Maize Stem Research Articles

Genome-Wide Identification and Analysis of Carbohydrate-Binding Modules in Colletotrichum graminicola

Colletotrichum graminicola is the causative agent of both maize stem rot and leaf blight, which are among the most damaging diseases affecting maize. Carbohydrate-binding modules (CBMs) are protein domains that lack catalytic activity and are commonly found alongside carbohydrate-hydrolyzing enzymes in fungi. A comprehensive examination of the C. graminicola TZ-3 genome resulted in the identification of 83 C. graminicola CBM (CgCBM) genes, which are characterized by distinct gene structures and protein motifs. Subcellular localization analysis revealed that the majority of CgCBM proteins were localized in the extracellular space. Investigation of the promoter regions of CgCBM genes uncovered a variety of responsive elements associated with plant hormones, including abscisic acid and methyl jasmonate response elements, as well as various stress-related response elements for drought, cold, defense, and other stress factors. Gene ontology analysis identified the primary functions of CgCBM genes as being linked to polysaccharide metabolism processes. Furthermore, the 83 CgCBM genes exhibited varying responses at different time points during C. graminicola infection, indicating their contribution to the fungus–maize interaction and their potential roles in the fungal pathogenic process. This study provides essential insights into CgCBMs, establishing a crucial foundation for further exploration of their functions in the mechanisms of fungal pathogenicity.

Intercropping generates trait plasticity, which corresponds with year‐to‐year stability in productivity

Abstract Environmentally friendly approaches to increasing food production include using the positive effects of plant biodiversity, such as in intercropping. Functional traits are key drivers of these positive effects, in part because variation in functional traits can increase niche partitioning. However, we know little about how variation in functional traits affects the long‐term stability of yield in agroecosystems. We conducted a 5‐year field experiment with five different cropping systems; maize/peanut, maize/soybean intercropping, and maize, peanut and soybean monocultures. We compared the productivity of monocultures to intercrops and then compared plasticity in functional traits at different rates of nitrogen supply between the cropping systems. Intercropping generated plasticity, measured here as the inverse of the coefficient of variation, in three functional traits of maize (height, stem diameter and ear height), which probably increases above‐ground spatial niche differentiation, and decreases the intraspecific competition of maize. Intercropping also increased the stability of grain yield and above‐ground biomass. Plasticity in functional traits of maize correlated positively with year‐to‐year temporal stability (CV−1) of grain yield and biomass of maize and with the total productivity of the agroecosystem. Synthesis and applications. Our study provides evidence of the greater productivity and temporal stability of species‐diverse intercropping systems. Interspecific interaction‐induced plasticity suggests a unique mechanism for biodiversity effects on ecosystem function, which adds to our understanding of fixed, or inherent, variation in traits among genotypes or species. Theoretically, our findings provide novel insights into how interspecific interactions contribute to ecosystem service, especially in yield temporal stability, by increased trait plasticity of the dominant crop, maize. The results also had implications for applying intercropping in the sustainable management of food‐production systems with the use of more crop species. Greater stability in production has the potential to provide a stable income for farmers.

In vitro evaluation of maize varieties on the development and reproduction of Chilo partellus (Lepidoptera: Crambidae)

In vitro experiments were conducted to evaluate the developmental and reproductive responses of Chilo partellus on different maize varieties in the Pesticide Toxicology and Application Technology Laboratory, Sindh Agriculture University, Tandojam. The maize stem borer, C. partellus, is a highly destructive insect pest that severely affects both fodder and cultivated crops worldwide. Although pesticides provide limited control of early infestations, they are ineffective against internal feeders and pose environmental risks. In contrast, utilizing resistant maize cultivars offers a sustainable, ecologically safe, and socially acceptable pest management strategy. The study revealed significant differences in the survival rates and developmental durations of C. partellus between hybrid and conventional maize under laboratory conditions. On conventional maize, the total developmental period ranged from 46.22 to 69.34 days (mean: 57.78 ± 11.56 days), whereas on hybrid maize, it ranged from 26.87 to 40.99 days (mean: 33.93 ± 7.06 days). Each developmental stage was shorter on hybrid maize. Females survived longer than males on both maize varieties, but their lifespan was notably shorter on hybrid maize. Regarding reproductive traits, C. partellus showed higher mean fecundity on conventional maize (604 ± 104.67 eggs, range: 500.11-709.44) compared to hybrid maize (302 ± 95.06 eggs, range: 207.44-397.56). Egg fertility was also significantly higher on conventional maize (mean: 55.44 ± 1.81%) compared to hybrid maize (mean: 24.61 ± 1.77%). Statistical analysis confirmed significant differences in developmental durations and reproductive traits between the two maize varieties. These findings highlight the potential of hybrid maize as a resistant cultivar against C. partellus.

