Response of canopy structure, light interception and grain yield to plant density in maize

Abstract

Good canopy structure is essential for optimal maize (Zea mays L.) production. However, creating appropriate maize canopy structure can be difficult, because the characteristics of individual plants are altered by changes in plant age, density and interactions with neighbouring plants. The objective of the current study was to find a reliable method for building good maize canopy structure by analysing changes in canopy structure, light distribution and grain yield (GY). A modern maize cultivar (ZhengDan958) was planted at 12 densities ranging from 1.5 to 18 plants/m2 at two field locations in Xinjiang, China. At the silking stage (R1), plant and ear height increased with plant density as well as leaf area index (LAI), whereas leaf area per plant decreased logarithmically. The fraction of light intercepted by the plant (F) increased with increasing plant density, but the light extinction coefficient (K) decreased linearly from 0.61 to 0.39. Taking the optimum value of F (95%) as an example, and using measured values of K for each plant density at R1 and the equation from Beer's law, the corresponding (theoretical) LAI for each plant density was calculated and optimum plant density (9.72 plants/m2) obtained by calculating the difference between theoretical LAIs and actual observations. Further analysis showed that plant density ranging from 10.64 to 11.55 plants/m2 yielded a stable GY range. Therefore, taking into account the persistence time for maximum LAI, the plant density required to obtain an ideal GY maize canopy structure should be increased by 10–18% from 9.72 plants/m2.

Agronomic Responses of Maize Hybrids to Row Spacing and Plant Population in the Summer and Winter Seasons in Brazil

“…In previous studies, higher plant density resulted in lower N uptake per plant, but significantly increased the N accumulation per area, irrespective of the soil conditions (Xu et al, 2017a; Nelson et al, 2015). Our LA results are in agreement with Li et al (2018) and Qian et al (2016). These authors also found that the LA per plant decreased linearly with increasing plant population under diverse soil and climate conditions.…”

Evaluating soil nitrate dynamics in an intercropping dripped ecosystem using HYDRUS-2D

“…K c1 is equal to 0.30 during the early season, 1.20 during the mid-season, and 0.35 during the late season; K c2 is 0.60 during the early season, 1.15 during the midseason, and 0.70 during the late season (Allen et al, 1998). The extinction coefficient k is equal to 0.39 for corn (Li et al, 2018) and 0.65 for tomato (Cruz et al, 2014). The emitter fluxes in the corn and tomato regions were represented in HYDRUS-2D with two 10 cm long time-variable boundary conditions and were calculated as follows:…”

Identifying Ways to Narrow Maize Yield Gaps Based on Plant Density Experiments

“…At each experimental site, the crops were kept free from pests, weeds, and diseases using standard approved pesticides. Further information can be found in [23,27].…”

“…Some of these showed that the optimum plant population density can be evaluated using the relationship between population-level GY and plant population density because the population-level GY responds to the plant population density in a parabolic fashion; the suitable plant population density was obtained at the highest population-level GY [21,22]. Other studies confirmed that the optimum plant density can be evaluated based on Beer's law equation and the optimum light interception (95% of light interception) [12,23]. Moreover, there are still some studies showed that the optimum plant density can be evaluated using maize growth models, such as the Crop-Environment Resource Synthesis (CERES) Maize model [24][25][26].…”