Upconversion Nanoparticles Based Sensing: From Design to Point-of-Care Testing.

Rare earth-doped upconversion nanoparticles (UCNPs) have achieved a wide range of applications in the sensing field due to their unique anti-Stokes luminescence property, minimized background interference, excellent biocompatibility, and stable physicochemical properties. However, UCNPs-based sensing platforms still face several challenges, including inherent limitations from UCNPs such as low quantum yields and narrow absorption cross-sections, as well as constraints related to energy transfer efficiencies in sensing systems. Therefore, the construction of high-performance UCNPs-based sensing platforms is an important cornerstone for conducting relevant research. This work begins by providing a brief overview of the upconversion luminescence mechanism in UCNPs. Subsequently, it offers a comprehensive summary of the sensors' types, design principles, and optimized design strategies for UCNPs sensing platforms. More cost-effective and promising point-of-care testing applications implemented based on UCNPs sensing systems are also summarized. Finally, this work addresses the future challenges and prospects for UCNPs-based sensing platforms.

Enhanced detection of acrylamide using a versatile solid-state upconversion sensor through spectral and visual analysis.

Acrylamide (AM) generally forms in high-temperature processes and has been classified as a potential carcinogen. In this study, we put forward a maneuverable solid-state luminescence sensor using polydimethylsiloxane (PDMS) as the matrix coupled with upconversion nanoparticles as the indicator. The core-shell upconversion nanoparticles emitting cyan light were uniformly encapsulated in PDMS. Then it was further modified with complementary DNA of AM aptamer. The nanocrystalline fluorescein isothiocyanate isomer (FITC), coupled with AM aptamer, was attached to the surface of PDMS. FITC effectively quenched the upconversion luminescence through fluorescence resonance energy transfer (FRET). The introduction of AM resulted in preferentially bound to aptamer caused the separation of the quencher and the donor, and led to luminescence recovery. The developed sensor was applied for both spectral and visual monitoring, demonstrating a detection limit (LOD) of 1.00 nM and 1.07 nM, respectively. Importantly, in the actual foodstuffs detection, there is no obvious difference between the results of this study and the standard method, which indicates the developed method has good accuracy. Therefore, this solid-state sensor has the potential for on-site detection using a smartphone device and an Android application.

Wheat Pm55 alleles exhibit distinct interactions with an inhibitor to cause different powdery mildew resistance.

Powdery mildew poses a significant threat to wheat crops worldwide, emphasizing the need for durable disease control strategies. The wheat-Dasypyrum villosum T5AL·5 V#4 S and T5DL·5 V#4 S translocation lines carrying powdery mildew resistant gene Pm55 shows developmental-stage and tissue-specific resistance, whereas T5DL·5 V#5 S line carrying Pm5V confers resistance at all stages. Here, we clone Pm55 and Pm5V, and reveal that they are allelic and renamed as Pm55a and Pm55b, respectively. The two Pm55 alleles encode coiled-coil, nucleotide-binding site-leucine-rich repeat (CNL) proteins, conferring broad-spectrum resistance to powdery mildew. However, they interact differently with a linked inhibitor gene, SuPm55 to cause different resistance to wheat powdery mildew. Notably, Pm55 and SuPm55 encode unrelated CNL proteins, and the inactivation of SuPm55 significantly reduces plant fitness. Combining SuPm55/Pm55a and Pm55b in wheat does not result in allele suppression or yield penalty. Our results provide not only insights into the suppression of resistance in wheat, but also a strategy for breeding durable resistance.

A dual-mode fluorescence and colorimetric sensing platform for efficient detection of ofloxacin in aquatic products using iron alkoxide nanozyme.