Comparative Study of Zinc Concentration in the Root, Stem, and Leaf of Maize (Zea mays) Grown on Soil Collected From Several Dumpsites in Anyigba, Nigeria

Open dumpsites are becoming a major global concern in developing countries, causing heavy metal pollution, and posing a serious threat to human and plant health. This study assessed the zinc (Zn) concentration in the roots, stems, and leaves of maize plants growing on various dumpsite soils in Anyigba (Redeem, Market, and Anokwu). The plant tissues were tested for Zn using an Atomic Absorption Spectrophotometer (AAS). The study found that plants grown on a dumpsite had considerably higher Zn concentrations in their roots, stems, and leaves compared to the control site (p<0.05). The concentration of zinc ranges in the following sequence: Control (0.23 mg/kg)>Anokwu (0.62 mg/kg)>Market (0.63 mg/kg)>Redeem (0.80 mg/kg) for Stem; Control (0.34 mg/kg)>Market (0.68 mg/kg)>Anokwu (0.82 mg/kg)>Redeem (1.08 mg/kg) for Leaf; Control (0.66 mg/kg)>Anokwu (0.68 mg/kg)>Market (0.98)>Redeem (1.00 mg/kg). Zinc's bioconcentration factor (BCF) decreased in the following sequence among dumpsites: Anokwu (0.32 mg/kg) > Market (0.25 mg/kg) > Control (0.18 mg/kg) > Redeem (0.14 mg/kg), all of which exceeded WHO permitted levels. Bioaccumulation concentration (BAC) values range between 0.39 and 0.78 mg/kg, suggesting that maize plant is an excluder, while translocation factor (TF) values were all above 1, indicating that the plants translocate heavy metals from roots to shoots. Our study highlights the critical need for monitoring heavy metal contamination in food crops, especially in regions with open dumpsites, to protect public health. Given the potential risks of zinc bioaccumulation, effective measures are required to mitigate exposure, including soil remediation and the use of cleaner, safer agricultural practices. This research contributes to understanding the environmental and health implications of zinc pollution, emphasizing the urgency of addressing the risks associated with open dumpsites.

Tissue-specific chromatin accessibility and transcriptional regulation in maize cold stress response.

Maize, a vital crop globally, faces significant yield losses due to its sensitivity to cold stress, especially in temperate regions. Understanding the molecular mechanisms governing maize response to cold stress is crucial for developing strategies to enhance cold tolerance. However, the precise chromatin-level regulatory mechanisms involved remain largely unknown. In this study, we employed DNase-seq and RNA-seq techniques to investigate chromatin accessibility and gene expression changes in maize root, stem, and leaf tissues subjected to cold treatment. We discovered widespread changes in chromatin accessibility and gene expression across these tissues, with strong tissue specificity. Cold stress-induced DNase I hypersensitive sites (coiDHSs) were associated with differentially expressed genes, suggesting a direct link between chromatin accessibility and gene regulation under cold stress. Motif enrichment analysis identified ERF transcription factors (TFs) as central regulators conserved across tissues, with ERF5 emerging as pivotal in the cold response regulatory network. Additionally, TF co-localization analysis highlighted six TF pairs (ERF115-SHN3, ERF9-LEP, ERF7-SHN3, LEP-SHN3, LOB-SHN3, and AS2-LOB) conserved across tissues but showing tissue-specific binding preferences. These findings indicate intricate regulatory networks in maize cold response. Overall, our study provides insights into the chromatin-level regulatory mechanisms underpinning maize adaptive response to cold stress, offering potential targets for enhancing cold tolerance in agricultural contexts.

Regulation of Insect Hormones in Different Types of Diapause in Chilo Partellus (Swinhoe).

