Maize Plant Density Research Articles

Soil respiration response to reductions in maize plant density and increased row spacing (Southeast pampas, Argentina)

Previous studies have recognized the influence of crop cover and agricultural management on variables (soil temperature, soil moisture, and root biomass) that influence soil respiration. However, despite the influence of plant density and row spacing on these variables in the maize crop (Zea mays L.), their impact on soil respiration has received little attention. Thus, the aims of this study were (i) to investigate whether reducing plant density and row spacing influences soil respiration, and (ii) to identify the controlling variables (soil temperature and soil moisture) underlying this response. We conducted field experiments in Balcarce, Argentina, over two seasons. Treatments included (i) maize crops at high plant density (≈8 plants m−2) and narrow rows (0.52 cm, HDN), and (ii) maize crops at low plant density (≈6.5 plants m−2) and wide row spacing (0.70 cm; LDW). Leaf area index (LAI), soil CO2 fluxes, soil superficial temperature, and moisture (characterized by the water-filled pore space, WFPS) were assessed throughout the growing season. Grain yield and cumulative soil CO2 emissions were determined at the final harvest. Major findings relevant to understanding the influence of reducing plant density and wider row spacing on instant CO2 fluxes include: (i) LAI reductions were related to higher superficial soil moisture, which was consistent at LAI ≥ 3; suggesting higher decreases in water uptake than increases in soil evaporation, and in turn (ii) increments in soil moisture were associated with higher CO2 fluxes. While lower plant density and wider row spacing had notable short-term effects on WFPS and soil respiration fluxes, they did not significantly affect cumulative soil respiration throughout the growing season. However, the combination of this practice with low-yield potential genotypes that exhibit low stability to changes in resource availability can increase CO2 emissions per unit of grain yield. These findings contribute to a better understanding of the impacts of management practices on soil respiration and, consequently, on carbon cycling within agricultural ecosystems.

Is it necessary to increase the maize planting density in China?

Increasing the maize planting density is considered a potential approach for increasing the grain yield in China, but there is no consensus regarding its yield-increasing effect and the influence of specific factors. Thus, we established a database (2721 pairs of data from 187 publications) to quantify the effects of increasing the maize planting density on the phenotypic traits and yield, to determine an appropriate maize planting density for each planting area, and to quantify the effects of environmental factors and agricultural imputs on the outcomes of increasing the planting density. We found that increasing the planting density increased the individual competition among maize plants, with negative effects on their growth, but the grain yield increased by 11.18–13.43 % due to the increased population biomass. Using the database, we found large differences in the optimal density and peak grain yield among maize planting areas, and the factors that caused these differences were analyzed based on subgroup analysis. Field management practices significantly influenced the outcomes of increasing the planting density. In particular, higher agricultural inputs (irrigation amount, and nitrogen and phosphorus application rates) enhanced the positive effect of increasing plant density on the optimal plant density and peak grain yield. In addition, the effects of increasing the planting density were significantly influenced by environmental (climate and soil) factors. When the mean annual temperature was 7–14°C and the mean annual precipitation was 400–800 mm, the yield and maximum peak yield were highest in relatively fertile (high total nitrogen, available nitrogen, and soil organic matter contents) and neutral (pH 6–8) soils. Our results highlight the need to increase the current maize planting density and provide a scientific basis for determining reasonable planting densities for different maize growing areas in China.