Trace detection of ofloxacin (OFL) with high sensitivity, reliability, and visual clarity is challenging. To address this, a novel dual-modal aptasensor with fluorescence-colorimetric capabilities was designed that exploit the target-induced release of 3,3',5,5'-tetramethylbenzidine (TMB) molecules from aptamer-gated mesoporous silica nanoparticles (MSNs), the oxidase-like activity of iron alkoxide (IA) nanozyme, and the fluorescence attributes of core-shell upconversion nanoparticles. Therefore, the study reports a dual mode detection, with a fluorescence detection range for OFL spanning from 0.1 µg/kg to 1000 µg/kg (and a detection limit of 0.048 µg/kg). Additionally, the colorimetric method offered a linear detection range of 0.3 µg/kg to 1000 µg/kg, with a detection limit of 0.165 µg/kg. The proposed biosensor had been successfully applied to the determination of OFL content in real samples with satisfactory recoveries (78.24-96.14 %).

Estimating BDS-3 Satellite Differential Code Biases with the Single-Frequency Uncombined PPP Model.

Differential Code Bias (DCB) is a crucially systematic error in satellite positioning and ionospheric modeling. This study aims to estimate the BeiDou-3 global navigation satellite system (BDS-3) satellite DCBs by using the single-frequency (SF) uncombined Precise Point Positioning (PPP) model. The experiment utilized BDS-3 B1 observations collected from 25 International GNSS Service (IGS) stations located at various latitudes during March 2023. The results reveal that the accuracy of estimating B1I-B3I DCBs derived from single receiver exhibits latitude dependence. Stations in low-latitude regions show considerable variability in the root mean square (RMS) of absolute offsets for satellite DCBs estimation, covering a wide range of values. In contrast, mid- to high-latitude stations demonstrate a more consistent pattern with relatively stable RMS values. Moreover, it has been observed that the stations situated in the Northern Hemisphere display a higher level of consistency in the RMS values when compared to those in the Southern Hemisphere. When incorporating estimates from all 25 stations, the RMS of the absolute offsets in satellite DCBs estimation consistently remained below 0.8 ns. Notably, after excluding 8 low-latitude stations and utilizing data from the remaining 17 stations, the RMS of absolute offsets in satellite DCBs estimation decreased to below 0.63 ns. These enhancements underscore the importance of incorporating a sufficient number of mid- and high-latitude stations to mitigate the effects of ionospheric variability when utilizing SF observations for satellite DCBs estimation.

Genetic basis of resistance against powdery mildew in the wheat cultivar "Tabasco".

European winter wheat cultivar "Tabasco" was reported to have resistance to powdery mildew disease caused by Blumeria graminis f. sp. tritici (Bgt) in China. In previous studies, Tabasco was reported to have the resistance gene designated as Pm48 on the short arm of chromosome 5D when a mapping population was phenotyped with pathogen isolate Bgt19 collected in China and was genotyped with simple sequence repeat (SSR) markers. In this study, single-nucleotide polymorphism (SNP) chips were used to rapidly determine the resistance gene by mapping a new F2 population that was developed from Tabasco and a susceptible cultivar "Ningmaizi119" and inoculated with pathogen isolate NCF-D-1-1 that was collected in the USA. The segregation of resistance in the population was found to link with Pm2 which was identified in Tabasco. Therefore, it was concluded that the previously reported Pm48 on chromosome arm 5DS in Tabasco should be the Pm2 gene on the same chromosome. The Pm2 was also found in European cultivars "Mattis" and "Claire" but not in any of the accessions from diploid wheat Aegilops tauschii or modern cultivars such as "Gallagher," "Smith's Gold," and "OK Corral" being used in the Great Plains in the USA. A KASP marker was developed to track the resistance allele Pm2 in wheat breeding. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-023-01402-3.

Enhanced detection of endocrine disrupting chemicals in on-chip microfluidic biosensors using aptamer-mediated bridging flocculation and upconversion luminescence.

