Grain Yield Of Maize Research Articles

Straw Mulching and Weather Conditions Affecting the Trade-Off Between Grain Yield and Agronomic Traits of Maize

Straw mulching (SM) plays an important role in promoting the grain yield (GY) of maize under no-tillage conditions. However, there is still a lack of deep understanding on the interactive impact of SM and weather conditions on agronomic traits and the contributions to GY. This study selected a cornfield in the North China Plain as the research object and set up a straw management experiment, including SM and no straw mulching (NSM). The GY and agronomic traits of maize from 2018 to 2020 were monitored, and the relationship of agronomic traits with GY and the weather conditions were analyzed. The results show that SM promoted maize GY by 20.44%. Straw mulching increased the plant height, ear diameter, and ear height by 8.43%, 1.99%, and 12.65%, respectively. A correlation analysis showed that the ear length and ear height were the main factors affecting maize yield. Ear length was significantly correlated with kernel numbers per ear in SM. Growing degree days, hot dry wind, and air temperature significantly affected kernel numbers per ear and plant growth. This study highlights the contributions of agronomic factors to maize GY under SM and variable weather conditions and is helpful to improve cropland management.

Soil Mulching Practices Increased Grain‐Filling Capacity of Rainfed Maize (Zea mays L.) by Improving Soil Hydrothermal Condition and Leaf Photosynthetic Potential

ABSTRACTGrain‐filling rate and duration largely affect the grain‐filling capacity, which determines the grain yield of maize (Zea mays L.). Nevertheless, there is little about the mechanism of how various soil mulching practices affect the leaf photosynthetic potential and subsequent grain‐filling capacity of maize. Field experiments were undertaken on rainfed summer maize in northwest China under flat cultivation without mulch (FNM), flat cultivation with straw mulch (FSM), flat cultivation with transparent film mulch (FTF), flat cultivation with black film mulch (FBF), ridge‐furrow cultivation with transparent film mulch (RTF) and ridge‐furrow cultivation with black film mulch (RBF) in 2021 and 2022. This study explored the impact of various soil mulching patterns on soil hydrothermal condition, leaf growth, photosynthetic potential, aboveground dry matter growth and grain‐filling process of rainfed maize. The dynamics of leaf area index (LAI) and grain‐filling were fitted with growth equations, and the relationships of grain‐filling rate, leaf area duration and LAI withering rate were quantified. The results showed that, compared with FNM, other five soil mulching practices improved soil hydrothermal condition, the maximum LAI and leaf expansion rate but reduced leaf withering rate, thereby increasing radiation interception rate (RI) at the grain‐filling stage. The soil mulching practices also increased leaf SPAD value, net photosynthetic rate, photosynthetic nitrogen use efficiency and the aboveground dry matter. Compared with FNM, other five practices extended the effective grain‐filling period and the active period of grain‐filling, increased the maximum and mean grain‐filling rates, improved the 100‐kernel weight and the average kernel per ear (KPE), thereby increasing grain yields by 9.2%, 33.7%, 38.0%, 46.3% and 58.6%, respectively. The functional relationships of grain‐filling rate and accumulated leaf area duration (y = a/(1 + b*exp(−kx))), and the functional relationships of grain‐filling rate and LAI withering rate (y = (a + cx + ex2)/(1 + bx + dx2)) were first proposed. In conclusion, various soil mulching practices improved the soil hydrothermal condition, green leaves growth process and RI, which improved the leaf photosynthetic potential and the grain‐filling capacity, thereby increasing the 100‐kernel weight, KPE and grain yield. This study can help us quantitatively describe and better understand the maize grain‐filling process under various mulching practices.

