Maize Seeds Research Articles

Germination Indices and Seedling Growth Parameters in Maize under Salinity Stress with Varying Concentrations of Giberellic Acid (GA)

Salinity stress is one of the factors limiting seed emergence and seedling development in sunflower at New halfa scheme in East of Sudan. A study of two factors pots experiment was conducted during winter season of 2019 to evaluate germination indices and seedling growth characters of maize seeds under salinity stress with varying concentrations of synthetic growth regulator namely (GA3). The experiment was laid out according RCBD with three replications. Treatments consisted of five levels of salinity (0, 0.5, 1.0, 1.5 and 2% ) designated as Na0, Na0.5, Na1.0 ,Na1.5 and Na2.0, and four levels of GA3 were (0, 50,75 and 100 p.pm) designated as G0, G50, G75 and G100, respectively,. The studied parameters include germination indices; daily germination (MDG), daily germination speed (DGS), final germination percentage (FGP), mean emergence time (MET), mean Energy of germination (EE), emergence index (EI), coefficient of uniformity of emergence (CUE) and vigour index (SVI). Also, seedling fresh and dry weight, shoot length and root length were measured, and the shoot/root ratio was calculated. The negative effects of salinity stress significantly decreased germination indices and seedlings growth characters in a dose dependent manner. The results showed that, application of GA3 at medium levels concentration (specify those doses) increased all studied parameters. In conclusion, application of high Ga3 levels enhanced all germination indices and seedlings growth characters while high salinity levels reduced these traits of maize seeds. Such result has made the base for further study that should be conducted in different seasons with different growth regulators involving different parameters of other crops.

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.

Manganese(II)-Enhanced Graphene Oxide Fluorescence Switch-Based Hybridization Chain Reaction for the Enzyme-Free and Sensitive Determination of Bacillus thuringiensis (Bt) in Transgenic Crops

Bacillus thuringiensis, as a special DNA sequence, has been introduced into crops for insect control. At the same time, the safety risk of transgenic crops has received wide concern. Herein, a simple, enzyme-free and sensitive novel nanosensor for the determination of Bacillus thuringiensis by manganese(II)-enhanced graphene oxide (GO) fluorescence switch (Mn(II)-GO-FS)-based hybridization chain reaction (HCR) signal amplification was developed. The high affinity of Mn(II) to oxygen-containing groups in double-stranded DNA and on the surface of GO was able to overcome the steric effect of rigid double chains and drive the efficient adsorption of HCR hairpin probes with sticky ends on GO. The efficient quenching of 6-carboxyfluorescein (FAM) labeled on the HCR hairpin probes guaranteed a low background. The Bacillus thuringiensis acted as a trigger to initiate a cascade of hybridization events between the two metastable HCR hairpin probes (H1 and H2) to polymerize into a nicked long double-helix structure (dsDNA). The products desorbed from the surface of GO and produced strong fluorescence. The results included a wide linear range (0.1 pM-50 nM) and a low detection limit (0.05 pM). This nanosensor was successfully applied to determine Bacillus thuringiensis in maize seeds with spiked recoveries between 97.5% and 103%. The Mn(II)-GO-FS had a simple design and was conveniently used for the determination of other special genes by changing the corresponding HCR hairpin probe sequence. Moreover, this novel nanosensor did not require harsh experimental conditions, operating in a neutral environment.

Factors Influencing the Use of Improved Maize Seed and Participation in the Seed Demonstration Program by Smallholder Farmers in Kwali Area Council Abuja, Nigeria

This study identified the factors influencing the use of improved maize seeds by the smallholder maize farmers and their participation in the National Agricultural Seeds Council (NASC) seed demonstration program (SDP) in the Kwali area. A multistage sample strategy was utilized to obtain 250 cross-sectional data from nine wards (rural settlements) in the study area. The data was analyzed using linear and logistic regression models. The estimation results from the linear model revealed that total farm size and participation in NASC Seed demonstration program significantly influenced the likelihood of smallholder farmers using improved maize seeds in the study area. The logit model indicates that household income and well-being influenced the likelihood of smallholder farmers’ participation in the NASC seed demonstration program. Therefore, the study recommended that the federal government and policymakers should formulate and implement policies and interventions to encourage the use of improved maize seeds in Nigeria.