Exposure to endocrine-disrupting chemicals (EDCs) can lead to detrimental impacts on human health, making their detection a critical issue. A novel approach utilizing on-chip microfluidic biosensors was developed for the simultaneous detection of two EDCs, namely, bisphenol A (BPA) and diethylstilbestrol (DES), based on upconversion nanoparticles doped with thulium (Tm) and erbium (Er), respectively. From the perspective of single nanoparticles, the construction of an active core-inert shell structure enhanced the luminescence of nanoparticles by 2.28-fold (Tm) and 1.72-fold (Er). From the perspective of the nanoparticle population, the study exploited an aptamer-mediated bridging flocculation mechanism and effectively enhanced the upconversion luminescence of biosensors by 8.94-fold (Tm) and 7.10-fold (Er). A chip with 138 tangential semicircles or quarter-circles was designed and simulated to facilitate adequate mixing, reaction, magnetic separation, and detection conditions. The on-chip microfluidic biosensor demonstrated exceptional capabilities for the simultaneous detection of BPA and DES with ultrasensitive detection limits of 0.0076 µg L-1, and 0.0131 µg L-1, respectively. The first reported aptamer-mediated upconversion nanoparticle bridging flocculation provided enhanced luminescence and detection sensitivity for biosensors, as well as offering a new perspective to address the instability of nanobiosensors.

On-line monitoring of total sugar during kombucha fermentation process by near-infrared spectroscopy: Comparison of linear and non-linear multiple calibration methods.

Kombucha is widely recognized for its health benefits, and it facilitates high-quality transformation and utilization of tea during the fermentation process. Implementing on-line monitoring for the kombucha production process is crucial to promote the valuable utilization of low-quality tea residue. Near-infrared (NIR) spectroscopy, together with partial least squares (PLS), backpropagation neural network (BPANN), and their combination (PLS-BPANN), were utilized in this study to monitor the total sugar of kombucha. In all, 16 mathematical models were constructed and assessed. The results demonstrate that the PLS-BPANN model is superior to all others, with a determination coefficient (R2p) of 0.9437 and a root mean square error of prediction (RMSEP) of 0.8600 g/L and a good verification effect. The results suggest that NIR coupled with PLS-BPANN can be used as a non-destructive and on-line technique to monitor total sugar changes.

Application of visible-near infrared spectroscopy in tandem with multivariate analysis for the rapid evaluation of matcha physicochemical indicators.

Consumer preference for matcha is heavily influenced by its physicochemical properties. The visible-near infrared (Vis-NIR) spectroscopy technology coupled with multivariate analysis was investigated for rapid and non-invasive evaluation of particle size and the ratio of tea polyphenols to free amino acids (P/F ratio) of matcha. The multivariate selection algorithms such as synergy interval (Si), variable combination population analysis (VCPA), competitive adaptive reweighted sampling (CARS), and interval combination population analysis (ICPA) were compared, and eventually, the variable selection strategy of ICPA and CARS hybridization was firstly proposed for selecting the characteristic wavelengths from Vis-NIR spectra to build partial least squares (PLS) models. Results indicated that the ICPA-CARS-PLS models achieved satisfactory performance for the evaluation of matcha particle size (Rp = 0.9376) and P/F ratio (Rp = 0.9283). Hence the rapid, effectual, and nondestructive online monitoring, Vis-NIR reflectance spectroscopy in tandem with chemometric models is significant for the industrial production of matcha.

Feasibility of an NIR spectral calibration transfer algorithm based on optimized feature variables to predict tobacco samples in different states.

The prediction accuracy of calibration models for near-infrared (NIR) spectroscopy typically relies on the morphology and homogeneity of the samples. To achieve non-homogeneous tobacco samples for non-destructive and rapid analysis, a method that can predict tobacco filament samples using reliable models based on the corresponding tobacco powder is proposed here. First, as it is necessary to establish a simple and robust calibrated model with excellent performance, based on full-wavelength PLSR (Full-PLSR), the key feature variables were screened by three methods, namely competitive adaptive reweighted sampling (CARS), variable combination population analysis-iteratively retaining informative variables (VCPA-IRIV), and variable combination population analysis-genetic algorithm (VCPA-GA). The partial least squares regression (PLSR) models for predicting the total sugar content in tobacco were established based on three optimal wavelength sets and named CARS-PLSR, VCPA-IRIV-PLSR and VCPA-GA-PLSR, respectively. Subsequently, they were combined with different calibration transfer algorithms, including calibration transfer based on canonical correlation analysis (CTCCA), slope/bias correction (S/B) and non-supervised parameter-free framework for calibration enhancement (NS-PFCE), to evaluate the best prediction model for the tobacco filament samples. Compared with the previous two transfer algorithms, NS-PFCE performed the best under various wavelength conditions. The prediction results indicated that the most successful approach for predicting the tobacco filament samples was achieved by VCPA-IRIV-PLSR when coupled with the NS-PFCE method, which obtained the highest determination coefficient (Rp2 = 0.9340) and the lowest root mean square error of the prediction set (RMSEP = 0.8425). VCPA-IRIV simplifies the calibration model and improves the efficiency of model transfer (31 variables). Furthermore, it pledges the prediction accuracy of the tobacco filament samples when combined with NS-PFCE. In summary, calibration transfer based on optimized feature variables can eliminate prediction errors caused by sample morphological differences and proves to be a more beneficial method for online application in the tobacco industry.