Maize stem borer, Chilo partellus (Swinhoe) is a key pest of maize and sorghum. It undergoes both in estivation and hibernation depending on prevailing environmental conditions. Present investigations were aimed to decipher the regulation of ecdysone, 20-hydroxyecdysone (20E) and juvenile hormone III (JH III) during different stages (prediapause, diapause and post-diapause/pupae) of hibernation and estivation as compared to counterpart nondiapause C. partellus. Significant variations were found in the ecdysone, 20E and JH III titers in the hemolymph of different stages of hibernation and estivation over the nondiapause C. partellus. At the prediapause stages of hibernation and estivation, the 20E was greater than the ecdysone. However, the ecdysone and 20E downregulated, while JH III upregulated during prediapause stages of hibernation and estivation as compared to nondiapause larvae. During diapause, 20E decreased in hibernation, and increased in estivation as compared to their respective prediapause stages. The JH III significantly upregulated in diapause stages of hibernation and estivation over the nondiapause larvae. However, it was significantly greater in prediapause and diapause stages of estivation as compared to hibernation strain. During post-diapause stage, the ecdysone and 20E titers were greater in estivation than in the hibernation and nondiapause strains, while JH III was greater in nondiapause than in the hibernation and estivation strains. These findings suggest the crucial role of these hormones in establishing switch between different stages of diapause and metamorphosis in C. partellus, which could further be useful to strategize sustainable management of C. partellus.

Appropriate water and nitrogen supply regulates the dynamics of nitrogen translocation and thereby enhancing the accumulation of nitrogen in maize grains

To improve nitrogen uptake and grain quality in maize, this study explores the dynamic processes of nitrogen accumulation, distribution, and translocation under varying water and nitrogen supplies, aiming to optimize water-nitrogen management practices. Field trials were conducted in Karamay, Xinjiang, in 2022 and 2023, with different irrigation levels (75 % ETc, 100 % ETc, 125 % ETc) and nitrogen application rates (0, 93, 186, 279 kg Nhm−2). The effects of water and nitrogen supply on nitrogen accumulation and distribution in aboveground maize organs were analyzed, and the dynamic characteristics of maize nitrogen accumulation were examined using the characteristic parameters of the Richards nitrogen accumulation equation. The results showed that beyond the W2N2 treatment (irrigation at 100 % ETc and nitrogen application of 186 kg N hm−2), increases in irrigation and nitrogen did not significantly enhance nitrogen accumulation per plant. Under W2N2, high levels of nitrogen were accumulated in maize leaf, stem, bract, cob, and grain. The nitrogen transfer among different organs and their contribution to grain nitrogen showed the following hierarchy: leaf > stem > cob > bract, with the contribution rates to grain nitrogen ranging from 26.16 % to 56.23 % over the two years. The Richards model accurately quantified the dynamic relationship between water-nitrogen supply and crop nitrogen accumulation, with the coefficient of determination (R²) ranging from 0.9864 to 0.9999 and the normalized root mean square error (NRMSE) from 0.70 % to 6.51 %. Optimal water-nitrogen supply significantly reduced the accumulated temperature required for maize to enter the rapid nitrogen accumulation phase and achieve maximum growth rates, while extending the duration of the rapid growth phase and increasing both the maximum growth rate and the average growth rate during this period. Grain nitrogen accumulation was positively correlated with nitrogen accumulation rates, as well as nitrogen accumulation and translocation in various organs. Under suitable irrigation and nitrogen application, the interactive effects of water and nitrogen (W × N) significantly increased both nitrogen accumulation and nitrogen accumulation rates, laying a foundation for nitrogen translocation to grains in the late growth stages and enhancing grain nitrogen accumulation. Thus, appropriate water and nitrogen supply can significantly influence nitrogen accumulation, distribution, and translocation processes in maize, regulating grain nitrogen accumulation. This study provides valuable information for nitrogen accumulation regulation and grain quality improvement in maize in Xinjiang and other regions with similar climatic conditions.