Establishment of a high-yield intercropping system for maize and legumes under rainfed conditions in eastern Bhutan

ABSTRACT Maize-legume intercropping is a sustainable strategy to improve maize production for smallholder farmers. Maize is a staple food crop in Bhutan and integration of legumes with maize has been considered as an alternative option towards enhancing maize production in the country. Here, we conducted two studies in eastern Bhutan: first study (2021) to identify suitable legumes for intercropping with maize and second study (2022) to evaluate the effects of different maize-soybean intercropping patterns on grain yield, land use efficiency, and economic benefits. The maize-soybean intercropping system showed better productivity and economic viability than the kidney bean and groundnut systems in both the sites. Row intercropping and strip intercropping with 2 rows of maize alternating with 2 rows of soybean (2 M:2S) spaced 0.3 × 0.3 m showed stable and consistently higher grain yield at Lingmethang and Wengkhar (LING = 6.05 t ha−1; WENG = 8.37 t ha−1). The land equivalent ratio (LING = 1.78; WENG = 1.73) and net return (0.16 million Nu. ha−1 for LING and 0.21 million Nu. ha−1 for WENG) were notably higher for these intercropping methods. Our results suggest that the integration of legumes between conventional maize planting density, row intercropping and strip intercropping (2 M:2S) spaced at 0.3 × 0.3 m would be beneficial for achieving higher productivity for smallholder farmers in eastern Bhutan.

Mapping Maize Planting Densities Using Unmanned Aerial Vehicles, Multispectral Remote Sensing, and Deep Learning Technology

Maize is a globally important cereal and fodder crop. Accurate monitoring of maize planting densities is vital for informed decision-making by agricultural managers. Compared to traditional manual methods for collecting crop trait parameters, approaches using unmanned aerial vehicle (UAV) remote sensing can enhance the efficiency, minimize personnel costs and biases, and, more importantly, rapidly provide density maps of maize fields. This study involved the following steps: (1) Two UAV remote sensing-based methods were developed for monitoring maize planting densities. These methods are based on (a) ultrahigh-definition imagery combined with object detection (UHDI-OD) and (b) multispectral remote sensing combined with machine learning (Multi-ML) for the monitoring of maize planting densities. (2) The maize planting density measurements, UAV ultrahigh-definition imagery, and multispectral imagery collection were implemented at a maize breeding trial site. Experimental testing and validation were conducted using the proposed maize planting density monitoring methods. (3) An in-depth analysis of the applicability and limitations of both methods was conducted to explore the advantages and disadvantages of the two estimation models. The study revealed the following findings: (1) UHDI-OD can provide highly accurate estimation results for maize densities (R2 = 0.99, RMSE = 0.09 plants/m2). (2) Multi-ML provides accurate maize density estimation results by combining remote sensing vegetation indices (VIs) and gray-level co-occurrence matrix (GLCM) texture features (R2 = 0.76, RMSE = 0.67 plants/m2). (3) UHDI-OD exhibits a high sensitivity to image resolution, making it unsuitable for use with UAV remote sensing images with pixel sizes greater than 2 cm. In contrast, Multi-ML is insensitive to image resolution and the model accuracy gradually decreases as the resolution decreases.

Plant nutrient removal and soil residual chemical properties as impacted by maize planting date and density.

This study aimed to measure maize (Zea mays) plant nutrient content and nutrient removal in grain, and to evaluate the residual soil nitrogen, phosphorus, and potassium as impacted by planting date and density. Field experiments were conducted to evaluate six plant densities and seven planting dates using a split-split plot design with three replications. Besides the crop growth and yield parameters, six plants were collected at the maturity and soil was sampled from each plot for nutrient analysis. Plant N, P, and K concentrations varied with planting date and density and within the ranges of 0.6-1.024%, 0.054-0.127%, and 0.75-1.71%, respectively. Grain N, P, and K concentrations decreased with plant density and varied from 1.059 to 1.558%, 0.20 to 0.319%, and 0.29 to 0.43%, respectively. Soil residual nutrient varied with depth, planting density and date. Residual N concentration in the topsoil varied from 0.6 to 37.2 mg kg-1 in 2019 and from 1.5 to 11.2 mg kg-1 in 2020 and was high under the last two planting dates. Soil residual N concentration was higher in the second layer than in the topsoil. The N concentration in the third layer varied from 0.1 to 33.2 mg kg-1 and was impacted by plant density. Topsoil P did not vary among planting dates and densities. The second and third soil layers P concentration was not affected. There was 83% increase in topsoil K in 2020 compared to 2019, and a decrease of 65 and 23% in soil K was observed in the second and third soil layers, respectively. For maize production system sustainability, future research should use a holistic approach investigating the impact of planting date, plant density on crop growth, yield, nutrient uptake and remobilization, and soil properties under different fertilizer rates to develop the fertilizer recommendation for maize while reducing the environmental impact of the production system.