Development of A Robotic Maize Seed Planter

The automatic maize seed planter design to address the limitations of traditional planting techniques and reduce the lead time in agricultural processes and enhance the output. The research encompasses a comprehensive study of maize sowing techniques, challenges, and advancements in agricultural robotics. The literature review explores the limitations of traditional maize sowing techniques, such as inaccurate seed placement, labor intensiveness, and weather dependence. The construction process involves the integration of a chassis, wheels, sensors, microcontroller, and seed dispensing system. The software component utilizes a custom algorithm to control the movement and seed placement of the robot. Experimental testing and evaluation were conducted to assess the performance of the robot. The accuracy of seed placement was determined by analyzing the deviation from the desired spacing. The efficiency of the robot was measured by comparing the time taken for sowing with traditional methods. The results demonstrated that the automatic maize seed planter achieved high accuracy in seed placement with minimal deviation from the desired spacing. The results validate the effectiveness of the robotic system in addressing the limitations of traditional sowing techniques and demonstrate its potential to revolutionize the agriculture industry. The objectives are to develop a cost-effective, efficient, and accurate maize seed planter and implement the design in the fabrication. Recommendations for further work is real-time mapping and monitoring. Real-time mapping and monitoring of the field can help the robot navigate the field more efficiently and accurately.

Correlation between the quality and health of maize (Zea mays) seeds with flint and floury endosperms produced in the Central Highland Valley of Mexico

The assessment of physiological quality and health in maize seeds is crucial for selecting high-quality genotypes suitable for planting. However, this quality can vary due to different variables, including genotype or endosperm composition. Therefore, the present study aimed to establish a relationship between the physiological quality and health of the nine evaluated maize genotypes. Special attention was given to the dimensions of flint and floury endosperms, following protocols described by ISTA. Additionally, the study aimed to understand the interaction between each assessed variable and its influence on the performance of crops adapted to the Central High Valleys region of Mexico. The results of this study demonstrated that seeds with flint endosperms exhibited superiority in their physiological quality and health compared to those with floury endosperms.

Secondary Metabolites of Bacillus sp. as Antifungal of Seed-borne Pathogen Fungi on Maize Seed Using Blotter Test Method

Background: Seed is a planting material that must have high viability and quality, including being free from pathogens. One of the obstacles in the supply of quality maize seeds is seed-borne fungal pathogen which can affect the quality of maize seeds and cause plant disease. Endophytic bacteria Bacillus sp. has been widely studied to be able to produce secondary metabolites as antifungals. This study aimed to determine the exact concentration of secondary metabolites of endophytic bacteria Bacillus sp. to decrease the infections of seed-borne pathogens fungal on maize seeds using the blotter test method. Methods: This study used a completely randomized design with four concentration levels (10%, 15%, 20%, 25%) and two strain codes of endophytic bacteria Bacillus sp. (Bth-31a and Bth-22). Results: The result of identifying seed-borne fungal pathogen on maize seed included Fusarium sp., Aspergillus flavus, Aspergillus niger, and Rhizopus sp. The Bth-22 treatment with a concentration of 25% could decrease the infection of seed-borne fungal pathogen and had the highest percentage until 50% compared to the control. While the lowest percentage to decrease the infections of seed-borne fungal pathogen occurred in the Bth-31a treatment with a concentration of 10%, which was 32.1% compared to the control. Conclusions: All seed treatments that used secondary metabolites of Bacillus sp. able to decrease the infections of seed-borne fungal pathogen on maize seed compared to the control. In addition, the treatment of secondary metabolites Bacillus sp. is able to increase the germination of maize seeds.