Deep learning applications for real-time and early detection of fall armyworm, African armyworm, and maize stem borer

The application of artificial intelligence for identifying Fall armyworm (Spodoptera frugiperda), African armyworm (Spodoptera exempta), and Maize stem borer (Busseola fusca) is critical due to the threats they pose to global food production. This study aims to evaluate and identify the most accurate and robust DL models in detecting and classifying these three significant agricultural pests. Seven traditional DL models: Convolutional Neural Network, Visual Geometry Group (VGG16), Residual Networks (ResNet50), MobileNetV2, InceptionV3, Deep Neural Network (DNN), and InceptionResNetV2 and the advanced You Look Only Once (YOLOv8) model were trained and tested using pest image datasets. The results showed that all traditional models except DNN had high accuracies ranging from 93.17% (InceptionResNetV2) to 99.43% (MobileNet) in training and testing, with losses ranging from 1.71% (MobileNetV2) to 24.99% (InceptionResNetV2). DNN had a slightly lower accuracy range of 55.27% to 56.39% and a loss range of 85.02% to 89.96% in training and testing. YOLOv8 emerged as the best and most robust model in the pest detection and classification tasks, achieving Precision and Recall scores ranging from 98.4% to 100% on single-class and multi-class classifications, making it highly suitable for real-world pest management applications. This research pioneers the use of DL for the classification and detection of maize stem borer, African armyworm and Fall armyworm, unique and separately addressing a critical gap in agricultural pest management in corn. With early and accurate pest identification, crop protection measures can be implemented efficiently. The findings lead to reduced crop damage and enhanced food security.

Maize Phenotypic Parameters Based on the Constrained Region Point Cloud Phenotyping Algorithm as a Developed Method

As one of the world’s most crucial food crops, maize plays a pivotal role in ensuring food security and driving economic growth. The diversification of maize variety breeding is significantly enhancing the cumulative benefits in these areas. Precise measurement of phenotypic data is pivotal for the selection and breeding of maize varieties in cultivation and production. However, in outdoor environments, conventional phenotyping methods, including point cloud processing techniques based on region growing algorithms and clustering segmentation, encounter significant challenges due to the low density and frequent loss of point cloud data. These issues substantially compromise measurement accuracy and computational efficiency. Consequently, this paper introduces a Constrained Region Point Cloud Phenotyping (CRPCP) algorithm that proficiently detects the phenotypic traits of multiple maize plants in sparse outdoor point cloud data. The CRPCP algorithm consists primarily of three core components: (1) a constrained region growth algorithm for effective segmentation of maize stem point clouds in complex backgrounds; (2) a radial basis interpolation technique to bridge gaps in point cloud data caused by environmental factors; and (3) a multi-level parallel decomposition strategy leveraging scene blocking and plant instances to enable high-throughput real-time computation. The results demonstrate that the CRPCP algorithm achieves a segmentation accuracy of 96.2%. When assessing maize plant height, the algorithm demonstrated a strong correlation with manual measurements, evidenced by a coefficient of determination R2 of 0.9534, a root mean square error (RMSE) of 0.4835 cm, and a mean absolute error (MAE) of 0.383 cm. In evaluating the diameter at breast height (DBH) of the plants, the algorithm yielded an R2 of 0.9407, an RMSE of 0.0368 cm, and an MAE of 0.031 cm. Compared to the PointNet point cloud segmentation method, the CRPCP algorithm reduced segmentation time by more than 44.7%. The CRPCP algorithm proposed in this paper enables efficient segmentation and precise phenotypic measurement of low-density maize multi-plant point cloud data in outdoor environments. This algorithm offers an automated, high-precision, and highly efficient solution for large-scale field phenotypic analysis, with broad applicability in precision breeding, agronomic management, and yield prediction.

Damage and insecticidal control of stem borer (Busseola fusca L; Lepidoptera: Noctuidae) on maize in Halhal Begoss

A maize stem borer (Busseola fusca L) control study was conducted in Halhal Begos with the objectives of assessing the damage caused by the pest and identifying the simple method of control. The treatments used were Furadan 1G, Carbaryl 85%WP, Cymbush 1G and control. The data collected were larval count, dead heart count, tunnel length, per cent infestation at 30 and 45 days after emergency. The larval count was taken from the border rows, and yield was taken from the central row at harvest. All agronomic data, like the date to the heading plant height etc were taken on time. The results of the study showed that all the pesticides used gave good control of the larvae. Furadan gave the highest yield benefit and monetary value compared to the check.