Measurement and estimation of evapotranspiration in a maize field: A new method based on an analytical water flux model

Quantifying evapotranspiration (ET) in rainfed cropping systems can be challenging due to complicated interactions among site-specific soil, plant, and management factors. In Northeast China, ET and soil water status in maize fields often display strong spatial and temporal variations due to the changes in tillage practice, planting pattern, and maize plant density. Previous studies have shown that near-surface soil water content (θ) observations at multiple scales provide the potential to estimate surface soil water fluxes. In this study, we introduced a new method to estimate daily field ET by using a soil water flux model mainly based on the time-series of θ at a depth of 2.5 cm. The new method required a calibration of soil water diffusivity with maximum net water flux in the near-surface soil layer, which was related to precipitation redistribution below the canopy. Finally, the new method was evaluated using observed ET values over a 2-year period in a maize field, where independent measurements of soil water evaporation (E) and transpiration (T) were made with heat-pulse sensors and sap-flow gauges, respectively. Field observations showed that E dominated water loss during the seedling stage (16% of total ET). As the canopy was fully developed, E sharply decreased to a value of 0.4 mm d−1, and T accounted for about 89% of ET since the silking stage. The new method to estimate ET performed well in drying periods, while it tended to underestimate ET in wet periods with substantial infiltration into the surface layer. On rain-free days, the ET values estimated with the new method matched well with the measured E+T values, with R2 and RMSE values of 0.85 and 1.93 mm d−1. Therefore, the new approach provides an effective way to quantify maize ET.

WGCNA analysis of the effect of exogenous BR on leaf angle of maize mutant lpa1

Leaf angle, as one of the important agronomic traits of maize, can directly affect the planting density of maize, thereby affecting its yield. Here we used the ZmLPA1 gene mutant lpa1 to study maize leaf angle and found that the lpa1 leaf angle changed significantly under exogenous brassinosteroid (BR) treatment compared with WT (inbred line B73). Transcriptome sequencing of WT and lpa1 treated with different concentrations of exogenous BR showed that the differentially expressed genes were upregulated with auxin, cytokinin and brassinosteroid; Genes associated with abscisic acid are down-regulated. The differentially expressed genes in WT and lpa1 by weighted gene co-expression network analysis (WGCNA) yielded two gene modules associated with maize leaf angle change under exogenous BR treatment. The results provide a new theory for the regulation of maize leaf angle by lpa1 and exogenous BR.

From a point to a range of optimum estimates for maize plant density and nitrogen rate recommendations

AbstractThe interaction between nitrogen (N) rate, plant density, and hybrid on net return to seed and fertilizer cost remains unknown but important to be addressed given the multi‐input decision process corn growers make every year. We collected grain yield from a factorial experiment with five N rates (0–291 kg N ha−1), five plant densities (3.7–11.4 plants m−2), and four hybrids (old vs. new) over 2 years in Iowa. Data were sufficiently modeled with a quadratic plateau model with continuous covariate terms to include N × plant density interactions (R2 = 0.925, n = 387). We found a wide range of plant densities (6.7–8.4 plants m−2) and N rate (150–212 kg N ha−1) combinations to achieve 99% of the maximum net revenue. The economic optimum N rate increased with increasing plant density from 4 to 7 plants m−2. The fundamental relationships between grain yield response to N fertilizer and plant density were similar across old and new hybrids; however, the absolute values were different, with newer hybrids having 20% higher economic optimum N rate and 23% higher yield than the older hybrids. We concluded that by accounting for two inputs into the revenue equation, a larger range of combinations was found to achieve 99% of the maximum net revenue. Our study offers new insights into N rate by plant density by hybrid interaction to assist future research.

