کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
84243 | 158870 | 2014 | 11 صفحه PDF | دانلود رایگان |
• RW and W LEDs are more conducive to wheat growth and development.
• Use an inverse system model strategy to analyze and optimize the planting regime.
• Positive and inverse system possessed high accuracy with good dynamic performance.
Wheat (Triticum aestivum L.) has been selected as one of the core crops in Bioregenerative Life Support Systems (BLSS) for future long-term space mission, and its cultivation is affected by several environmental factors. Both light system and nutrient solution are most efficient for plant growth. The objective of this study was to investigate the influences of different spectra combinations and ionic concentration (NH4+, K+, Mg2+, Ca2+, NO3−, H2PO4−, SO42−) on wheat growth, photosynthetic rate, transpiration rate, antioxidant capacity and biomass yield. The results showed that red–white light (RW) and white light (W) are more conducive to wheat growth and development. There are obvious advantages: photosynthetic rate, harvest index, thousand kernel weight, edible and inedible biomass. In order to conduct wheat cultivation for good quality, high yield and efficiency in the artificial environment, a valid state-space model of wheat growth process (WGP) was developed by experimental data and system identification, and then the inverse system model of WGP was derived accordingly to theoretically optimize the planting regime including light intensity and mineral ions concentrations based on prescribed output responses of WGP and computer simulation. Analysis of the most efficient nutrient mixtures showed that depending on the light (intensity and quality) and the plant age the different absorption of mineral elements from nutrient solution was observed. Therefore, it is important to develop a balanced nutrient mixture and light, which would provide the optimum uptake by plants of each element for the growing season.
Journal: Computers and Electronics in Agriculture - Volume 109, November 2014, Pages 221–231