Effects of transgenic modification on the bacterial communities in different niches of maize under glyphosate toxicity

Transgenic glyphosate-resistant maize has emerged as a way to expand the use of glyphosate for weed control. Studying the microbiome in the tissues and rhizosphere soil of transgenic plants is vital for understanding the glyphosate-resistant mechanism and optimizing the transgenic design of crops. In our study, the expression of a mutant cp4epsps gene in transgenic maize, which confers tolerance to glyphosate, was performed using the maize variety Xianyu 335 as the genetically modified acceptor line. This transgenic modification did not affect the initial bacterial community in the leaf, stem, or root of maize, but promoted a differential bacterial community in the rhizosphere soil. Under glyphosate application, the abundance of beneficial bacteria involved in N fixation and P solubilization in plant tissues and the rhizosphere soil of glyphosate-resistance maize were higher than those in the glyphosate-sensitive maize. In contrast, the abundance of pathogens had the opposite trend, suggesting that the enhanced health of transgenic maize prevented microbiome deterioration under glyphosate. The re-inoculation of bacterial strains isolated from glyphosate-resistance maize into the leaf and rhizosphere soil of glyphosate-sensitive maize resulted in an enhanced photosynthetic capacity in response to glyphosate, demonstrating the vital role of specific bacteria for glyphosate resistance. Our study provides important evidence of how transgenic maize tolerance to herbicides affects the bacterial communities across the maize niches under glyphosate toxicity.

Effects of Ascorbic, Citric, and Humic Acids on Maize Stem and Leaf Anatomy

درست التغيرات التشريحية في الأنسجة الداخلية للساق والورقة عند معاملة البذور والنبات بالأحماض لتعزيز النمو والتطور في الذرة الصفراء خلال فصلي الربيع لعامي 2019 و2020. تم تطبيق تصميم القطاعات الكاملة المعشاة بترتيب الالواح المنشقة بثلاثة مكررات. تضمنت الالواح الرئيسة معاملات التغذية الورقية (حامض الأسكوربيك (AA) وحامض الستريك (CA) بتركيز 100 ملغم لتر-1، وكذلك حامض الهيوميك (HA) بتركيز 1 مل لتر -1. تم استخدام الماء المقطر كمعاملة مقارنة. وتضمنت الالواح الثانوية معاملات نقع البذور بنفس المعاملات. كشفت نتائج تحليل المقطع العرضي للساق وجود اختلافات في حجم الحزم الوعائية بين المعاملات المختلفة بالمقارنة مع معاملة المقارنة، وأن التغذية الورقية باستخدام CA أظهرت نتائج متفوقة في كلا الموسمين. كما تفوقت البذور المنقوعة في CA و HA على المعاملات الاخرى. كان هناك تداخل معنوي بين التغذية الورقية بالـ CA ونقع البذور بالماء المقطر في عام 2019، أما في عام 2020 فتفوقت معاملة التداخل بين التغذية الورقية بالـ CA ونقع البذور بالـ HA على بقية المعاملات. ومن المهم أن نلاحظ أن المعاملات كان لها تأثير محدود على بشرة أوراق النبات، مع ملاحظة آثار طفيفة فقط. على سبيل المثال، تسببت المعاملات بالـ AA و CA في حدوث بعض التشوه في أشكال بعض الثغور في البشرة العلوية عند مقارنتها بمعاملة المقارنة. أدت المعاملات باستخدام الـ AA و HA إلى زيادة في حجم خلايا البشرة العادية، مع جدران خلايا أكثر استقامة، بينما في معاملة المقارنة، كانت جدران الخلايا متموجة فضلاً عن ذلك كان هناك زيادة وتوسع في حجم خلايا الفلين والسيليكا في النباتات المعاملة. تسهم هذه الدراسة في فهم التغيرات التشريحية التي تحدث في الأوراق والسيقان خلال فترات الإجهاد في موسم نمو الذرة الصفراء، وتسلط الضوء على التأثيرات المحتملة للمعاملات الحامضية على وظائف النبات.