Precision drip Irrigation System and Foliar Application of Biostimulant and Fertilizers Containing Micronutrients Optimize Photochemical Efficiency and Grain Yield of Maize (Zea mays L)

Abstract Asymmetric drought propagation and depletion of soil nutrients threaten cereal crop productivity worldwide, calling for the application of validated agronomic practices to curtail their effect on crop production. This study evaluated the effect of precision drip irrigation, biostimulant, and micronutrients application on photochemical efficiency and yield of maize.An experiment laid in a randomized complete block design with irrigation and water stress was established in 2022 and 2023 growing seasons at the experimental area of the University of Debrecen. Other treatments included T1 (non-microbial biostimulant from plant origin), T2 (zinc based chemical fertilizer), T3 (boron and molybdenum based chemical fertilizer), and T4 (control). Data was collected on steady-state fluorescence (F’), maximal fluorescence (Fm’), quantum photosynthetic yield or efficiency of photosystem II (ΦPSII or Y(II)), electron transport rate (ETR), and grain yield and yield components. Precision drip irrigation significantly optimized ΦPSII, ETR, cob weight, number of seeds per cob, weight of 1000 seeds and grain yield. The biostimulant and micronutrients optimized Fm’, ΦPSII, and ETR at VT and R2 growth stages. Regardless of the water management regime, T1, T2 and T3 seasonally optimized grain yield. Between water management regimes, biostimulant had the highest yield optimization effect under precision drip irrigation in the season with elevated water stress.Optimum photochemical efficiency and grain yield is achievable through precision drip irrigation, biostimulant, and micronutrient application. However, further research involving 2–3 application times at critical stages of maize under precision drip irrigation and/or combined application of these treatments at season specific precision drip irrigation is required.

Effect of maize (zea mays l.) and cowpea (vigna unguiculata l.) intercropping on agronomic performance, yield and nutritional values of maize and cowpea under supplementary irrigation

A field experiment was conducted to evaluate the effect of maize (Zea mays L.) and cowpea (Vigna Unguiculata L.) intercropping on agronomic performance, yield, and nutritional values at Arba Minch University. Treatments were only maize crop (T1), only cowpea (T2), intercrop (maize and cowpea) in a 1:1 ratio (T3) and alternative rows of 2:2 (T4) as treatments. Treatments were arranged in a randomized complete block design (RCBD). Data on plant morphology, yield, nutritional composition, and economic return were recorded. The height of the plant (145.5 cm) of maize was significantly (P<0.001) higher at 1:1 intercropping than the height of the sole while the height of the cowpea was higher at the sole cropping. Higher number of branches (P <0.05) per plant (5.28) of cowpea was recorded in pure stands of cowpea than intercropping. The grain yield of maize (6.9 t/ha) and cowpea (4.2 t/ha) was significantly (P<0.05) higher in sole cropping than in intercropping. A higher dry matter yield of 9.06 t/ha of maize was obtained in a 1:1 maize- cowpea intercropping ratio than sole maize. Significantly (P<0.001) highest dry matter cowpea yield of 5.77 t/ha was obtained at sole cultivation than intercropping. The intercropping of maize with cowpea had an advantage of resource utilization in terms of land equivalent ratio (LER) 41.7% to 62.5%. The marginal rate of return (MRR) of intercropping in the ratio of 1:1 was as high as 48.23% in intercropping maize-cowpea, which was much better than sole cropping. Therefore, it could be recommended that the ratio of 1:1 maize-cowpea intercropping for land resource use and economic food and feed production in Arba Minch and similar agro-ecology zones.

Genome-wide association analysis of grain yield and Striga hermonthica and S. asiatica resistance in tropical and sub-tropical maize populations