Potential crop yield gains under intensive soybean/maize intercropping in China

Abstract Aims Intensive soybean/maize intercropping, a specific form of intercropping, holds promise in addressing the challenges posed by increasing food demands, diminishing cropland areas, deteriorating soil quality, and escalating environmental pollution. Methods To evaluate the potential of this system, we conducted a national meta-analysis, quantifying its absolute yield gain (net effect, NE) and land use efficacy (land equivalent ratio, LER). We further investigated the underlying mechanisms by examining local climate, soil properties, and field management practices and then developed random forest (RF) models to assess the system's potential, incorporating current information on natural resources. Results In China, an average NE of 3.2 ± 0.1 Mg ha−1 and LER of 1.4 ± 0.02 were achieved by intensive soybean/maize intercropping. The variance of NE was significantly influenced by air temperature (10%), soybean delay days (8%), and maize plant density (9%). Similarly, the LER was strongly driven by soybean delay days (14%), sunshine hours (11%), and maize density (10%). Notably, this intensive intercropping system efficiently utilizes available resources, such as light, temperature (heat), accumulated temperature, and soil nutrients, particularly in regions characterized by low soil fertility and limited agricultural resources. Ultimately, the RF model estimated substantial overyielding of 2 800 kg per hectare, representing approximately 1.4 times the current soybean and maize production under China's monoculture. Conclusions The implementation of intensive soybean/maize intercropping is highly beneficial throughout China, especially in areas with limited agricultural resources. The Yangtze River Basin, in potentially, emerges as the most suitable region for adopting this intensive intercropping practice.

Optimizing root system architecture to improve root anchorage strength and nitrogen absorption capacity under high plant density in maize

Optimizing root system architecture to improve root anchorage strength and nitrogen absorption capacity under high plant density in maize

Optimizing maize planting density based on soil organic matter to achieve synergistic improvements of yield, economic benefits, and resource use efficiency

With the development of the economy, the contradiction between population, resources, and the environment has become more and more prominent. How to make full use of limited cultivated land resources to increase food production while reducing damage to the environment is an important issue facing agricultural production. Maize plays an essential role in ensuring global food security. Furthermore, planting density is a key agronomic factor affecting maize yield. Although soil organic matter (SOM) is an important indicator of soil fertility. Whether there are different agronomic optimal planting densities of maize under varying SOM contents remains unknown. Furthermore, there is limited understanding on whether optimizing maize planting density based on SOM further improves grain yield and resource use efficiency. Therefore, this study investigates the influence of SOM and planting density on maize grain yield. We also determine the relationship between SOM and agronomic optimal planting density (AOPD) and compare the grain yield, economic benefits, and resource use efficiency of sowing under uniform conventional planting density (SUD) versus optimized planting density based on SOM (SOD). The results showed that AOPD and its corresponding yield increased linearly with the increase in SOM. Compared with SUD, the yield of the two experimental sites under SOD increased by 2.3 % and 5.5 %, respectively, and the economic benefits increased by 0.5 % and 4.9 %, respectively. The average energy use efficiency, energy mass productivity, and energy economic productivity of the two experimental sites under SOD were all higher than those of SUD. These results demonstrate that it is theoretically feasible to optimize maize planting density based on the spatial heterogeneity of SOM. SOD is a potentially sustainable maize production method that can fully utilize the resources of cultivated land to increase grain yield and economic benefits.