Farmers Survey to Assess of Yield Loss due to Insect Pests in Maize and their Management Strategies Adopted by Farmers of Baitadi District of Nepal

The loss due to insect-pests is one of the major constraints in crop cultivation. In order to assess the losses due to insect pests, a survey was conducted in Dashrath Chand municipality and Surnaya Rural Municipality of Baitadi district under Prime Minister Agriculture Modernization Project (PMAMP), Maize Zone, Baitadi. A total of 100 household heads were selected among the farmers of maize pocket areas of the Prime Minister Agriculture Modernization Project for interview using a semi-structured questionnaire. The descriptive and comparative analysis was done for the field survey data using Microsoft Excel (MS Excel), and ranking the problems using the Wilcoxon signed rank test using statistical tools Statistical Packages for the Social Sciences (SPSS). Additionally, indexing was used to rank the major insect pests found in the maize field. Results showed that the major problematic insects found in the maize field were fall armyworm (Spodoptera frugiperda), cutworm (Agrotis spp.), maize stem borer (Chilo partellus) and white grub (Phyllophaga spp.) respectively, as ranked by the farmers according to losses caused by them. The indexing identified fall armyworm infestation as the most crucial problem with an index value of 0.85 (I=0.85). Interestingly, the maximum loss was found 37.5% (local variety) and the minimum loss 8.33% (hybrid variety). Farmers responded that the average loss caused by the insect in local and improved varieties was 25.19% and 18.38%, respectively. Thus, it can be concluded that comparatively the local varieties are more affected by insect pests than the improved varieties. All the surveyed farmers were found to be practicing both the physical and cultural methods. However, some farmers (10%) were also found to be using biological method of insect control. None of the farmers in the selected areas were found to be using chemical pesticides. So this research is focused on identifying damage and various management practices that can be adopted to solve the yield loss caused by insect pests.

Influence of IAA and ABA on maize stem vessel diameter and stress resistance in variable environments.

The plasticity of the xylem and its associated hydraulic properties play crucial roles in plant acclimation to environmental changes, with vessel diameter (Dv) being the most functionally prominent trait. While the effects of external environmental factors on xylem formation and Dv are not fully understood, the endogenous hormones indole-3-acetic acid (IAA) and abscisic acid (ABA) are known to play significant signalling roles under stress conditions. This study investigates how these hormones impact Dv under various environmental changes. Experiments were conducted in maize plants subjected to drought, soil salinity, and high CO2 concentration treatments. We found that drought and soil salinity significantly reduced Dv at the same stem internode, while an elevated CO2 concentration can mitigate this decrease in Dv. Remarkably, significant negative correlations were observed between Dv and the contents of IAA and ABA when considering the different treatments. Moreover, appropriate foliar application of either IAA or ABA on well-watered and stressed plants led to a decrease in Dv, while the application of corresponding inhibitors resulted in an increase in Dv. This finding underscores the causal relationship between Dv and the levels of both IAA and ABA, offering a promising approach to manipulating xylem vessel size.

Maize plant growth period identification based on MobileNet and design of growth control system

To address the current inefficiencies and subjective nature of manual observation in maize cultivation, with the aim of achieving high efficiency and productivity, this study focused on the DeMaya D3 maize variety. It proposes a maize growth stage recognition method based on the MobileNet model, which is a lightweight convolutional neural network architecture. The method was tested and achieved recognition accuracies of 0.98, 0.96, 0.92, 0.85, and 0.97 for different growth stages, respectively. Additionally, a maize growth prediction model was developed. Based on data collected from experimental plots regarding maize plant height and stem diameter, the Prophet model and an optimized version of the Prophet model were used to forecast maize growth trends. The Prophet model is an open-source tool for time series forecasting. Comparative analysis was conducted between the predictions of the original Prophet model and the optimized version. The relative errors of the Prophet model predictions were 0.85%, 2.11%, and 0.79%, while those of the optimized Prophet model were 0.76%, 0.47%, and 0.71%. Compared to the Prophet model, the optimized model reduced errors by 0.09%, 1.64%, and 0.08%, respectively. The maize plant growth control system was designed to obtain the information through the collection layer. The decision-making layer judged the soil nutrient absorption and growth status. Finally, the management layer controlled water and fertilizer.

