Considering the time-consuming and tedious work of the current methods to control plant layout, which is mostly based on expert experience or field trials, we propose an algorithm to optimize and simulate a planting layout based on a virtual plant model and an optimization algorithm. A functional-structural plant model, which combines the structure and physiological function of plants, is used to construct a planting scene. The planting and row spacing are set as the genetic factors and the chromosomes of the genetic algorithm are encoded with a binary method. The photosynthetic yield of the unit planting area is denoted as the fitness value. By using this method, the intercropping of maize and soybean plants and the sole cropping of rice plants are studied. Experimental results show that the proposed method can obtain a high yield planting plan.

Nicotinic partial agonists provide an accepted aid for smoking cessation and thus contribute to decreasing tobacco-related disease. Improved drugs constitute a continued area of study. However, there remains no reductionist method to examine the cellular and subcellular pharmacokinetic properties of these compounds in living cells. Here, we developed new intensity-based drug-sensing fluorescent reporters (iDrugSnFRs) for the nicotinic partial agonists dianicline, cytisine, and two cytisine derivatives - 10-fluorocytisine and 9-bromo-10-ethylcytisine. We report the first atomic-scale structures of liganded periplasmic binding protein-based biosensors, accelerating development of iDrugSnFRs and also explaining the activation mechanism. The nicotinic iDrugSnFRs detect their drug partners in solution, as well as at the plasma membrane (PM) and in the endoplasmic reticulum (ER) of cell lines and mouse hippocampal neurons. At the PM, the speed of solution changes limits the growth and decay rates of the fluorescence response in almost all cases. In contrast, we found that rates of membrane crossing differ among these nicotinic drugs by >30-fold. The new nicotinic iDrugSnFRs provide insight into the real-time pharmacokinetic properties of nicotinic agonists and provide a methodology whereby iDrugSnFRs can inform both pharmaceutical neuroscience and addiction neuroscience.