Single seed precise sowing of maize using computer simulation

PLoS One. 2018 Mar 5;13(3):e0193750. doi: 10.1371/journal.pone.0193750. eCollection 2018.

Abstract

In order to test the feasibility of computer simulation in field maize planting, the selection of the method of single seed precise sowing in maize is studied based on the quadratic function model Y = A×(D-Dm)2+Ym, which depicts the relationship between maize yield and planting density. And the advantages and disadvantages of the two planting methods under the condition of single seed sowing are also compared: Method 1 is optimum density planting, while Method 2 is the ideal seedling emergence number planting. It is found that the yield reduction rate and yield fluctuation of Method 2 are all lower than those of Method 1. The yield of Method 2 increased by at least 0.043 t/hm2, and showed more advantages over Method 1 with higher yield level. Further study made on the influence of seedling emergence rate on the yield of maize finds that the yields of the two methods are both highly positively correlated with the seedling emergence rate and the standard deviations of their yields are both highly negatively correlated with the seedling emergence rate. For the study of the break-up problem of sparse caused by the method of single seed precise sowing, the definition of seedling missing spots is put forward. The study found that the relationship between number of hundred-dot spot and field seedling emergence rate is as the parabola function y = -189.32x2 + 309.55x - 118.95 and the relationship between number of spot missing seedling and field seedling emergence rate is as the negative exponent function y = 395.69e-6.144x. The results may help to guide the maize seeds production and single seed precise sowing to some extent.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Agriculture / methods*
  • Computer Simulation*
  • Seedlings / growth & development
  • Seeds / growth & development*
  • Zea mays / growth & development*

Grants and funding

The corresponding author, Qi Hua, received the National Key Research and Development Program of China (2016YFD0300103) for this work.