Effects of microplastics and cadmium co-contamination on soil properties, maize (Zea mays L.) growth characteristics, and cadmium accumulation in maize in loessial soil-maize systems

Microplastics (MPs) are pervasive pollutants found in agricultural soils, yet research on the combined impacts of MPs and heavy metals on soil-plant systems remains limited. This study investigates the combined impact of low-density polyethylene (LDPE) microplastics (L: 1 mm, S: 100 μm, 0.1%, 1%) and Cd on soil properties, available Cd content, maize growth, and Cd accumulation by mazie through pot experiments. The findings unveiled notable impacts of the treatment groups, namely MP-L0.1%, MP-S0.1%, MP-L1%, and MP-S1%, on soil organic carbon (SOC), maize height, and catalase (CAT) activity (P < 0.05). The dosage of MPs significantly influenced maize height, MP-S0.1% treatment resulted in a 5.6% reduction, while the other groups had insignificant effects. Particle size and dosage significantly affected SOC and CAT (P < 0.01). The MP-L1% and MP-S1% groups resulted in increases of SOC by 121.5% and 281.0%, respectively. CAT reductions were 32.6%, 62.8%, 41.9%, and 34.9% in MP-L0.1%, MP-S0.1%, MP-L1%, and MP-S1% groups, individually. The Cd treatment induced a significant decrease in soil cation exchange capacity (CEC), maize stem diameter, and root length, accompanied by significant increases in maize plant height, malondialdehyde (MDA), CAT, and superoxide dismutase (SOD) activities. Combined LDPE and Cd contamination had significant effects on maize height and Cd content in leaves. Specifically, MP-L0.1%+Cd, MP-S0.1%+Cd, MP-L1%+Cd, and MP-S1%+Cd reduced maize height by 4.1%, 4.5%, 8.7%, and 13.8%, respectively. The co-presence of LDPE and Cd increased available Cd content in soil while elevating Cd concentration in maize shoots and roots, with a notable 25.5% increase in Cd concentration in maize leaves in the MP-L1%+Cd group compared to the Cd group. Furthermore, LDPE effects on soil-plant systems varied depending on particle size and dosage. This research provides important perspectives on evaluating the concurrent contamination and potential dangers of MPs and toxic metals in soil-plant environments.

Spatial and agronomic stage distribution dynamics of maize stem borers (Lepidoptera) in the Agricultural development Zone B of Niger State, Nigeria

Maize farmers in Nigeria have been facing challenges as efforts towards the cultivation of maize is seriously hampered by insect pest infestation in maize fields, of which stem borers are a major culprit. The study was carried out to identify the species of stem borers present and their abundance in Agricultural development Zone B of Niger State. Farm sites located in Beji, Chanchaga, Paiko and Shanu, were selected and sampled for stem borers, during vegetative, reproductive and harvest stages of the field maize crops. Identification was done using standard taxonomic keys. The results indicated the presence of three species of stem borer belonging to three families. A species each from Noctuidae, Crambidae and Pyralidae consisting of Busseola fusca (n = 1639, 68.24%), Chilo partellus (n = 160, 6.66%) and Eldana saccharina (n = 603, 25.10%) respectively. Generally, all sites had two species of the stem borer (B. fusca and E. saccharina) present in all growth stages of the maize plant during the destructive sampling with the exception of Chilo partellus that was rarely found; occurring only in one site (Beji), all amounting to a total of 2402 stem borers collected during the study period. Among all the growth stages of the maize plants in all sampled sites the level of infestation varied significantly (p&lt; 0.05), in an increasing order: vegetative stage &lt; reproductive stage &lt; harvest stage of the maize plants. The findings of this study suggest that there is a serious stem borer pest infestation in the maize farms of Agricultural development Zone B of Niger state that could pose threats to maize (Zea mays) production in the area; thus, requiring urgent interventions on the parts of all stakeholders.

Detection of maize stem diameter by using RGB-D cameras' depth information under selected field condition.

