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Ground penetrating radar (GPR) has emerged as a pivotal tool for subsurface explorations, particularly in detecting subsurface defects that might endanger structural integrity. While GPR B-scan data visually depict underground conditions, it represents the time delay and amplitude of the returned electromagnetic (EM) waves, making them complex to interpret due to both their image-like appearance and their inherent waveform changes. To address this complexity, this article introduces the novel temporal–spatial synthesis network, designed to harness both temporal and spatial features for enhanced subsurface defect detection in GPR B-scan data. The echo state network, underpinned by reservoir computing, is utilized to fit the GPR data and capture its “temporal features,” emphasizing the temporal variations present in the EM waves. Concurrently, the convolutional neural network focuses on discerning “spatial features” from the B-scan images, spotlighting spatial patterns that possibly indicate subsurface defects. After extracting these temporal and spatial features, they are synthesized to form a comprehensive representation of the GPR data. The enhanced synthesized feature facilitates precise classification, resulting in heightened differentiation between normal and defect-contained subsurface areas. Experiments on real-world GPR datasets are conducted, with the results underscoring the efficacy of the proposed approach.

Fusarium crown rot (FCR) is a soilborne disease causing severe yield losses in many wheat-growing areas of the world. Diseased plants show browning and necrosis of roots and stems causing white heads at maturity. Little is known about the molecular processes employed by wheat roots to respond to the disease. We characterized morphological, transcriptional and hormonal changes in wheat seedling roots following challenge with Fusarium pseudograminearum (Fp), the main pathogen of FCR. The pathogen inhibited root development to various extents depending on plants’ resistance level. Many genes responsive to FCR infection in wheat roots were enriched in plant hormone pathways. The contents of compounds involved in biosynthesis and metabolism of jasmonic acid, salicylic acid, cytokinin and auxin were drastically changed in roots at five days post-inoculation. Presoaking seeds in methyl jasmonate for 24 h promoted FCR resistance, whereas presoaking with cytokinin 6-benzylaminopurine made plants more susceptible. Overexpression of TaOPR3, a gene involved in jasmonic acid biosynthesis, enhanced plant resistance as well as root and shoot growth during infection.

The pitaya is a common fruit in southern China, but the growing environment of pitayas is complex, with a high density of foliage. This intricate natural environment is a significant contributing factor to misidentification and omission in the detection of the growing state of pitayas. In this paper, the growth states of pitayas are classified into three categories: flowering, immature, and mature. In order to reduce the misidentification and omission in the recognition process, we propose a detection model based on an improvement of the network structure of YOLOv8, namely YOLOv8n-CBN. The YOLOv8n-CBN model is based on the YOLOv8n network structure, with the incorporation of a CBAM attention mechanism module, a bidirectional feature pyramid network (BiFPN), and a C2PFN integration. Additionally, the C2F module has been replaced by a C2F_DCN module containing a deformable convolution (DCNv2). The experimental results demonstrate that YOLOv8n-CBN has enhanced the precision, recall, and mean average precision of the YOLOv8n model with an IoU threshold of 0.5. The model demonstrates a 91.1% accuracy, a 3.1% improvement over the original model, and an F1 score of 87.6%, a 3.4% enhancement over the original model. In comparison to YOLOv3-tiny, YOLOv5s, and YOLOv5m, which are highly effective target detection models, the mAP@0.50–0.95 of our proposed YOLOv8n-CBN is observed to be 10.1%, 5.0%, and 1.6% higher, respectively. This demonstrates that YOLOv8n-CBN is capable of more accurately identifying and detecting the growth status of pitaya in a natural environment.

