Li Weijia, Zhang Kun, Liu Jianxia, Wu Juan, Zhang Yue, Henke Michael
Engineering Research Center of Coal-Based Ecological Carbon Sequestration Technology of the Ministry of Education, Shanxi Datong University, Datong, China.
Key Laboratory of Graphene Forestry Application of National Forest and Grass Administration, Shanxi Datong University, Datong, China.
Front Plant Sci. 2024 Sep 13;15:1442485. doi: 10.3389/fpls.2024.1442485. eCollection 2024.
Optimizing the dynamics of daylily (Hemerocallis citrina Baroni) growth under various planting patterns is critical for enhancing production efficiency. This study presents a comprehensive model to simulate daylily growth and optimize planting patterns to maximize bud yield while minimizing land resource utilization.
The model incorporates source-sink relationship specific to daylilies into physiological process modeling, considering environmental factors such as micro-light and temperature climate, and CO2 concentration. Spatial factors, including planting pattern, row spacing, plant spacing, and plant density were examined for their impact on light interception, photosynthesis, and resource efficiency. Employing partial least square path modeling (PLS-PM), we analyzed the interrelations and causal relationships between planting configurations and physiological traits of daylily canopy leaves and buds. Through in situ simulations of 36 planting scenarios, we identified an optimal configuration (Scenario ID5) with a density of 83,000 plants·ha, row spacing of 0.8 m, and equidistant planting with a plant spacing of 0.15 m.
Our research findings indicate that increased Wide+Narrow row spacing can enhance yield to a certain extent. Although planting patterns influence daylily yield, their overall impact is relatively minor, and there is no clear pattern regarding the impact of plant spacing on individual plant yield. This modeling approach provides valuable insights into daylily plant growth dynamics and planting patterns optimization, offering practical guidance for both farmers and policymakers to enhance daylily productivity while minimizing land use.
优化黄花菜（Hemerocallis citrina Baroni）在不同种植模式下的生长动态对于提高生产效率至关重要。本研究提出了一个综合模型，用于模拟黄花菜生长并优化种植模式，以在最小化土地资源利用的同时最大化花蕾产量。
该模型将黄花菜特定的源库关系纳入生理过程建模，考虑了微光照、温度气候和二氧化碳浓度等环境因素。研究了包括种植模式、行距、株距和种植密度在内的空间因素对光截获、光合作用和资源效率的影响。采用偏最小二乘路径建模（PLS-PM），分析了种植配置与黄花菜冠层叶片和花蕾生理性状之间的相互关系和因果关系。通过对36种种植方案的原位模拟，我们确定了一种最优配置（方案ID5），密度为83000株·公顷，行距为0.8米，株距为0.15米的等距种植。
我们的研究结果表明，增加宽窄行间距可以在一定程度上提高产量。虽然种植模式会影响黄花菜产量，但其总体影响相对较小，并且株距对单株产量的影响没有明显规律。这种建模方法为黄花菜植株生长动态和种植模式优化提供了有价值的见解，为农民和政策制定者提高黄花菜生产力同时最小化土地利用提供了实际指导。