Stem diameter is a critical phenotypic parameter for maize, integral to yield prediction and lodging resistance assessment. Traditionally, the quantification of this parameter through manual measurement has been the norm, notwithstanding its tedious and laborious nature. To address these challenges, this study introduces a non-invasive field-based system utilizing depth information from RGB-D cameras to measure maize stem diameter. This technology offers a practical solution for conducting rapid and non-destructive phenotyping. Firstly, RGB images, depth images, and 3D point clouds of maize stems were captured using an RGB-D camera, and precise alignment between the RGB and depth images was achieved. Subsequently, the contours of maize stems were delineated using 2D image processing techniques, followed by the extraction of the stem's skeletal structure employing a thinning-based skeletonization algorithm. Furthermore, within the areas of interest on the maize stems, horizontal lines were constructed using points on the skeletal structure, resulting in 2D pixel coordinates at the intersections of these horizontal lines with the maize stem contours. Subsequently, a back-projection transformation from 2D pixel coordinates to 3D world coordinates was achieved by combining the depth data with the camera's intrinsic parameters. The 3D world coordinates were then precisely mapped onto the 3D point cloud using rigid transformation techniques. Finally, the maize stem diameter was sensed and determined by calculating the Euclidean distance between pairs of 3D world coordinate points. The method demonstrated a Mean Absolute Percentage Error (MAPE) of 3.01%, a Mean Absolute Error (MAE) of 0.75mm, a Root Mean Square Error (RMSE) of 1.07mm, and a coefficient of determination (R²) of 0.96, ensuring accurate measurement of maize stem diameter. This research not only provides a new method of precise and efficient crop phenotypic analysis but also offers theoretical knowledge for the advancement of precision agriculture.

Maize stem–leaf segmentation framework based on deformable point clouds

The efficacy of three-dimensional (3D) point clouds in studying crop morphological structures is based on their direct and accurate data presentation ability. With deep-learning integration, organ segmentation from point clouds could serve as the basis for tremendous advancements in organ-level phenotyping. However, despite the potential, the acquisition of a sufficient number of annotated plant point clouds for practical model training remains a major hurdle. To help overcome this limitation, we constructed a 3D point-cloud dataset specifically for maize stem–leaf segmentation encompassing 428 maize plants ranging from 2 to 12 leaves. We also developed a point cloud enhancement strategy that uses highly controllable deformations to improve the morphological diversity of the training set significantly, while preserving the local geometric features of organs. Our dataset supports the generation of abundant training data from a limited number of labelled data, and we also provide a segmentation framework based on the augmented data to validate the efficiency of our enhancement technique. Two labelled data items were randomly chosen from our plant dataset based on every leaf number, yielding 22 labelled data items total, to produce several deformed point clouds for training the PointNet++ semantic segmentation model, as well as the hierarchical aggregation for the 3D instant segmentation (HAIS) model. These models were tested on 406 datasets, where the PointNet++ model secured a 91.93 % mean intersection-over-union (mIoU) in semantic segmentation and the HAIS model obtained an 89.57 % mean average precision (mAP) in instance segmentation. Following post-processing, an instance segmentation result of 93.74 % mAP was achieved with the HAIS model. These findings demonstrate that our method allows for the efficient training of organ segmentation models with minimal labelled data input in a reduced timeframe. Moreover, it offers an effective tool for point-cloud parsing in maize phenotyping research. Our Maize dataset is available from https://github.com/syau-miao/SignleMaizePointCloudDataSet.git, and the source code of our method can be found at https://github.com/yangxin6/Deformation3D.git.

The Management Strategies against Maize Stem Borer, Chilo partellus (Swinhoe) on Maize (Zea mays L.): A Review

The research provides updated information on the effect of different insecticides and biopesticides against maize stem borer (Chilo partellus Swinhoe) were carried out at different areas by different scientists. Combining Imidacloprid and Trichogramma chilonis resulted in significantly decreased leaf injury m-2 (1.32) and dead hearts (4.16%) in several trials done in different agroclimatic zones. With maximum grain yield (39.5 q/ha), imidacloprid + Karanj oil significantly reduced dead heart (2.8%), plant infestation (14.1%), stem tunneling (2.7%), and number of exit holes per plant (0.6). Results of the field bio-efficacy study showed that at, Chloropyrifos 50% + Cypermethrin 5% @2500 g.a.i./ha recorded significantly lower larval populations (1.18 larvae per plant) and a lower percentage of plant damage (9.00%). As per the findings this study suggests the percentage infestation and larval population of Chilo partellus can be minimized by the application of combinations of insecticides and biopesticides.