Antifungal efficacy of garlic (Allium sativum L.) on selected crop seed-borne fungi

This study aimed to assess the inhibitory effectiveness of garlic products on fungi associated with cowpea, sorghum, maize, and groundnut seeds. The in-vivo evaluation involved a seed culture bioassay treated with garlic aqueous extract, while the in vitro antifungal activity of the extract on the radial growth of isolated fungi was determined using the agar well diffusion method. The treatments included garlic powder, garlic paste, garlic powder + molasses, garlic aqueous extracts at 100%, garlic aqueous extracts + adjuvant, and Thiram® (a synthetic fungicide). On untreated cowpea seeds, Aspergillus niger was the most frequently isolated fungal species, with an incidence of 61.5%. Cowpea seeds treated with 100% garlic extracts showed zero incidence of fungal colonies, whereas sorghum seeds + garlic aqueous extract displayed only A. niger. The in vitro study revealed that the inhibitory effect of 100% garlic aqueous extracts + adjuvant on the radial growth inhibition of A. niger, A. flavus, and P. chrysogenum was 78.86%, 70.40%, and 67.36%, respectively. In contrast, the inhibition by garlic powder + molasses and the control was significantly lower (p≤0.05) than other treatments. In conclusion, this study suggests that garlic extracts could be a potential source of organically-based natural fungicides for safeguarding crop seeds.

Electrochemical Processes Used to Degrade Thiamethoxam in Water and Toxicity Analyses in Non-Target Organisms

Pesticides ensure greater productivity in less time; however, they spread beyond the perimeters to which they are applied to reach non-target organisms, thereby affecting plant, animal, and human health. Thiamethoxam (TMX) is considered to be one of the main agents responsible for poisoning bees and potentially contaminating surface and groundwater. Conventional water-treatment protocols are unable to degrade thiamethoxam; therefore, electrochemically advanced oxidative processes (EAOPs) have become promising alternatives owing to their ease of operation and cost-effectiveness. Herein, we examined the use of EAOPs to oxidize thiamethoxam in commercial Actara® and analyzed treatment efficiencies through phytotoxicity studies using cucumber and maize seeds as bioindicators. In addition, the cost of each process was analyzed based on the resulting current efficiency. The treated solutions were used to germinate seeds that were analyzed for total protein, hydrogen peroxide, lipid peroxidation (MDA), superoxide dismutase (SOD), and catalase (CAT) activities. EAOPs were found to effectively oxidize TMX, with more than 50% degraded and 80% COD removed under all treatment conditions, even when the commercial product was used. The photoelectro-Fenton process using 10 mg L−1 FeSO4 and 100 mg L−1 H2O2 exhibited the best results, with 79% of the TMX degraded and 83% of the COD removed, additionally exhibiting the lowest estimated operating cost (USD 1.01 dm−3). Higher enzymatic SOD and CAT activities, total protein content, and H2O2 concentration were observed; however, no significant changes in MDA were recorded. This treatment protocol effectively oxidizes TMX and reduces its phytotoxicity in maize and cucumber seedlings.

Endophytic fusarium solani exhibiting potential stress tolerance and enhances growth of maize in South Africa

New technological approaches harness the potential of endophytic fungi as growth promoters, utilizing their bioactive compounds to protect against herbivores, insects, and various unfavourable abiotic stresses, including temperature, salinity, drought, and heavy metals. Zea mays (L.) is considered as a staple food source in many countries including South Africa. Endophytic fungi are natural growth promoters without causing any disease or symptoms of diseases. In the current study, nine endophytic fungi were examined for abiotic stress tolerance and were inoculated in the maize seeds prior to plantation. The construction of the phylogenetic tree was based on consensus sequences (ITS) using endophytic fungi produced three clades with four subgroups. Among the 9 endophytic fungi, only 3 fungal isolates (END 15, MHE 55, RNK 4) grew on 3% and 6% salinity PDA. Boeremia exigua was the only isolate that could withstand 6%. Fusarium solani (MHE 55) survived at low pH. Furthermore, Neurospora sp. (GG 9) and Fusarium solani (MHE 55) grew at 37 ºC. Greenhouse experiments were conducted to establish the growth promoting properties. The highest plant height was observed in the treatment which was inoculated with Fusarium oxysporum (GG 8) followed by Fusarium solani (MHE 55), reaching 46 cm and 44 cm respectively. The significant enhancement in plant height, root weight, fresh weight and leaf size, demonstrate the potential use of the selected isolate as a growth promoter for maize. In contrast Chaetomium (PG 9) and Alternaria (MHE 68) displayed none to limited growth promoting properties. To the best of our knowledge, this is the first report on the potential use of F. solani isolated from South African geranium as a growth promoter. As the world is aiming at a more sustainable and eco-friendly agriculture, the use of such endophytes will contribute to better crop production and protection, hence more food availability. Key words: Fusarium solani, Endophytes, Growth promotion, Maize, Stress tolerance, Boeremia exigua, Chaetomium, Alternaria

Three-dimensional polymer phenylethnylcopper/nitrogen doped graphene aerogel electrode coupled with Fe3O4 NPs nanozyme: Toward sensitive and robust photoelectrochemical detection of glyphosate in agricultural matrix

BackgroundPresently, glyphosate (Gly) is the most extensively used herbicide globally, Nevertheless, its excessive usage has increased its accumulation in off-target locations, and aroused concerns for food and environmental safety. Commonly used detection methods, such as high-performance liquid chromatography and gas chromatography, have limitations due to expensive instruments, complex pre-processing steps, and inadequate sensitivity. Therefore, a facile, sensitive, and reliable Gly detection method should be developed. ResultsA photoelectrochemical (PEC) sensor consisting of a three-dimensional polymer phenylethnylcopper/nitrogen-doped graphene aerogel (PPhECu/3DNGA) electrode coupled with Fe3O4 NPs nanozyme was constructed for sensitive detection of Gly. The microscopic 3D network of electrodes offered fast transfer routes for photo-generated electrons and a large surface area for nanozyme loading, allowing high signal output and analytical sensitivity. Furthermore, the use of peroxidase-mimicking Fe3O4 NPs instead of natural enzyme improved the stability of the sensor against ambient temperature changes. Based on the inhibitory effect of Gly on the catalytic activity Fe3O4 NPs, the protocol achieved Gly detection in the range of 5 × 10−10 to 1 × 10−4 mol L−1. Additionally, feasibility of the detection was confirmed in real agricultural matrix including tea, maize seedlings, maize seeds and soil. SignificanceThis work achieved facile, sensitive and reliable analysis towards Gly, and it was expected to inspire the design and utilization of 3D architectures in monitoring agricultural chemicals in food and environmental matrix.

Phytochemical screening and insecticidal activities of some medicinal plants against the maize weevil, Sitophilus zeamais (Motschulsky) (Coleoptera: Curculionidae)

This study emphasizes the phytochemical study of some locally available botanicals against maize weevils. Nine plant parts were collected from six plant species. The test plant powder (200 g) was suspended sequentially in 600 ml of petroleum ether, chloroform, acetone, methanol, and distilled water for 72 h with frequent agitation. Different concentrations of the crude extracts were applied to maize seeds at rates of 10 ml, 15 ml and 20 ml per 100 g. All treatments with different extracts at different rates of application showed significant differences (p < 0.05) in the cumulative mean percentage mortality of the maize weevil. The seed extract of Maesa lanceolata and Croton macrostachyus and the leaf extract of Clausena anisata showed cumulative percent mortality ranged 95.32–98.02% in 28 days after treatment application. There was no significant difference (p > 0.05) among all treatments for the prevention of F1 progeny emergence. In all extracts, Clausena anisata showed 100% inhibition of F1 progeny emergence. All treatments significantly reduced seed weight loss and damage. The treated maize seeds were germinated with an acceptable germination quality. In conclusion, an increased dosage of the extract resulted in significant mortality in maize weevils. The seed extracts of Maesa lanceolata and Croton macrostachyus and Clausena anisata leaf extract were observed to be the most promising botanical in protecting stored maize against maize weevil.

Synergistic Effects of Chemical Fungicides with Crude Extracts from Bacillus amyloliquefaciens to Control Northern Corn Leaf Blight

In this research, our objective was to investigate the combined impact of microbial extracts and chemical fungicides on Northern corn leaf blight (NCLB), which is induced by Exserohilum turcicum, and the growth-promoting effect of the crude extracts was also determined. NCLB poses a serious threat to global maize production, necessitating sustainable and environmentally friendly solutions. Mycelial growth rate assays were used to assess the single or synergistic effects of microbial crude extracts and chemical fungicides, and the seed-soaking and root irrigation method was used to detect the growth-promoting effect of the crude extracts on maize seedlings. The results revealed an 84.60% inhibition rate of B. amyloliquefaciens gfj-4 against E. turcicum, and with an EC50 of 49.01 mg·L−1 for the crude extracts. Chemical fungicides demonstrated varying toxicity levels, with fludioxonil exhibiting the highest potency. The mixture of the crude extracts and pyraclostrobin at an 8:2 volume ratio displayed the highest toxicity ratio of 1.24, indicating a synergistic effect. The selected combinations exhibited strong synergistic effects. Soaking maize seeds with 80 mg·L−1 of the crude extracts followed by root irrigation with 40 mg·L−1 produced the most significant growth-promoting effect on maize seedlings. This study highlights the potential of microbial crude extracts to enhance the control of NCLB when combined with pyraclostrobin, along with its growth-promoting effects on maize seedlings.

Functional transgenes in Mexican maize: benefits and risks for insect pest management in Mexico and the United States

Abstract Corn earworm (Helicoverpa zea) and fall armyworm (Spodoptera frugiperda) are major migratory pests of maize (Zea mays) in the United States and Mexico. They are primarily controlled in the United States with genetically engineered (GE) maize, while the 25-yr moratorium on cultivating GE maize in Mexico has forced growers to control these pests with insecticides, where maize productivity remains 35% below the world’s average. The United States annually exports 5% of its maize grain to Mexico, where it provides human food and animal feed. This seed is often sown by smallholder growers, leading to plantings of GE transgene-expressing maize and potential hybridization with local landraces. As a result, transgenes are now present in Mexican maize products and landraces. In this study, we examined the F1 offspring of GE maize to better understand the frequency of different transgenes expressed in maize seeds exported to Mexico. We show that exported seed contains numerous transgenes, including an estimated ~68% epsps expressing resistance to the herbicide glyphosate; ~80% pat and bar expressing resistance to the herbicide glufosinate; and ~82% Bacillus thuringiensis (Bt) genes that effectively protect maize plants from several insect pests. We tested 134 samples, including landraces from 10 Mexican states, and found that 35% expressed resistance to glyphosate and 33% to glufosinate. Many samples containing herbicide resistance also expressed 11%–100% functional Bt transgenes, which can effectively reduce the refuge area provided by Mexican maize and increase the Bt-resistant allele frequency. We discuss ways that the introgression of transgenes could provide pest management benefits to Mexican growers but, at the same time, accelerate the development of Bt-resistance in corn earworm and fall armyworm. Our cost-effective screening methods can be used to determine the introgression of functional herbicide resistance and Bt transgenes in maize.

Seeding detection and distribution evaluation using the developed automatic maize seeding machine

Seeding is a time-consuming and labour-intensive process in the detection of maize seeds germination rate. Automatic seeding can reduce labour requirements and improve efficiency. The quality of automatic seeding plays an important role in collecting accurate germination rates. In this research, a newly developed automatic maize seeding machine (AMSM) was used to detect the maize seeds and evaluate distribution by advanced computer vision and analysis methodologies. Three methods were utilized to detect maize seeds after they were loaded into the holes of the seed plate of AMSM: colour segmentation + connected component analysis, support vector machine (SVM) + sliding window, and YOLOV5. The results showed that compared with colour + connected component analysis and sliding window + SVM, YOLOV5 exhibited higher accuracy and improved computational efficiency. When the input image pixel size was 960 × 960, the precision of YOLOV5 + merge-NMS was 97.3 %, the recall was 0.918, the F1-score was 0.945, and the processing time of a single image was 0.38 ms, which is the optimal performance. YOLOV5 + merge-NMS demonstrated robust detection maize seeds in images with different illumination equalization processing. Based on maize seeds detection results, seeding distribution evaluation was realized with an average accuracy of 91.14 %. In addition, the normal seeding of the AMSM was 82.3 %. Utilization of YOLOV5 + merge-NMS enables rapid and precise detection of maize seeding while establishing a basis for accurately calculating seed distribution. The AMSM can meet the requirements of automatic maize seeds detection and distribution evaluation and the developed methodologies have the potential for automatic germination detection.