BackgroundGenetic improvement for Striga hermonthica (Sh) and S. asiatica (Sa) resistance is the most economical and effective control method to enhance the productivity of maize and other major cereal crops. Hence, identification of quantitative trait loci (QTL) associated with Striga resistance and economic traits will guide the pace and precision of resistance breeding in maize. The objective of this study was to undertake a genome-wide association analysis of grain yield and Sh and Sa resistance among tropical and sub-tropical maize populations to identify putative genetic markers and genes for resistance breeding. 126 maize genotypes were evaluated under controlled environment conditions using artificial infestation of Sh and Sa. The test genotypes were profiled for grain yield (GY), Striga emergence counts at 8 (SEC8) and 10 (SEC10) weeks after planting, and Striga damage rate scores at 8 (SDR8) and 10 (SDR10) weeks after planting. Population structure analysis and genome-wide association mapping were undertaken based on 16,000 single nucleotide polymorphism (SNP) markers.ResultsA linkage disequilibrium (LD) analysis in 798,675 marker pairs revealed that 21.52% of pairs were in significant linkage (P < 0.001). Across the chromosomes, the LD between SNPs decayed below a critical level (r2 = 0.1) at a map distance of 0.19 Mbp. The genome-wide association study identified 50 significant loci associated with Sh resistance and 22 significant loci linked to Sa resistance, corresponding to 39 and 19 candidate genes, respectively.ConclusionThe study found non-significant QTL associated with dual resistance to the two examined Striga species Some of the detected genes reportedly conditioned insect and pathogen resistance, plant cell development, variable senescence, and pollen fertility. The markers detected in the present study for Sa resistance were reported for the first time. The gene Zm00001eb219710 was pleiotropic, and conditioned GY and SEC10, while Zm00001eb165170 affected SDR8 and SDR10, and Zm00001eb112030 conditioned SDR8 and SDR10 associated with Sh resistance. The candidate genes may facilitate simultaneous selection for Sh and Sa resistance and grain yield in maize after further validation and introgression in breeding pipelines. Overall, we recommend breeding maize specifically for resistance to each Striga species using germplasm adapted to the endemic region of each parasite.

Assessment of yield loss due to fall armyworm in maize using high-resolution multispectral spaceborne remote sensing

ABSTRACT The fall armyworm (FAW), Spodoptera frugiperda (J.E. Smith), invasion endangered the maize production worldwide, including India. The objective of this study was to quantify the FAW damage severity and its impact on leaf area index (LAI), biomass and grain yield of maize and to detect the field damage using high-resolution multispectral spaceborne remote sensing data. Maize growing fields in the Kurnool District of Andhra Pradesh and the Gadwal District of Telangana, India, were randomly surveyed to collect detailed ground-truth information. Foliar damage due to FAW was recorded, and the fields were categorized into various severity grades (healthy, low, medium and severe). FAW infestation caused significant change in LAI between the severity grades, which formed the basis for its damage detection using multispectral spaceborne remote sensing. Severe FAW infestation caused significant reduction in LAI, biomass and grain yield ranging between 36.9 and 39.9% compared to healthy grade. The infestation at the leaf collar (LC) stage caused significant yield loss of up to 26.5% compared to the tassel initiation (TI) and tasselling and silking (TS) stages. Canopy spectral reflectance from healthy and FAW-infested plants showed significant differences in the visible and near infrared (NIR) regions. A reflectance peak was observed in the NIR region of healthy plants compared to infested plants. Among various spaceborne vegetation indices, the Soil Adjusted Vegetation Index (SAVI) performed better in identifying the FAW infestation (R2 = 0.61**), biomass (R2 = 0.70**) and yield loss (R2 = 0.82**). These findings indicate the feasibility of utilizing multispectral remote sensing data for monitoring FAW infestation on a spatial scale, thus enabling the site-specific management.

Mulching tree leaves improve the growth, yield, and yield components of hybrid maize

The experiment was carried out at the Agroforestry Farm, Department of Agroforestry, Bangladesh Agricultural University, Mymensingh from November 2019 to March 2020 to assess the impact of tree leaf mulching on the growth, yield attributes, and yield of maize. The study used a Randomized Complete Block Design with three replications and six treatments. These treatments were: T0=Control (no mulch), T1=Akashmoni (Acacia auriculiformis) tree leaf mulch, T2=Segun (Tectona grandis) tree leaf mulch, T3=Kalo koroi (Albizia lebbeck) tree leaf mulch, T4=Jhau (Casuarina equisetifolia) tree leaf mulch, and T5=Jackfruit (Artocarpus heterophyllus) tree leaf mulch. The results showed that the Kalo koroi tree leaf mulch (T3) led to the highest values for various parameters such as plant height, number of effective tillers per plant, number of leaves per plant, leaf length, leaf diameter, number of cobs per plant, length, and diameter of cob, the weight of single cob, number of grains per cob, grain weight per cob, 100-grain weight, and grain yield of maize (221.18 cm, 0.93, 17.29, 79.26 cm, 7.30 cm, 4.18, 1.70, 21.11 cm, 6.08 cm, 212.12 g, 453.85 g, 138.91 g, 30.60 g, and 11.81 t/ha). Conversely, the lowest values were obtained in the control (T0) (no mulch), followed by T2 and T1 treatments (209.39 cm, 0.37, 12.5, 72.48 cm, 4.62 cm, 1.50, 15.03 cm, 4.44 cm, 202.19 g, 421.56 g, 111.55 g, 26.46 g, and 8.35 t/ha). Among the various tree leaf mulch treatments, it was found that the Kalo koroi tree leaf mulch performed better for vegetative growth, yield, and yield-contributing attributes in maize compared to the no mulch treatment. Therefore, it was suggested that tree leaf mulches could be a potential alternative to traditional mulches in maize cultivation. Res. Agric. Livest. Fish. Vol. 11, No. 2, August 2024: 205-214