Selection of Weeding Method and Plant Density in Maize (Zea mays L.) Based on Morphological and Physiological Characteristics

Aims: Maize is annual plant of the Poaceae, which, with a relatively short growth period and high yield, is ranked second in the world in terms of production after wheat. Choosing the most suitable different planting densities and weeding methods can have a favorable effect on increasing the yield of corn plants.
 Study Design: To investigate the traits and choose the most appropriate planting density and weeding method in maize (Zea mays L.) using graphic methods, a factorial experiment based on randomized complete block design was conducted in three replications.
 Place and Duration of Study: This study was conducted in Shahre-Rey region in 2020-2021.
 Methodology: The hybrid cultivated in the SC647 experiment was selected. Each test plot included four cultivation lines with a width of 75 cm and a length of 4 meters. The experimental land was fallow the year before maize cultivation, which was prepared by spring plowing and disk operations.
 Results: Based on the analysis of variance, the effect of planting density in all traits except the thousand seed weight trait and the effect of weeding stages in all traits except the trait number of rows in the cob showed a significant difference at the probability level of 0.01. Based on the means comparison of D3W3, D1W3 and D3W2 were selected as suitable treatments. Based on the correlation intensity map between the traits, the highest correlation intensity was estimated for the ear length trait with the plant height and the grain yield trait with the harvest index. The grouping diagram of the treatments formed four groups based on the first and second main components that justified 50.45% of the total variance of the data. Based on the polygon graph, treatments D2W3, D1W3, D3W2, D3W3, D1W1 and D1W2 were identified as the best treatments. Based on the cluster analysis diagram and heat map drawn on the experiment data, the treatments were divided into two main groups.
 Conclusion: In general, by reviewing all the analyzes performed on the experiment data, D3W3 (density of 85,000 plants per hectare and no weeding) and D3W2 (density of 85,000 plants and two stages of weeding 4 to 8 weeks after planting) can be used for maize cultivation.

Biomass and Methane Production in Double Cereal Cropping Systems with Different Winter Cereal and Maize Plant Densities

The biogas supply chain requires a correct combination of crops to maximize the methane yield per hectare. Field trials were carried out in North Italy over three growing seasons, according to a factorial combination of four cropping systems (maize as a sole-crop or after hybrid barley, triticale and wheat) and two maize plant densities (standard, 7.5 plants m−2 and high, 10 plants m−2) with the plants harvested as whole-crop silage. The specific methane production per ton was measured through the biochemical methane potential (BMP) method, while the methane yield per hectare was calculated on the basis of the BMP results and considering the biomass yield. The average methane yield of wheat resulted to be equal to 4550 Nm3 ha−1, and +17% and +28% higher than triticale and barley, respectively, according to the biomass yield. A delay in maize sowing reduced the yield potential of this crop; the biomass of maize grown after barley, triticale and wheat was 20%, 33% and 47% lower, respectively, than maize cultivated as a single crop. The high plant population increased the biomass yield in the sole-crop maize (+23%) and in the maize grown after barley (+20%), compared to the standard density. The highest biomass (32 t ha−1 DM) and methane yield (9971 Nm3 ha−1) within the cropping systems were obtained for barley followed by maize at a high plant density. This cropping system increased the methane yield by 46% and 18%, respectively, compared to the sole-crop maize or maize after triticale at a standard density. The smaller amount of available solar radiation, resulting from the later sowing of maize, reduced the advantage related to the application of a high plant density.

An EMS-induced allele of the brachytic2 gene can reduce plant height in maize.