Hyperspectral imaging combined with GA-SVM for maize variety identification.

The demand for identification of maize varieties has increased dramatically due to the phenomenon of mixed seeds and inferior varieties pretending to be high-quality varieties continuing to occur. It is urgent to solve the problem of efficient and accurate identification of maize varieties. A hyperspectral image acquisition system was used to acquire images of maize seeds. Regions of interest (ROI) with an embryo size of 10 × 10 pixel were extracted, and the average spectral information in the range of 949.43-1709.49 nm was intercepted for the subsequent study in order to eliminate random noise at both ends. Savitzky-Golay (SG) smoothing algorithm and multiple scattering correction (MSC) were used to pretreat the full-band spectrum. The feature wavelengths were screened by successive projection algorithms (SPA), competitive adaptive reweighted sampling (CARS) single screening, and two combinations of CARS-SPA and CARS + SPA, respectively. Support vector machines (SVMs) and models optimized based on genetic algorithm (GA), particle swarm optimization (PSO) were established by using full bands (FB) and feature bands as the model input. The results showed that the MSC-(CARS-SPA)-GA-SVM model had the best performance with 93.00% of the test set accuracy, 8 feature variables, and a running time of 24.45 s. MSC pretreatment can effectively eliminate the scattering effect of spectral data, and the feature wavelengths extracted by CARS-SPA can represent all wavelength information. The study proved that hyperspectral imaging combined with GA-SVM can realize the identification of maize varieties, which provided a theoretical basis for maize variety classification and authenticity identification.

Proposition of empirical equations to describe the kinetics of water absorption by film-coated maize seeds during germination

Maize is a crop widespread in various parts of the world, serving as a source of food for humans and animals and also as a source of energy. Seeds can be attacked by pathogenic microorganisms and, a way to protect them against these attacks, it is to coat them with suitable products. In this paper, empirical equations with 2 and 3 parameters are proposed to describe the kinetics of water absorption by film-coated maize seeds during germination at temperature of 10 °C and atmospheric pressure of 71 cmHg. A total of 14 experiments involving different types of film on the seeds were carried out, plus a control experiment without film coating. A computer program, which automatically fits about 200 functions available in its library to the experimental data, was used for each of the 15 datasets. This program uses non-linear regression to generate a classification of the best-fitted functions, based on the value of the reduced chi-square of each fit performed. The best equations with 2 and 3 parameters obtained in this study were compared with each other, and the one that best described the kinetics of water absorption by the seeds was chosen. Also, the equation chosen in this study was compared with other empirical equations available in the literature. In all comparisons, the equation obtained and proposed in this study showed better statistical indicators than the empirical equations available in the literature. It was also possible to conclude that the film coating treatments did not significantly interfere with the value of the final moisture content (about 35%, w.b.), but influenced the time of the seed germination process (between 24 and 40 days).

