A Process-Based Model for Simulating Phasic Developmentand Phenology in Rice

A simulation model for phasic and phenological development of rice was developed using the scale of physiological development time, based on the ecophysiological development processes. The interaction of daily thermal effectiveness, photoperiod effectiveness and intrinsic earliness(before heading), and basic filling duration factor(after heading)determined the daily physiological effectiveness, which accumulated to get physiological development time. The Beta and quadratic functions were used to describe daily thermal and photoperiod effectiveness, respectively. Five specific genetic parameters were added to adjust the genotypic differences in rice development so that all different varieties could reach the same physiological development time at a given development stage. The stages of seedling emergence, panicle initiation, heading, and maturity were validated using sowing dates under different ecological environments, with the RMSE of 1. 47, 5. 10, 4.58 and 3.37 days, respectively. The results showed that the model was not only explanatory and systematic but also accurate and applicable.

Modeling Fiber Fineness, Maturity, and Micronaire in Cotton (Gossypium hirsutum L.)

Crop performance is determined by the combined effects of the genotype of the crop and the environmental conditions of the production system. This study was undertaken to develop a dynamic model for simulating environmental （temperature and solar radiation） and N supply effects on fiber fineness, maturity and micronaire. Three different experiments involving genotypes, sowing dates, and N fertilization rates were conducted to support model development and model evaluation. The growth and development duration of fiber fineness, maturity, and micronaire were scaled by using physiological development time of secondary wall synthesis （PDT SWSP ）, which was determined based on the constant ratio of SWSP/ BMP. PTP （product of relative thermal effectiveness （RTE） and photosynthetically active radiation （PAR）, MJ m-2） and subtending leaf N content per unit area （N A , g m-2） and critical subtending leaf N content per unit area （CN A , g m-2） of cotton boll were calculated or simulated to evaluate effects of temperature and radiation, and N supply. Besides, the interactions among temperature, radiation and N supply were also explained by piecewise function. The overall performance of the model was calibrated and validated with independent data sets from three field experiments with two sowing dates, three or five flowering dates and three or four N fertilization rates for three subsequent years （2005, 2007, and 2009） at three ecological locations. The average RMSE and RE for fiber fineness, maturity, and micronaire predictions were 372 m g-1 and 5.0%, 0.11 m g-1 and 11.4%, 0.3 m g-1 and 12.3%, respectively, indicating a good fit between the simulated and observed data. It appears that the model can give a reliable prediction for fiber fineness, maturity and micronaire formation under various growing conditions.

Single-Cell Transcriptome Analysis in Plants:Advances and Challenges

The rapid and enthusiastic adoption of single-cell RNA sequencing(scRNA-seq)has demonstrated that this technology is far more than just another way to perform transcriptome analysis.It is not an exaggeration to say that the advent of scRNA-seq is revolutionizing the details of whole-transcriptome snapshots from a tissue to a cell.With this disruptive technology,it is now possible to mine heterogeneity between tissue types and within cells like never before.This enables more rapid identification of rare and novel cell types,simultaneous characterization of multiple different cell types and states,more accurate and integrated understanding of their roles in life processes,and more.However,we are only at the beginning of unlocking the full potential of scRNA-seq applications.This is particularly true for plant sciences,where single-cell transcriptome profiling is in its early stage and has many exciting challenges to overcome.In this review,we compare and evaluate recent pioneering studies using the A rabidopsis root model,which has established new paradigms for scRNA-seq studies in plants.We also explore several new and promising single-cell analysis tools that are available to those wishing to study plant development and physiology at unprecedented resolution and scale.In addition,we propose some future directions on the use of scRNA-seq technology to tackle some of the critical challenges in plant research and breeding.