D129 is an EMS-induced mutant with dwarf phenotype, which has important breeding potential to cultivate new varieties suitable for high-density plantingin maize Plant height is one of the important agronomic traits that affecting maize planting density, identification of superior dwarf mutants can provide important genetic materials for breeding new varieties suitable for high-density planting. In this study, we identified a dwarf mutant, d129, from maize EMS-induced mutant population. Gene mapping indicated that a G-to-A transition in the second exon of the br2 gene was responsible for the dwarf phenotype of the d129 mutant using MutMap method, which was further validated through allelism testing. Compared with WT plants, the average plant height and ear height of d129 were reduced by 26.67% and 39.43%, respectively, mainly due to a decrease in internode length. Furthermore, the d129 mutant exhibited increased internode diameter, which is important for increasing planting density due to the lodging resistance may be enhanced. Endogenous hormone measurement demonstrated that the contents of IAA and GA3 in the internode of the mutant were significantly lower than that of WT plants. RNA-seq analysis indicated that at least fifteen auxin-responsive and signaling-related genes exhibited differential expression, and some genes involved in cell development and other types of hormone signaling pathways, were also identified from the differential expressed genes. These genes may be related to the reduced hormone contents and decreased elongation of internode cells of the d129 mutant. Our study provided a novel dwarf mutant which can be applied in maize breeding to cultivate new varieties suitable for high-density planting.

Increasing Maize Production and Advancing Rational Water Allocation and Usage Based on the Optimal Planting Density and Irrigation Levels in Northwest China

Increasing water-use efficiency by optimizing planting density and irrigation regimes in maize is crucial for food security under limited water resources. In this study, six plant densities (6.0, 7.5, 9.0, 10.5, 12.0, and 13.5 × 104 plants ha−1) and three irrigation amounts (300, 450, and 600 mm) were assessed to analyze the effects of planting density and irrigation amount on the yield and yield components. We also explored the combination of maize production capacity and maximizing economic returns in a planting region. The results demonstrated that as planting density increased, grain yield first increased and then decreased. The optimum planting density was 9 × 104 plants ha−1 when the irrigation amount was 300 mm, and 10.5 × 104 plants ha−1 under both 450 mm and 600 mm irrigation amounts. The relationship between planting density, irrigation amount, planting area, production capacity, and economic return showed that a current production capacity with 6.75 × 104 plants ha−1, 600 mm, and 1.066 million ha, could be achieved with 10.5 × 104 plants ha−1, 344 mm, and 1.1 million ha. The water-use efficiency of irrigation was increased by 74%. Current returns could be achieved with 10.5 × 104 plants ha−1, 405 mm, and 1.1 million ha, or by 9.0 × 104 plants ha−1, 449 mm, and 1.1 million ha. These observations demonstrated that appropriately increasing the planting area and reducing the irrigation amount per hectare under an optimal planting density could achieve a greater economic return and water-use efficiency than either increasing the planting density or reducing the irrigation volume alone in North Xinjiang. We concluded that concurrent optimization of the maize planting density, irrigation amount and plant area will not only meet the demand of food security but also achieve a rational use of water resources and farmland.

The effects of plant density and nitrogen fertilization on maize yield and soil microbial communities in the black soil region of Northeast China

To obtain high maize yield (Zea mays L.), nitrogen (N) fertilizer is widely used across the world and has greatly altered soil microbial communities and influenced soil health. Increasing plant density is an effective strategy for increasing maize yield, while variations in soil microbial communities in response to plant density under high N levels have not been well-studied. In Northeast China, maize was grown at low (LD, 67,500 plants ha−1) and high (HD, 90,000 plants ha−1) densities, combined with three N application rates of 0, 200, and 400 kg N ha−1yr−1(N0, N200 and N400). Based on a six-year field experiment, key soil microbial characteristics and physicochemical properties of top soils (0–20 cm), as well as yield and vegetative parameters were examined. Compared with that of LD, the maize grain yield of HD increased 10.8 % across N application rates from 2012 to 2017 (P < 0.05), while no significant differences between N200 and N400 were observed. HD significantly increased microbial biomass carbon (MBC), microbial biomass N (MBN), and bacterial and fungal diversity at N400 (P < 0.05). Dominant bacterial phyla across all samples were Proteobacteria, Acidobacteria, Actinobacteria and Thaumarchaeota, and fungal phyla were Ascomycota, Basidiomycota and Zygomycota. Species composition of HD shared more similarity between N200 and N400 than that of LD. HD significantly increased the abundance of Nitrososphaera and reduced the abundance of Pseudomonas and Sphingobium. From LD to HD, ammonia-oxidizing archaea (AOA) gene abundance increased while nirK gene abundance decreased at all N application rates, and ammonia oxidizing bacteria (AOB) and nirS gene abundances decreased at N0 and N400 but increased at N200 (P < 0.05). Shoot biomass and N uptake were positively correlated with MBC and MBN but negatively correlated with microbial community diversity. HD directly increased root biomass and N uptake, then reduced soil N contents (NH4+-N, NO3–-N, and TN) and thus positively regulated soil microbial communities. Relative differences of diversity indexes and functional gene abundances between N application rates of HD were significantly lower than those of LD. Overall, our findings indicate that higher plant density of maize could mitigate the adverse effects of N fertilizer overuse on soil microbial communities, thus reconciling maize productivity and black soil health in Northeast China.