Pitaya fruit is a significant agricultural commodity in southern China. The traditional method of determining the ripeness of pitaya by humans is inefficient, it is therefore of the utmost importance to utilize precision agriculture and smart farming technologies in order to accurately identify the ripeness of pitaya fruit. In order to achieve rapid recognition of pitaya targets in natural environments, we focus on pitaya maturity as the research object. During the growth process, pitaya undergoes changes in its shape and color, with each stage exhibiting significant characteristics. Therefore, we divided the pitaya into four stages according to different maturity levels, namely Bud, Immature, Semi-mature and Mature, and we have designed a lightweight detection and classification network for recognizing the maturity of pitaya fruit based on the YOLOv8n algorithm, namely GSE-YOLO (GhostConv SPPELAN-EMA-YOLO). The specific methods include replacing the convolutional layer of the backbone network in the YOLOv8n model, incorporating attention mechanisms, modifying the loss function, and implementing data augmentation. Our improved YOLOv8n model achieved a detection and recognition accuracy of 85.2%, a recall rate of 87.3%, an F1 score of 86.23, and an mAP50 of 90.9%, addressing the issue of false or missed detection of pitaya ripeness in intricate environments. The experimental results demonstrate that our enhanced YOLOv8n model has attained a commendable level of accuracy in discerning pitaya ripeness, which has a positive impact on the advancement of precision agriculture and smart farming technologies.

Histone deacetylase (HDAC) inhibitors (HDACis) have been widely used in plants to investigate the role of histone acetylation, particularly the function of HDACs, in the regulation of development and stress response. However, how histone acetylation is involved in rice (Oryza sativa L.) disease resistance has hardly been studied. In this paper, four HDACis including Sodium butyrate (NaBT), Suberoylanilide Hydroxamic Acid (SAHA), LBH-589 and Trichostatin A (TSA) were used to treat rice seedlings at different concentrations before inoculation of Magnaporthe oryzae. We found that only 10mM NaBT treatment can significantly enhanced rice blast resistance. However, treatment of the four HDACis all increased global histone acetylation but at different sites, suggesting that the inhibition selectivity of these HDACis is different. Notably, the global H3K9ac level was dramatically elevated after both NaBT and LBH589 treatment although LBH589 could not enhance rice blast resistance. This indicates that the HDACs they inhibit target different genes. In accordance with the phenotype, transcriptomic analysis showed that many defense-related genes were up-regulated by NaBT treatment. Up-regulation of the four genes bsr-d1, PR10B, OsNAC4, OsKS4 were confirmed by RT-qPCR. ChIP-qPCR results revealed that H3K9ac level on these genes was increased after NaBT treatment, suggesting that these defense-related genes were repressed by HDACs. In addition, by promoter motif analysis of the genes that induced by both NaBT treatment and rice blast infection, we found that the motifs bound by ERF and AHL transcription factors (TFs) were the most abundant, which demonstrates that ERF and AHL proteins may act as the candidate TFs that recruit HDACs to defense-related genes to repress their expression when plants are not infected by rice blast.

Abstract Background Heat stress is one of the most crucial environmental factors, which reduces crop yield worldwide. In plants, the MYB family is one of the largest families of transcription factors (TFs). Although some wheat stress-related MYB TFs have been characterized, their involvement in response to high-temperature stress has not been properly studied. Results Six novel heat-induced MYB genes were identified by comparison with previously established de novo transcriptome sequencing data obtained from wheat plants subjected to heat treatment; genomic and complete coding sequences of these genes were isolated. All six TaMYBs were localized in the nucleus of wheat protoplasts. Transactivation assays in yeast revealed that all six proteins acted as transcriptional activators, and the activation domains were attributed to the C-termini of the six wheat MYB proteins. Phylogenetic analysis of the six TaMYBs and R2R3-MYBs from Arabidopsis revealed that all six proteins were in clades that contained stress-related MYB TFs. The expression profiles of TaMYB genes were different in wheat tissues and in response to various abiotic stresses and exogenous abscisic acid treatment. In transgenic Arabidopsis plants carrying TaMYB80 driven by the CaMV 35S promoter, tolerance to heat and drought stresses increased, which could be attributed to the increased levels of cellular abscisic acid. Conclusions We identified six heat-induced MYB genes in wheat. We performed comprehensive analyses of the cloned MYB genes and their gene products, including gene structures, subcellular localization, transcriptional activation, phylogenetic relationships, and expression patterns in different wheat tissues and under various abiotic stresses. In particular, we showed that TaMYB80 conferred heat and drought tolerance in transgenic Arabidopsis. These results contribute to our understanding of the functions of heat-induced MYB genes and provide the basis for selecting the best candidates for in-depth functional studies of heat-responsive MYB genes in wheat.