Impact of Different Herbicidal Treatments on Hybrid Maize: A Review

Maize (Zea mays L.) is an important cereal crop grown in the world. The living factors (insects, pests, weeds) and non-living factors (drought, salinity, heat stress) affects the yield of maize; among which weeds are considered as most destructive in decreasing the maize crop yield. Weeds negatively affect the grain yield of maize and increase the production cost of farmers. Various herbicides are used to control weeds in maize including atrazine, tembotrione etc. Atrazine is a pre-emergence herbicide used to control weeds. It is a selective herbicide used to control broad-leaved weeds and annual grasses. Tembotrione is a PoE (Post-emergence) broad spectrum herbicide used to control broad-leaved and grassy weeds in maize. This herbicide effectively reduces the density and dry weight of most of the weeds present in maize crop. Tembotrione gives lower weed index and higher weed control efficiency, when applied at 150 g ha−1 + surfactant and 125 g ha−1 + surfactant at 20 DAS. These herbicide shows no phytotoxicity effect on the crops. They are totally safe for weed control and enhance the productivity and profatibilty of the crop.

Enhancing yield of modern maize (ZeamaysL.) hybrids through the optimization of population photosynthetic capacity and light-nitrogen efficiency under high density

Due to the breeding of dense-resistant and lodging-resistant varieties in maize production, dense planting has become an effective means for achieving high and stable yields, while excellent hybrids are a prerequisite for reasonable dense planting in maize production. Nonetheless, the photosynthetic mechanism of improving plant density tolerance of maize hybrids released at different era in China remains unclear. This study aims to investigate the 40-year breeding effort for enhanced photosynthetic trait at different densities, and elucidate the physiological and ecological mechanisms of improving the density tolerance of maize hybrids. We conducted a 3-year study in 2019, 2020, and 2021. From 1970 to 2009, a comparison was made between the eight major hybrids promoted in China, divided into four decades, under three planting densities (45,000 (D1), 67,500 (D2), and 90,000 (D3) plants ha−1). At high density, modern hybrids had more rational canopy structure and leaf photosynthetic performance compared with old hybrids and specific leaf nitrogen has decreased slightly. Among all treatments, the modern hybrids (2000s) were able to maintain higher net photosynthetic rate and photosynthetic nitrogen utilization efficiency (PNUE) at D3 density, and therefore possessed the highest grain yield (GY), which was 118.47% higher than that of the old hybrids (1970s). Leaf area duration after anthesis, total chlorophyll content, photosynthesis key enzyme activities, and maximum efficiency of PSII photochemistry were all positively correlated with GY, with PNUE was more significantly correlated with GY indeed and is a key indicator for maize hybrids optimization. Based on these results, breeders should continue to conduct hybrid selections under adverse and high-density conditions, focusing on the optimization of population structure and the continuous improvement of photosynthetic capacity, searching for the optimal leaf nitrogen-content status, so as to select and breed high-yielding and density-tolerance hybrids, which resulted in a sustained increase in maize GY.