Effects of planting density and variety on productivity of maize-faba bean intercropping system

Maize (Zea mays)-faba bean (Vicia faba) intercropping is a recent practice in eastern Ethiopia and there is limited information on optimum planting density and suitable varieties of faba bean for productive intercropping with maize. Therefore, a field experiment was conducted in eastern Ethiopia during the 2018 and 2019 main cropping seasons to determine the effects of variety and density of faba bean on the yield components of the crops and the productivity of the intercropping. Treatments consisted of three farmers’ varieties (Yeferenji Baqela, Yehabesha Baqela, Batte) and one improved variety (Gachena)intercropped with maize in an additive design at three plant densities (25%, 50%, and 75% of their recommended sole crop density of 250,000 plants ha−1) and the recommended 100% plant density of sole faba bean and sole maize. A randomized complete block design in a factorial arrangement of treatments replicated three times per treatment was used. Analysis of data revealed that sole maize produced a significantly higher number of ears per plant (1.70), thousand kernel weight (287.9 g), aboveground dry biomass (19.11 t ha−1) and grain yield (6.16 t ha−1) than intercropped maize. Among the intercropping systems, maize intercropped with 25% of the sole faba bean produced a significantly higher grain yield (5.56 t ha−1) than 50% and 75% plant density. Similarly, the 75% plant density of the sole faba bean intercropped with maize produced the highest grain yield (0.96 t ha−1) compared to the 25% and 50% plant densities. Faba bean planted in the sole system produced a significantly higher seed yield (2.08 t ha−1) than the intercropped faba bean with maize. Faba bean variety Gachena was found to be superior than the other varieties in number of pods per plant (10.23), aboveground dry biomass (3.73 t ha−1), grain yield (1.96 t ha−1) and harvest index (26.75%). Land equivalent ratio showed 18.4% higher yield advantage when maize was intercropped with faba bean than when it was sole-cropped. The highest gross monetary value (99318 Ethiopian Birr ha−1) and maize equivalent yield (6621.2 kg ha−1) were obtained from maize intercropped with Gachena faba bean variety with no significant differences among the plant densities. It is concluded that intercropping of maize with 75% plant density of improved Gachena variety resulted in superior performance of the system in terms of productivity and economic return.

Response of Water Radiation Utilization of Summer Maize to Planting Density and Genotypes in the North China Plain

Increasing the planting density of summer maize to improve the utilization efficiency of limited soil and water resources is an effective approach; however, how the leaf water-use efficiency (WUEL), yield, and RUE respond to planting density and genotypes remains unclear. A 2-year field experiment was performed in the North China Plain (NCP) to investigate the effects of planting density (high, 100,000 plants ha−1; medium, 78,000 plants ha−1; and low, 56,000 plants ha−1) and genotypes (Zhengdan 958 and Denghai 605) on the leaf area index (LAI), photosynthetic characteristics, dry-matter accumulation, WUEL, and RUE of maize. The objective was to explore the effect of density and genotype on the WUEL and RUE of maize. Increasing planting density boosted LAI, light interception, dry-matter accumulation, and spike number but reduced the chlorophyll content, net photosynthetic rate, transpiration rate, and 1000-kernel weight. Both high and low planting densities were averse to RUE and yield. Zhengdan 958 increased the WUEL by 19.45% compared with Denghai 605, but the RUE of Denghai 605 was 18.19% higher than Zhengdan 958, suggesting that Denghai 605 had a greater production potential as the planting density increased. Our findings recommend using 78,000 plants ha−1 as the planting density with Denghai 605 to maintain summer maize yields in the NCP.