Azospirilla and Nitrogen Fertilization to Promote Maize Seed Development and Yield

Aims: This study evaluated the interaction of Azospirillum brasilense (Ab) strains and nitrogen fertilizer doses on maize.&#x0D; Study Design: Laboratory experiment evaluated Ab strains (PCR and PTF) on maize seed germination and vigor (completely randomized design). Field experiment evaluated Ab strains and nitrogen fertilization on maize yield parameters (randomized block design).&#x0D; Place and Duration of Study: The germination and vigor experiment (10 days in April 2019) was implemented in a controlled environment at the Seed Analysis Laboratory of the Universidade Federal de Uberlândia, Brazil. The field experiment (137 days in winter 2019) was implemented at the Fisioplant Research Station (Uberlândia, Brazil) under commercial maize crop management.&#x0D; Methodology: In controlled conditions (laboratory), 200 seeds of maize (K9105VIP3, Riber KWS Seeds) were incubated (25 °C) with the Ab strain solutions for germination and vigor evaluations. In the field, 60,000 plants ha-1 (0.5 m space between sowing lines) of maize were cropped under combinations of nitrogen fertilizer and volumes of Ab strains (treatments) for leaf nitrogen, SPAD index, leaf count, fresh and dry maize shoot biomass, one-thousand grains weight, grain rows per maize ear, productivity (kg ha-1).&#x0D; Results: Treatment with 100 mL ha-1 of Ab PFT strain increased maize seed germination and vigor more than Ab PCR strain and control (no-inoculation or fertilizer). The number of grain rows of the 100% N + 150 mL ha-1 of Ab PFT strain and the maize shoot dry mass of the 100% N (no-inoculation) were higher than the control. The treatments did not affect the SPAD index, weight of one thousand grains, fresh maize shoot biomass, or productivity.&#x0D; Conclusion: Using Ab with nitrogen fertilizer is a promising strategy to improve maize crop responses; however, more studies are needed to detail the ideal management of Ab strains for maize crops and yield construction.

Non-Destructive Classification of Maize Seeds Based on RGB and Hyperspectral Data with Improved Grey Wolf Optimization Algorithms

Ensuring the security of germplasm resources is of great significance for the sustainable development of agriculture and ecological balance. By combining the morphological characteristics of maize seeds with hyperspectral data, maize variety classification has been achieved using machine learning algorithms. Initially, the morphological data of seeds are obtained from images, followed by the selection of feature subsets using Recursive Feature Elimination (RFE) and Select From Model (SFM) methods, indicating that features selected by RFE exhibit better performance in maize seed classification. For hyperspectral data (350–2500 nm), Competitive Adaptive Re-weighted Sampling (CARS) and the Successive Projections Algorithm (SPA) are employed to extract feature wavelengths, with the SPA algorithm demonstrating superior performance in maize seed classification tasks. Subsequently, the two sets of data are merged, and a Random Forest (RF) classifier optimized by Grey Wolf Optimization (GWO) is utilized. Given the limitations of GWO, strategies such as logistic chaotic mapping for population initialization, random perturbation, and final replacement mechanisms are incorporated to enhance the algorithm’s search capabilities. The experimental results show that the proposed ZGWO-RF model achieves an accuracy of 95.9%, precision of 96.2%, and recall of 96.1% on the test set, outperforming the unimproved model. The constructed model exhibits improved identification effects on multi-source data, providing a new tool for non-destructive testing and the accurate classification of seeds in the future.

Germination test of maize (Zea mays L.) seeds in a NaCl solution

R bjective: To evaluate the germination behavior and to define the initial vigor of maize seeds. Methodology: The genetic material consisted of four batches of 20 hybrid seeds each (M-2014, SR-2014, SR-2012, and SR-2011), which were germinated in a NaCl solution (0, 5, 10, and 15 dS m-1) in a germination chamber. A randomized complete block experimental design was used, in which the seed batch and salinity level were the experimental units, with four repetitions each. Seeds with defined radicle and plumule were counted for evaluation. Results: As a result of the comparison of the three batches from the same environment (production site) and different years, the statistical analysis indicated that the longest-lived seeds have a lower germination percentage. Similarly, when batches from different production environments and the same year were compared, M-2014 obtained the highest average germination percentage (92.19%). When the maximum level of salinity (15 dS m-1) was evaluated, an average 41.25% loss in germination was observed. Conclusions: The test efficiently discriminated seed batches, based on speed and uniformity in NaCl-based germination, therefore providing acceptable results for the evaluation of the viability and vigor of a seed batch.