Developing a Deep Learning network “MSCP-Net” to generate stalk anatomical traits related with crop lodging and yield in maize

Plant stem is essential for the delivery of resources and has a great impact on plant lodging resistance and yield. However, how to accurately and efficiently extract structural information from crop stems is a big headache. In this study, we first established a Maize Stalk Cross-section Phenotype (MSCP) dataset containing anatomical information of 990 images from hand-cut transections of stalks. Then, to large-scale measure the stalk anatomy features, we developed a Maize Stalk Cross-section Phenotyping Network (MSCP-Net) which integrated a convolutional neural network and the methods of instance segmentation and key point detection. A total of 14 stalk anatomical parameters (traits) can be automatically produced with high mAP@.5 (0.907) for the parameter “vascular bundles segmentation” and high DICE (0.864) for the parameter “functional zones segmentation”. The cross-validation with the MSCP dataset indicated the good performance of MSCP-Net in predicting anatomical traits. On this basis, the correlation analysis across 14 anatomical traits and 12 agronomic importance traits in 110 maize inbred-lines was conducted and revealed that the stalk related traits (stem cross-section, large vascular bundles, fiber contents, and aerial roots) are key indicators for lodging resistance and grain yield of maize. In addition, the maize inbred-lines were classified into two groups, and the higher value of group II compared with group I in breeding hybrid varieties was discussed. The results demonstrated that the MSCP-Net is expected to be a useful tool to rapidly obtain stem anatomical traits which are agronomic important in maize genetic improvement.

Optimize planting density and nitrogen fertilizer rate on green cob and grain yield of maize (Zea mays L.) under irrigation in North Shewa, Ethiopia

Nowadays producing maize for green cob is a profitable business in addition to producing maize for grain yield. High plant density has been widely used to enhance grain yield in maize. A field experiment was conducted at four locations for two consecutive years (2021–2022) to determine the optimum plant density and nitrogen level and to assess the advantage of selling the green cob rather than the grain yield. The experiment was laid out in a Randomized Complete Block Design in a factorial arrangement with three replications. Three plant populations (44,444, 66,666, and 88,888 plants ha−1) with five nitrogen levels (0, 46, 92, 138, and 184 kg ha−1 were combined by factorial combinations and tested in the experimental plots to select the optimum level for high grain and green cob yield. The maximum grain yield (8656 kg ha−1) was obtained under the highest plant population (88,888 plants ha−1), and from tested nitrogen rates 46, 92, and 138 kg nitrogen ha−1 gave statically similar higher yield. Based on partial budget analysis, the application of 92 kg ha-1 nitrogen under 88,888 plant population was more economically feasible than other treatment combinations. This result showed 23.42 % yield advantages compared to the positive control. In addition, applying 138 kg N under 88,888 plant densities was the most profitable compared to other combinations to produce green cob. Thus, the blanket recommended plant population, 44,444 plants ha−1 with application of 46 kg N ha−1 is insufficient for maize green cob and grain yield production. Rather use of 88,888 plants ha−1 with the application of 92 kg N ha−1 for grain yield production and the use of 88,888 plants per ha−1 with the application of 138 kg N ha−1 is profitable for the production of maize green cob.

Genotype-environment interaction for grain yield in maize (Zea mays L.) using the additive main effects and multiplicative interaction (AMMI) model.

Genotype-environment interaction consists of the different response of individual genotypes resulting from changing environmental conditions. Its significance is a phenomenon that makes the breeding process very difficult. On the one hand, the breeder expects stable genotypes, i.e., yielding similarly regardless of environmental conditions. On the other hand, selecting the best genotypes for each region is one of the key challenges for breeders and farmers. The aim of this study was to evaluate genotype-by-environment interaction for grain yield in new maize hybrids developed by Plant Breeding Smolice Co. Ltd., utilizing the additive main effects and multiplicative interaction (AMMI) model. The investigation involved 69 maize (Zea mays L.) hybrids, tested across five locations in a randomized complete block design with three replications. Grain yield varied from 8.76 t ha-1 (SMH_16417 in Smolice) to 16.89 t ha-1 (SMH_16043 in Płaczkowo), with a mean yield of 13.16 t ha-1. AMMI analysis identified significant effects of genotype, environment, and their interaction on grain yield. Analysis of variance indicated that 25.12% of the total variation in grain yield was due to environment factor, 35.20% to genotypic differences, and 21.18% to genotype by environmental interactions. Hybrids SMH_1706 and SMH_1707 are recommended for further breeding programs due to their high stability and superior average grain yield.