Leaf, plant, to canopy: A mechanistic study on aboveground plasticity and plant density within a maize-soybean intercrop system for the Midwest, USA.

Plants have evolved to adapt to their neighbours through plastic trait responses. In intercrop systems, plant growth occurs at different spatial and temporal dimensions, creating a competitive light environment where aboveground plasticity may support complementarity in light-use efficiency, realizing yield gains per unit area compared withmonoculture systems. Physiological and architectural plasticity including the consequences for light-use efficiency and yield in a maize-soybean solar corridor intercrop system was compared, empirically, withthe standard monoculture systems of the Midwest, USA. The impact of reducing maize plant density on yield was investigated in the following year. Intercropped maize favoured physiological plasticity over architectural plasticity, which maintained harvest index (HI) but reduced light interception efficiency (ɛi ) and conversion efficiency (ɛc ). Intercropped soybean invested in both plasticity responses, which maintained ɛi , but HI and ɛc decreased. Reducing maize plant density within the solar corridor rows did not improve yields under monoculture and intercrop systems. Overall, the intercrop decreased land-use efficiency by 9%-19%and uncoordinated investment in aboveground plasticity by each crop under high maize plant density does not support complementarity in light-use efficiency. Nonetheless, the mechanistic understanding gained from this study may improve crop cultivars and intercrop designs for the Midwest to increase yield.

Maize/soybean strip intercropping produces higher crop yields and saves water under semi-arid conditions.

Sustainable increases in crop production require efficient use of resources, and intercropping can improve water use efficiency and land productivity at reduced inputs. Thus, in a three-year field experiment, the performance of maize/soybean strip intercropping system differing with maize plant density (6 maize plants m-2, low, D1; 8 maize plants m-2, medium, D2; and 10 maize plants m-2, high, D3) was evaluated in comparison with sole maize or soybean cropping system. Results revealed that among all intercropping treatments, D2 had a significantly higher total leaf area index (maize LAI + soybean LAI; 8.2), total dry matter production (maize dry matter + soybean dry matter; 361.5g plant-1), and total grain yield (maize grain yield + soybean grain yield; 10122.5kg ha-1) than D1 and D3, and also higher than sole maize (4.8, 338.7g plant-1, and 9553.7kg ha-1) and sole soybean (4.6, 64.8g plant-1, and 1559.5kg ha-1). The intercropped maize was more efficient in utilizing the radiation and water, with a radiation use efficiency of 3.5, 5.2, and 4.3g MJ-1 and water use efficiency of 14.3, 16.2, and 13.3kg ha-1 mm-1, while that of intercropped soybean was 2.5, 2.1, and 1.8g MJ-1 and 2.1, 1.9, and 1.5kg ha-1 mm-1 in D1, D2, and D3, respectively. In intercropping, the land and water equivalent ratios ranged from 1.22 to 1.55, demonstrating that it is a sustainable strategy to improve land and water use efficiencies; this maximization is likely associated with the species complementarities for radiation, water, and land in time and space, which resulted in part from competition avoidance responses that maximize the economic profit (e. g., 1300 US $ ha-1 in D2) over sole maize (798 US $ ha-1) or sole soybean (703 US $ ha-1). Overall, these results indicate that optimizing strip intercropping systems can save 20-50% of water and land, especially under the present scenario of limited resources and climate change. However, further research is required to fully understand the resource capture mechanisms of intercrops in intercropping.