A Knowledge Model For Suitable Growth Index Dynamic For Double Cropping Rice

Rice is one of the most important food crops and double cropping rice is also the important crop for ensuring food security in China.By conducting rice cropping area suitable growth index dynamic analysis,growth index dynamic model can be established to provide technical support for rice’s diagnosis of seeding condition and topdressing,in order to promote the intelligent and digital direction of crop planting.In this study,double cropping rice were selected four varities including early season rice(ZhongJiaZao 17 and TanLiangYou 83)and late rice(TianYouHuaZhan and YueYou 9113).We implemented four different levels of nitrogen treatment and a zero nitrogen treatment for comparison.Use GDD as variables,systematically analyzes the group stem and tiller number,leaf area index and dry matter accumulation dynamic change rules under different nitrogen levels.The results show that the different nitrogen treatment on each double cropping rice growth index has a significent effect,and can directly affect production.The suitable cultivation measures and fertilizer levels can be helpful for the growth of double cropping rice and yield formation.Quantitative analysis of growth index in the process of growing under different nitrogen treatment dynamics,establish suitable crop growth index dynamic model.It can be used as a key regulator of crop growth status real-time diagnosis and management basis.For the development of crop cultivation to the intelligent mode and digital mode is of great significance.Four varieties based on double cropping rice field trials,this study focused on building the double cropping dynamic model suitable for the growth indicators have machine rational.According to the principle of constant crop physiological development time,forecast period for PDT,dynamic compute cropping to each growth period required for growth.The model normalized processing GDD as well as the growth index including group stem and tiller numbers,leaf area index and dry matter accumulation.The study builds a dynamic model of relative group stem and tiller number based on relative GDD.The dynamic model of relative group stem and tiller number is RSTN(RGDD)=(RSTNtsp+α×RGDD)/(1+β×RGDD+γ×RGDD2).The study builds a dynamic model of relative leaf area index based on relative GDD.The dynamic model of relative leaf area index is RLAI(RGDD)=(RLAItsp + a×RGDD)/(1+b×RGDD+c×RGDD2).The study builds a dynamic model of relative dry matter accumulation based on relative GDD.The dynamic model of relative dry matter accumulation of early season rice is RDMAesr(RGDD)=1.022/(1+m1×e-n1×RGDD).The dynamic model of relative dry matter accumulation of late rice is RDMAsr(RGDD)=1.088/(1+m2×e-n2×RGDD).Model for double cropping rice under different environmental conditions in the process of cultivation’s diagnosis provides the quantitative indicators,including group stem and tillers number,leaf area index and aboveground dry matter accumulation,etc.The study verified and evaluated above models.The results shows that rational function can better describe the relative group stem and tillers dynamics and relative leaf area index.The results of the validation is better.The Logistic equation can well describle the relative dry matter accumulation dynamic.The results of the validation is also better.Based on the above model of relative growth index,obtained by further calculation of maximum growth index,obtained the actual suitable growth index.