Sub-surface drip fertigation of nitrogen coupled with crop residue incorporation enhanced the growth and yield of maize in an alluvial soils

A two-year field experiment was conducted at ICAR-Indian Agricultural Research Institute, New Delhi, to standardize the N-fertigation schedule and crop residue management in sub-surface drip fertigated (SSDF) maize [Pusa HQPM 1’ improved: double bio-fortified]. The experiment was laid-out in a split-plot design with 3 replications. There were 8 main-plot treatments comprising different N sub-surface drip fertigation levels (0, 50, 75, 100% RDN) with one conventional cultivation of maize, where RDN (150 kg/ha) was applied as per recommendation. Under sub-surface fertigation of N, each dose of N was divided into 3-and 4-splits, for fertigation. Sub-plot treatments included greengram residue (3 t/ha) and no greengram residue incorporation. P and K (60 kg P2 O5 /ha and 40 kg K2 O/ha respectively) fertilizers were supplied equally in all the plots by SSDF. Results revealed that plant height at various stages statistically varied with levels and splits of SSDF-N and crop residue incorporation. The highest plant height and leaf area were recorded with 100% RDN-4S which remained at par with 100% RDN-3S and 75% RDN-4S. Conventional maize cultivation was inferior to ‘RDN100’ and 75%, however on par with 50% RDN. The nitrogen uptake was found significantly superior in 100 and 75%RDN over conventional and control treatments. Similarly, the grain yield of maize was highest under 100% ‘RDN-4’ &amp;3 S, and 75% RDN-4S, which were at par with one another. Overall, it could be concluded that sub-surface fertigation of N not only improved the growth and yield of maize but also helped in 25–50% saving of valuable fertilizer.

Exogenous application of plant bio-regulators improve yield and water use efficiency of maize under drought stress

Moisture stress in rainfed areas has significant adverse impact on plant growth and yield. Exogenous application of plant bio-regulators (PBRs) plays an important role to mitigate drought stress in plants. A field experiment was conducted during rainy (kharif) seasons of 2018 and 2019 to explore the positive role of PBRs on the yield, economic feasibility and water use efficiency of maize grown under rainfed conditions. Ten treatments including PBRs, mulching and control were evaluated in a randomized block design. The result showed that foliar spray of salicylic acid (0.5 mM) with 1% urea solution improved the grain yield of maize by 24% as compared to control plot. Other PBRs such as glycine betaine, gibberellic acid and thiourea also increased the grain yield in the range of 10–21%. Application of 1% urea solution with PBRs synergise the effect of PBR to alleviate drought stress. The foliar applied PBRs maintained higher membrane stability index (73–78%), significantly increased relative water content (5–11%), chlorophyll content and decreased the proline content (11–21%) as compared to plants grown in control plot. Significant increase were noted in the rain and crop water use efficiency of maize with the foliar application of PBRs. Net returns were improved by 33% with application of salicylic acid (0.5 mM) + 1% urea as compared to control (₹49 × 103 /ha). Thus, foliar spray of salicylic acid (0.5 mM) with 1% urea solution could be an economic feasible strategy to reduce the adverse effects of drought and may increase the maize yield and water use efficiency.

Drip Fertigation Increases Maize Grain Yield by Affecting Phenology, Grain Filling Process, Biomass Accumulation and Translocation: A 4-Year Field Trial.

