Welcome to Smart Agriculture

Smart Agriculture ›› 2022, Vol. 4 ›› Issue (1): 97-109.doi: 10.12133/j.smartag.SA202202002

• Topic--Crop Growth and Its Environmental Monitoring • Previous Articles     Next Articles

Estimating the Differences of Light Capture Between Rows Based on Functional-Structural Plant Model in Simultaneous Maize-Soybean Strip Intercropping

LI Shuangwei1,2,3(), ZHU Junqi4, EVERS Jochem B.3, VAN DER WERF Wopke3, GUO Yan1, LI Baoguo1, MA Yuntao1()   

  1. 1.College of Land Science and Technology, China Agricultural University, Beijing 100193, China
    2.Institute of Agricultural Equipment, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China
    3.Centre for Crop Systems Analysis, Wageningen University, Wageningen 430-6700 AK, The Netherlands
    4.Marlborough Research Centre, The New Zealand Institute for Plant and Food Research Limited, Blenheim 7240, New Zealand
  • Received:2021-08-31 Online:2022-03-30

Abstract:

Intercropping creates a heterogeneous canopy and triggers plastic responses in plant growth and structural development. In order to quantify the effect of planting pattern, strip width and row position on the structural development and light capture of maize and soybean in simultaneous intercropping, both experimental and modelling approaches were used. Field experiments were conducted in 2017-2018 with two sole crops (maize and soybean) and two intercrops: Two rows of maize alternating with two rows of soybeans (2:2 MS) and three rows of maize alternating with six rows of soybean (3:6 MS). The morphological traits of maize and soybean e.g., leaf length and width, internode length and diameter, leaf and petiole declination angle in different rows and different planting patterns, and photosynthetically active radiation (PAR) above and below the canopy of 2:2 MS were measured throughout the growing season. A functional-structural plant model of maize-soybean intercropping was developed in the GroIMP platform. The model was parameterized based on the morphological data set of 2017, and was validated with the leaf area index (LAI), plant height and PAR data set of 2018. The model simulated the morphological development of individual organs based on growing degree days (thermal time) and calculated the light capture at leaf level. The model well reproduced the observed dynamics of leaf area index and plant height (RMSE: 0.24-0.70 m2/m2 for LAI and 0.06-0.17 m for plant height), and the fraction of light capture in the 2:2 MS intercropping (RMSE: 0.06-0.10). Maize internode diameter in intercrops increased, but the internode length did not change. Soybean internodes in intercrops became longer and thinner compared to sole soybean probably caused by the shading imposed by maize, and the 2:2 MS had longer internodes than the 3:6 MS, indicating the effects of strip width. Simulated light capture of maize in 2:2 MS intercropping was 35.6% higher than sole maize. For maize in 3:6 MS intercropping, the light capture of the border rows and inner row were 27.8% and 20.3% higher than sole maize, respectively. Compared to sole soybean, the simulated light capture of soybean in border rows was 36.0% lower in 2:2 MS intercropping, and was 28.8% lower in 3:6 MS intercropping. For 3:6 MS intercropping, light capture of soybean in inner rows I and inner rows II were 4.1% and 1.8% lower than sole soybean, respectively. In the future, the model could be further developed and used to explore and optimize the planting patterns of maize soybean intercropping under different environmental conditions using light capture as an indicator.

Key words: maize-soybean intercropping, functional-structural plant model, light capture, three-dimensional structure, phenotype plasticity, row difference

CLC Number: