tailored to mitigate the adverse impacts of drought stress, thereby fostering agricultural sustainability in resource-constrained environments like Madura Island.

Gypsum and organic materials improved soil quality and crop production in saline-alkali on the loess plateau of China

Arable soil and crop productivity are severely affected by salinization. Therefore, soil amendments are an important measure for improving saline-alkali soil for agricultural development. Desulfurized gypsum is a common soil amendment that has been used repeatedly alongside organic materials to improve the biological, physical, and chemical properties of saline soil. This study takes the typical saline-alkali farmland soil in Yulin as the research object, and five treatments were established: a blank treatment (CK), a single application 2.5 t ha−1 of desulfurized gypsum (T), 2.5 t ha−1 of desulfurized gypsum and 1.5 t ha−1 of green manure (TL), application 2.5 t ha−1 of desulfurized gypsum and 1.5 t ha−1 of straw (TS), and 2.5 t ha−1 of desulfurized gypsum and 1.5 t ha−1 of organic fertilizer (TV). The results show that the TV treatment achieved a significant improvement in soil nutrients, organic carbon, enzyme activity, and maize yield. In 2022 (2023), the compared of organic matter, TN, TP, TK, AP, and AK increased significantly compared with the CK treatment when the TV treatment was applied. Soil phosphatase activity (SPA), soil urease activity (SUA) and soil sucrase activity (SSA) significantly higher in the TV treatment compared with the other treatments and increased significantly over the two-year period. Furthermore, soil organic carbon (SOC), easily oxidizable organic carbon (EOC), dissolved organic carbon (DOC) and microbial biomass carbon (MBC) also significantly increased with the 2022 and 2023 TV treatments. Correlation analysis revealed a positive relationship between maize yield and soil nutrients, organic carbon, and enzyme activity (P &amp;lt; 0.05). Thus, the TV treatment was determined to be the optimal treatment for soil improvement. This conclusion was supported by analyses performed using membership function analysis, gray correlation analysis, and entropy TOPSIS model evaluation. Therefore, this method increases soil quality, improves soil fertility, achieves high maize yields, and provides a scientific basis for enhancing and utilizing saline-alkali soil in the Loess Plateau.

Meta-Analysis of the Effects of Straw Incorporation on Maize Yield and Water Use Efficiency in China under Different Production Conditions

Maize plays a crucial role in China’s grain production, with a cultivation area reaching 44.22 million hectares and an annual yield of 289 million tons in 2023. However, the challenge remains on how to further increase maize yield and water use efficiency (WUE) without adding to the environmental burden. To systematically evaluate the impact of straw incorporation under varying production conditions on maize yield and WUE, this study collected experimental data from multiple locations across China. A meta-analysis was conducted to compare the effects of straw incorporation versus no incorporation, and the main influencing factors were identified using correlation analysis and a random forest model. The results indicate that straw incorporation significantly enhances both maize yield and WUE, with the most pronounced improvements observed under conditions of an average growing season temperature of 19–23 °C, soil pH of 6.5–7.5, low initial soil organic matter content, and deep plowing for straw incorporation. Additionally, moderate nitrogen application rates and straw incorporation amounts (9000–15,000 kg·ha−2) also significantly boost maize yield and WUE. Field management practices and meteorological conditions are identified as the primary factors affecting maize yield and WUE under straw incorporation conditions. Therefore, straw incorporation stands out as an effective agricultural practice for achieving high maize yields and efficient resource utilization. The findings of this study provide valuable insights for global food security and the sustainable development of agriculture.

Maize plant height automatic reading of measurement scale based on improved YOLOv5 lightweight model.

Plant height is a significant indicator of maize phenotypic morphology, and is closely related to crop growth, biomass, and lodging resistance. Obtaining the maize plant height accurately is of great significance for cultivating high-yielding maize varieties. Traditional measurement methods are labor-intensive and not conducive to data recording and storage. Therefore, it is very essential to implement the automated reading of maize plant height from measurement scales using object detection algorithms. This study proposed a lightweight detection model based on the improved YOLOv5. The MobileNetv3 network replaced the YOLOv5 backbone network, and the Normalization-based Attention Module attention mechanism module was introduced into the neck network. The CioU loss function was replaced with the EioU loss function. Finally, a combined algorithm was used to achieve the automatic reading of maize plant height from measurement scales. The improved model achieved an average precision of 98.6%, a computational complexity of 1.2 GFLOPs, and occupied 1.8 MB of memory. The detection frame rate on the computer was 54.1 fps. Through comparisons with models such as YOLOv5s, YOLOv7 and YOLOv8s, it was evident that the comprehensive performance of the improved model in this study was superior. Finally, a comparison between the algorithm's 160 plant height data obtained from the test set and manual readings demonstrated that the relative error between the algorithm's results and manual readings was within 0.2 cm, meeting the requirements of automatic reading of maize height measuring scale.