Improving zinc (Zn) content in wheat and its processed foods is an effective way to solve human Zn deficiency, which can cause a variety of diseases. This article summarizes the works on Zn in wheat grain, wheat processing, and wheat-derived foods. Grain Zn content in wheat was 31.84 mg·kg⁻¹ globally but varied across continents, for example, 25.10 mg·kg⁻¹ in Europe, 29.00 mg·kg⁻¹ in Africa, 33.63 mg·kg⁻¹ in Asia, and 33.91 mg·kg⁻¹ in North America. Grain Zn content in wheat improved from 28.96 to 36.61 mg·kg⁻¹ and that in flour increased from 10.51 to 14.82 mg·kg⁻¹ after Zn fortification. Furthermore, Zn content varied in the different processed components of wheat; that is, Zn content was 12.58 mg·kg⁻¹ in flour, 70.49 mg·kg⁻¹ in shorts, and 86.45 mg·kg⁻¹ in bran. Zinc content was also different in wheat-derived foods, such as 13.65 mg·kg⁻¹ in baked food, 10.65 mg·kg⁻¹ in fried food, and 8.03 mg·kg⁻¹ in cooking food. Therefore, the suitable Zn fortification, appropriate processing, and food type of wheat are important to meet people's Zn requirement through wheat.

Wheat is one of the most important food crops in the world, with development of the grains directly determining yield and quality. Understanding grain development and the underlying regulatory mechanisms is therefore essential in improving the yield and quality of wheat. In this study, the developmental characteristics of the pericarp was examined in developing wheat grains of the new variety Jimai 70. As a result, pericarp thickness was found to be thinnest in grains at the top of the spike, followed by those in the middle and thickest at the bottom. Moreover, this difference corresponded to the number of cell layers in the pericarp, which decreased as a result of programmed cell death (PCD). A number of autophagy-related genes (ATGs) are involved in the process of PCD in the pericarp, and in this study, an increase in ATG8-PE expression was observed followed by the appearance of autophagy structures. Meanwhile, following interference of the key autophagy gene ATG8, PCD was inhibited and the thickness of the pericarp increased, resulting in small premature grains. These findings suggest that autophagy and PCD coexist in the pericarp during early development of wheat grains, with both processes increasing from the bottom to the top of the spike. Moreover, PCD was also found to rely on ATG8-mediated autophagy. The results of this study therefore provide a theoretical basis for in-depth studies of the regulatory mechanisms of wheat grain development.

Wheat ear counting is crucial for calculating wheat phenotypic parameters and scientifically managing fields, which is essential for estimating wheat field yield. In wheat fields, detecting wheat ears can be challenging due to factors such as changes in illumination, wheat ear growth posture, and the appearance color of wheat ears. To improve the accuracy and efficiency of wheat ear detection and meet the demands of intelligent yield estimation, this study proposes an efficient model, Generalized Focal Loss WheatNet (GFLWheatNet), for wheat ear detection. This model precisely counts small, dense, and overlapping wheat ears. Firstly, in the feature extraction stage, we discarded the C4 feature layer of the ResNet50 and added the Convolutional block attention module (CBAM) to this location. This step maintains strong feature extraction capabilities while reducing redundant feature information. Secondly, in the reinforcement layer, we designed a skip connection module to replace the multi-scale feature fusion network, expanding the receptive field to adapt to various scales of wheat ears. Thirdly, leveraging the concept of distribution-guided localization, we constructed a detection head network to address the challenge of low accuracy in detecting dense and overlapping targets. Validation on the publicly available Global Wheat Head Detection dataset (GWHD-2021) demonstrates that GFLWheatNet achieves detection accuracies of 43.3% and 93.7% in terms of mean Average Precision (mAP) and $A{P}_{50}$ (Intersection over Union (IOU) = 0.5), respectively. Compared to other models, it exhibits strong performance in terms of detection accuracy and efficiency. This model can serve as a reference for intelligent wheat ear counting during wheat yield estimation and provide theoretical insights for the detection of ears in other grain crops.

Plant cell walls are dynamic structural matrices that provide mechanical support while regulating growth, transport, environmental sensing, and defense. Their properties emerge from the coordinated biosynthesis, deposition, assembly, and remodeling of cellulose, hemicelluloses, pectins, lignin, and specialized wall polymers, yet how wall architecture is coupled to integrity surveillance and whole-plant physiology remains incompletely understood. Here, we synthesize current knowledge of plant cell wall classification, major polymer biosynthesis and assembly, cell wall integrity signaling, and physiological functions. We compare primary, secondary, and specialized walls and discuss how differences in their composition and organization confer distinct mechanical and functional properties. We then examine how wall-derived oligosaccharides, apoplastic peptides, receptor-like kinases, Ca²⁺ signaling, reactive oxygen species, cytoskeletal dynamics, and hormonal crosstalk translate wall perturbations into adaptive responses. Viewed in an integrated physiological context, wall composition, architecture, and remodeling shape anisotropic growth, morphogenesis, tissue repair, xylem hydraulics, ion homeostasis, abiotic stress adaptation, and pathogen defense. Collectively, current evidence supports a view of the cell wall as an active regulatory interface rather than a passive scaffold. Finally, we highlight unresolved questions concerning mechanochemical sensing, spatial heterogeneity, and growth–defense trade-offs, and discuss how advances in spatial omics, live-cell imaging, biomechanics, genome editing, and computational modeling may help resolve how wall properties are regulated across cells, tissues, and environmental contexts.