Wheat (Triticum aestivum L.) yield and quality are adversely affected by heat, drought, or the combination of these two stresses in many regions of the world. A phosphoenolpyruvate carboxylase kinase-related kinase gene, TaPEPKR2, was identified from our previous heat stress-responsive transcriptome analysis of heat susceptible and tolerant wheat cultivars. Based on the wheat cultivar Chinese Spring genome sequence, TaPEPKR2 was mapped to chromosome 5B. Expression analysis revealed that TaPEPKR2 was induced by heat and polyethylene glycol treatment. To analyze the function of TaPEPKR2 in wheat, we transformed it into the wheat cultivar Liaochun10, and observed that the transgenic lines exhibited enhanced heat and dehydration stress tolerance. To examine whether TaPEPKR2 exhibits the same function in dicotyledonous plants, we transformed it into Arabidopsis, and found that its overexpression functionally enhanced tolerance to heat and dehydration stresses. Our results imply that TaPEPKR2 plays an important role in both heat and dehydration stress tolerance, and could be utilized as a candidate gene in transgenic breeding.

Autophagy helps deliver sequestered intracellular cargo to lysosomes for proteolytic degradation and thereby maintains cellular homeostasis by preventing accumulation of toxic substances in cells. In a forward mosaic screen in Drosophila designed to identify genes required for neuronal function and maintenance, we identified multiple cacophony (cac) mutant alleles. They exhibit an age-dependent accumulation of autophagic vacuoles (AVs) in photoreceptor terminals and eventually a degeneration of the terminals and surrounding glia. cac encodes an α1 subunit of a Drosophila voltage-gated calcium channel (VGCC) that is required for synaptic vesicle fusion with the plasma membrane and neurotransmitter release. Here, we show that cac mutant photoreceptor terminals accumulate AV-lysosomal fusion intermediates, suggesting that Cac is necessary for the fusion of AVs with lysosomes, a poorly defined process. Loss of another subunit of the VGCC, α2δ or straightjacket (stj), causes phenotypes very similar to those caused by the loss of cac, indicating that the VGCC is required for AV-lysosomal fusion. The role of VGCC in AV-lysosomal fusion is evolutionarily conserved, as the loss of the mouse homologues, Cacna1a and Cacna2d2, also leads to autophagic defects in mice. Moreover, we find that CACNA1A is localized to the lysosomes and that loss of lysosomal Cacna1a in cerebellar cultured neurons leads to a failure of lysosomes to fuse with endosomes and autophagosomes. Finally, we show that the lysosomal CACNA1A but not the plasma-membrane resident CACNA1A is required for lysosomal fusion. In summary, we present a model in which the VGCC plays a role in autophagy by regulating the fusion of AVs with lysosomes through its calcium channel activity and hence functions in maintaining neuronal homeostasis.

Plant lifespan is affected by factors with genetic and environmental bases. The laws governing these two factors and how they affect plant lifespan are unclear. Here we show that the acyl chain length (ACL) of phosphatidylserine (PS) is correlated with plant lifespan. Among the detected eight head-group classes of membrane lipids with lipidomics based on triple quadrupole tandem mass spectrometry, the ACL of PS showed high diversity, in contrast to the ACLs of the other seven classes, which were highly conserved over all stages of development in all plant species and organs and under all conditions that we studied. Further investigation found that acyl chains of PS lengthened during development, senescence, and under environmental stresses and that increasing length was accelerated by promoted- senescence. The acyl chains of PS were limited to a certain carbon number and ceased to increase in length when plants were close to death. These findings suggest that the ACL of PS can count plant lifespan and could be a molecular scale ruler for measuring plant development and senescence.