Optimization Research On Crop Growth Light Recipe In Plant Factory

Plant factory agricultural production is currently internationally recognized as advanced development stage of facility agriculture,plant factory is through the agricultural facilities high-precision environmental control to achieve crop annual continuous production of efficient facility agricultural systems,the use of artificial light and industrial production environment is full artificial intelligence control and the use of agricultural producing factory to achieve efficient agricultural production,can significantly improve the yield and quality of planted crops,reduce pests and diseases,improve land use efficiency,it is considered to be an important means to solve the contradiction between population growth and food demand in the future.Previous research results show that in different stages of crop growth in plant factories on light,heat,water,fertilizer and other growth environment different factors,crop light recipe formula is the core factor affecting crop growth quality and yield and reduce the key indicators of plant factory energy consumption cost,how to obtain scientific and reasonable crop growth light formula and achieve the optimization of light formula,for the future application and popularization of plant factory plays an important role.In this paper,through the interactive experiment of environmental control variables for planting and production in plant factories,we explore the experimental observation and theoretical analysis of the effects of light formulas on crop quality and light physiology under the premise of controlling the relevant environmental impact factors affecting the production of plant factories(indoor temperature,humidity and other environmental impact factors,nutrient solution influencing factors,etc.),and study and analyze the effects of different light formulas on crop growth yield and quality.The light formula research initially shows that the light quality,light intensity and light duration provided by the artificial light supplement system in the plant factory are the main influencing factors affecting the quality and photophysiology of the crop,and extending the light time of the plant factory can significantly improve the dry matter content and quality of the crop,however,this effect varies from plant species to plant species,the reason may be that different crops have different physiological needs for light.The light formula plays a decisive role in the yield and quality of the plant factory.In view of the different needs of different crops in plant factories for light formulation,the authors designed experiments through orthogonal experimental design,conducted Analysis of Variance(ANOVA)method,established quadratic regression curves,and analyzed the interaction between different factors.The study reveals that more red light can affect lettuce photomorphism and growth to a large extent,meanwhile,more blue light can improve lettuce Vitamin C accumulation,increasing light intensity and duration in a certain range can significantly reduce nitrate content in lettuce leaves,these conclusions can be confirmed by the results of orthogonal experimental design and quadratic regression design.On the basis of experimental observation and theoretical analysis of the light formula of the plant factory,for the traditional data analysis methods are computationally intensive,different experiments need to be designed for different research purposes,and observations are only collected for analysis,however,the selectivity of machine learning methods for data is not very large,and the data collected from different research purposes can be used as input to model by machine learning methods.Therefore,the machine learning method is further applied to the numerical simulation and optimization analysis of the light formula of the plant factory,and the correlation analysis of the light environment factors of the plant factory on crop growth parameters and crop quality is completed,that is,the neural network model of the crop light formula of the plant factory is explored and established by machine learning method,the light formula simulation scheme of the plant factory to regulate crop growth and lettuce quality is obtained,and the genetic algorithm is used to optimize the light formula of the plant factory.The optimization of light formula scheme for plant factories that is conducive to crop growth and light ecological environment is completed,which provides theoretical methods for the production efficiency and quality improvement of light formula planting of different crops in plant factory planting and production,and provides scientific basis for energy conservation and emission reduction in plant factory production.