Drip fertigation (DF) is a widely used technology to increase grain yield with water and fertilizer conservation. However, the mechanism of high grain yield (GY) under DF is still unclear. Here, a four-year field experiment assessed the impacts of four treatments (i.e., conventional irrigation and nitrogen application, CK; drip irrigation with conventional nitrogen fertilization, DI; split-nitrogen fertigation with conventional irrigation, SF; and drip fertigation, DF) on maize phenology, leaf photosynthetic rates, grain filling processes, plant biomass, and GY. The results showed that DF significantly increased maize GY by affecting phenology, grain filling traits, aboveground biomass (BIO) accumulation, and translocation. Specifically, DF significantly increased leaf chlorophyll content, which enhanced leaf photosynthetic rates, and together with an increase of leaf area index, promoted BIO accumulation. As a result, the BIO at the silking stage of DF increased by 29.5%, transported biomass increased by 109.2% (1.2 t ha-1), and the accumulation of BIO after silking increased by 23.1% (1.7 t ha-1) compared with CK. Meanwhile, DF prolonged grain filling days, significantly increased the grain weight of 100 kernels, and promoted GY increase. Compared with CK, the four-year averaged GY and BIO increased by 34.3% and 26.8% under DF; a 29.7%, 46.1%, and 24.2% GY increase and a 30.7%, 39.5%, and 29.9% BIO increase were contributed by irrigation, nitrogen, and coupling effects of irrigation and nitrogen, respectively. These results reveal the high yield mechanism of drip-fertigated maize, and are of important significance for promoting the application of drip fertigation.

Unmanned Aerial Vehicle-Measured Multispectral Vegetation Indices for Predicting LAI, SPAD Chlorophyll, and Yield of Maize

Predicting crop yield at preharvest is pivotal for agricultural policy and strategic decision making. Despite global agricultural targets, labour-intensive surveys for yield estimation pose challenges. Using unmanned aerial vehicle (UAV)-based multispectral sensors, this study assessed crop phenology and biotic stress conditions using various spectral vegetation indices. The goal was to enhance the accuracy of predicting key agricultural parameters, such as leaf area index (LAI), soil and plant analyser development (SPAD) chlorophyll, and grain yield of maize. The study’s findings demonstrate that during the kharif season, the wide dynamic range vegetation index (WDRVI) showcased superior correlation coefficients (R), coefficients of determination (R2), and the lowest root mean square errors (RMSEs) of 0.92, 0.86, and 0.14, respectively. However, during the rabi season, the atmospherically resistant vegetation index (ARVI) achieved the highest R and R2 and the lowest RMSEs of 0.83, 0.79, and 0.15, respectively, indicating better accuracy in predicting LAI. Conversely, the normalised difference red-edge index (NDRE) during the kharif season and the modified chlorophyll absorption ratio index (MCARI) during the rabi season were identified as the predictors with the highest accuracy for SPAD chlorophyll prediction. Specifically, R values of 0.91 and 0.94, R2 values of 0.83 and 0.82, and RMSE values of 2.07 and 3.10 were obtained, respectively. The most effective indices for LAI prediction during the kharif season (WDRVI and NDRE) and for SPAD chlorophyll prediction during the rabi season (ARVI and MCARI) were further utilised to construct a yield model using stepwise regression analysis. Integrating the predicted LAI and SPAD chlorophyll values into the model resulted in higher accuracy compared to individual predictions. More exactly, the R2 values were 0.51 and 0.74, while the RMSE values were 9.25 and 6.72, during the kharif and rabi seasons, respectively. These findings underscore the utility of UAV-based multispectral imaging in predicting crop yields, thereby aiding in sustainable crop management practices and benefiting farmers and policymakers alike.

Growth and yield response of maize to integrated nutrient management of chicken manure and inorganic fertilizer in different agroecological zones

The productivity of maize, an essential staple food crop in Africa, is severely constrained by the declining fertility of the soil. The combined use of organic and inorganic fertilizers could ameliorate this challenge in a sustainable way to boost maize productivity. Two field trials were conducted at Ashanti -Mampong and Damongo, in the transitional and Guinea Savannah agroecologies of Ghana respectively, to assess the influence of sole and integrated application of chicken manure and NPK fertilizer on the growth and yield of maize. The treatments included two maize varieties; Abontem and Obatanpa, and five fertilizer rates; 3 t/ha chicken manure (CM), NPK (65:38:38 kg ha−1 NPK), ½ CM + ½ NPK and ¾ CM + ¼ NPK and control (no fertilizer). A 2 x 5 factorial randomized complete block design with three replications was used. Significant variations (p < 0.05) were revealed between varieties, fertilizer types and their interaction effects for phenological, growth and yield of maize in both locations. The superiority of the integrated application of NPK and chicken manure was also visible in the vegetative parameters such as plant height, number of leaves and shoot dry weight of the maize plants given them the comparative advantage to assimilate more photosynthates for partitioning to the ears and grains. Obatanpa treated with ½ CM + ½ NPK produced the highest yield of 4661.1 kg ha−1, which was 29.6 and 29.9 % higher than the same variety grown on sole NPK and sole chicken manure, respectively at Damongo. Abontem treated with ¾ CM + ¼ NPK recorded a grain yield of 4479.3 kg ha−1, 11.7 % higher than the sole NPK and 10.3 % higher than the sole CM at Damongo. Similarly, Obatanpa grown on the ½ CM + ½ NPK recorded the highest grain yield of 4349.3 kg ha−1at Mampong followed by Abontem treated with the sole NPK (4267.1 kg ha−1). Sole NPK and the combined application of NPK and chicken manure gave comparable responses for vegetative traits while the integrated application proved superior for grain yield of maize across the two agroecologies.

Does tillering affect the grain yield of maize (Zea mays)? A quantitative review

Does tillering affect the grain yield of maize (Zea mays)? A quantitative review

Effect of Different Doses of Nitrogen on Growth and Grain Yield of Hybrid Maize (Zea mays L., Gold 97)

This study investigates the impact of various nitrogen doses on the growth and grain yield of hybrid maize (Zea mays L., Gold 97). Nitrogen plays an important role in crop phenology, morphology, and grain yield of maize plants. A field experiment was conducted in a randomized complete block design with six levels of nitrogen (150, 160, 170, 180, 190, and 200 kg/ha) in four replications to evaluate the effect of different doses of nitrogen on the growth and yield of maize. Germination percentage, Days to 75% tasselling and silking, plant height, number of leaves, leaf area (LAI), cobs length, grain per row, pod, and total grain yield were recorded. Maximum germination was found in 180 kg N /ha. Plant height, number of leaves, and leaf area (LAI) were found to be maximum in the plots treated with 180-200 kg/ha of N. This field experiment revealed that different nitrogen dose has significant effects on days to 75% Tasselling and silking and found to be maximum in 180 kg/ha N treated plot. Also, nitrogen has a significant effect on cobs length, and grain per row was found highest at 180 kg N/ha. The highest Grain yield was found 180 kg/ha N treated plot. Findings have demonstrated that increasing nitrogen levels can often lead to increased grain yield up to a certain point, after which the yield plateaus or even declines. These findings provide valuable guidance for optimizing agricultural practices to meet the increasing global demand for cereal crops.

Influence of Simulated Erosion on Soil Properties and Maize Yield in the Southern Guinea Savanah Zone of Nigeria II

Aims: Long-term studies have been launched to assess the influence of artificial topsoil loss and its effects on soil properties and grain yield of cultivated maize. Place and Duration of Study: The study was conducted during the 2016 to 2019 agricultural seasons at the Federal University of Agriculture in Makurdi, Nigeria. Methodology: Three geo- referenced sites within the Federal University of Agriculture Makurdi, Nigeria namely: Site 1, Site_2 and Site_3 was used for the experiment. Erosion levels were established in June 2016 only by the incremental removal of topsoil at various depths. The study of crop productivity using simulated erosion was carried out using Randomized Complete Block Design (RCBD) with desurfaced soil depths of 0cm (control), 5cm, 10cm, 15cm and 20cm as treatments. One profile pit was also dug in each of the three sites for soil characterization and soil type establishment. Data collected on soil physical and chemical properties as well as crop growth parameters and grain yield was subjected to Analysis of Variance (ANOVA) using R core Statistical Software. Results: The study revealed that the soils of the three sites were classified as Kandic Paleustepts for Site_1, Typic Plinthustalfs for Site_2 and Typic Hapluderts for Site_3. These has brrn reported in drtail in paper I. In comparison with the 0cm (control), maize grain yield was reduced by 7%, 89%, 100% and 100% at Site_1, 5%, 64%, 82% and 85% at Site_2 and 6%, 71%, 82% and 92% at Site_3 for the 5cm, 10cm, 15cm and 20cm topsoil depth removal respectively. The topsoil loss greatly lowered the grain yield of maize. We report the effects of topsoil loss on crop productivity for two years.