The excellent stretchability and biocompatibility of flexible sensors have inspired an emerging field of plant wearables, which enable intimate contact with the plants to continuously monitor the growth status and localized microclimate in real‐time. Plant flexible wearables provide a promising platform for the development of plant phenotype and the construction of intelligent agriculture via monitoring and regulating the critical physiological parameters and microclimate of plants. Here, the emerging applications of plant flexible wearables together with their pros and cons from four aspects, including physiological indicators, surrounding environment, crop quality, and active control of growth, are highlighted. Self‐powered energy supply systems and signal transmission mechanisms are also elucidated. Furthermore, the future opportunities and challenges of plant wearables are discussed in detail.

Functional–structural plant models (FSPMs) have been evolving for over 2 decades and their future development, to some extent, depends on the value of potential applications in crop science. To date, stabilizing crop production by identifying valuable traits for novel cultivars adapted to adverse environments is topical in crop science. Thus, this study will examine how FSPMs are able to address new challenges in crop science for sustainable crop production. FSPMs developed to simulate organogenesis, morphogenesis, and physiological activities under various environments and are amenable to downscale to the tissue, cellular, and molecular level or upscale to the whole plant and ecological level. In a modeling framework with independent and interactive modules, advanced algorithms provide morphophysiological details at various scales. FSPMs are shown to be able to: (i) provide crop ideotypes efficiently for optimizing the resource distribution and use for greater productivity and less disease risk, (ii) guide molecular design breeding via linking molecular basis to plant phenotypes as well as enrich crop models with an additional architectural dimension to assist breeding, and (iii) interact with plant phenotyping for molecular breeding in embracing three-dimensional (3D) architectural traits. This study illustrates that FSPMs have great prospects in speeding up precision breeding for specific environments due to the capacity for guiding and integrating ideotypes, phenotyping, molecular design, and linking molecular basis to target phenotypes. Consequently, the promising great applications of FSPMs in crop science will, in turn, accelerate their evolution and vice versa.

High plant density is considered a proficient approach to increase maize production in countries with limited agricultural land; however, this creates a high risk of stem lodging and kernel abortion by reducing the ratio of biomass to the development of the stem and ear. Stem lodging and kernel abortion are major constraints in maize yield production for high plant density cropping; therefore, it is very important to overcome stem lodging and kernel abortion in maize. In this review, we discuss various morphophysiological and genetic characteristics of maize that may reduce the risk of stem lodging and kernel abortion, with a focus on carbohydrate metabolism and partitioning in maize. These characteristics illustrate a strong relationship between stem lodging resistance and kernel abortion. Previous studies have focused on targeting lignin and cellulose accumulation to improve lodging resistance. Nonetheless, a critical analysis of the literature showed that considering sugar metabolism and examining its effects on lodging resistance and kernel abortion in maize may provide considerable results to improve maize productivity. A constructive summary of management approaches that could be used to efficiently control the effects of stem lodging and kernel abortion is also included. The preferred management choice is based on the genotype of maize; nevertheless, various genetic and physiological approaches can control stem lodging and kernel abortion. However, plant growth regulators and nutrient application can also help reduce the risk for stem lodging and kernel abortion in maize.

Using state-of-the-art computer-aided technologies, particularly CAD and integrated CAD/FEA technique to model and simulate the composite, the single-fiber pull-out problem is presented. The capability and effectiveness of using enabled CAD to generate solid modeling based composite fiber/matrix heterogeneous assembly and its application with the seamless integration of CAD/FEA to simulate fiber pull-out mechanisms and effects of material and geometric variation on stresses in fiber and matrix are demonstrated. The CAD/FEA model predictions are compared with an analytical solution. Parametric studies of fiber pull-out problems with different stiffness ratios of fiber and matrix, and with irregular fiber cross-sections, for which solutions are difficult to obtain analytically, are also presented.

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