Competitive Ratiometric Aptasensing with Core-Internal Standard-Shell Structure Based on Surface-Enhanced Raman Scattering.

Reproducibility and stability are important indicators for the evaluation of quantitative sensing methods based on surface-enhanced Raman scattering (SERS) technology. Developing a SERS substrate with self-calibration capabilities is vital for effectively quantifying targets. In this work, a competitive ratiometric SERS aptasensor was developed. 4-Aminothiophenol as an internal standard (IS) was embedded in the substrate followed by gradually loading with the aptamer and methylene blue functionalizing of the complementary sequences of the aptamer (MB-cDNA). Recognition and binding of the target to the aptamer resulted in the shedding of MB-cDNA after magnetic separation reducing the SERS signal of MB, allowing for the ratiometric determination of the target based on the constant intensity from the IS. For the selective detection of okadaic acid (OA), a good negative correlation was achieved between the SERS ratiometric intensity and OA concentration in the range of 0.5-100 ng/mL. The magnetic separation strategy effectively simplifies the production steps of the aptasensor, and the ratiometric strategy effectively improved the reproducibility and stability of the OA sensing. This ratiometric aptasensor has been successfully employed to detect OA in food and environmental samples and is expected to be extended to detect other targets.

Bipyridine-mediated fluorescence charge transfer process based on copper ion grafted upconversion nanoparticle platform for ciprofloxacin sensing in aquatic products.

In this work, an ultrasensitive ciprofloxacin (CIP) detection strategy has been established based on copper (Cu2+) ions-induced strong charge transfer in poly acrylic acid (PAA) functionalized upconversion nanoparticles (UCNPs)/2,2-bipyridine (bipy) system. The positively charged Cu2+ ions electrostatically adhere to the surface of the PAA-UCNPs and deactivate the fluorescence via a charge transfer process. The bipy in this hybrid system controls the aggregation by chelating in proximity to the Cu2+ center. Due to the strong affinity between pyridone oxygen and carboxy oxygen, CIP coordinates in high stoichiometry with the bipy-Cu complex as compared to the PAA-UCNPs, causing the trapped fluorescence to be released in an amount equivalent to the target concentration. Under the optimum assay conditions, a good calibration plot (0.05-1000 ng/mL) was acquired with a detection limit of 0.13 ng/mL. The satisfactory recoveries (85.93-96.87%) for real prawn and fish samples were further validated by enzyme-linked immunoassays (P > 0.05).

Selective detection of carbendazim using a upconversion fluorescence sensor modified by biomimetic molecularly imprinted polymers.

The persistence of carbendazim residues in the food chain poses a potential risk to human health. Therefore, an eco-friendly selective and sensitive fluorescence nanosensor was established for carbendazim determination based on molecularly imprinted polymer (MIP) modified upconversion nanoparticles (UCNPs). The molecularly imprinted coating with methacrylamide as a functional monomer and carbendazim as a template molecule grafted on the UCNPs (UCNPs@MIP) constituted fluorescent recognition elements. The fluorescence emission of UCNPs@MIP significantly declined in the presence of carbendazim due to electron transfer induced by its selective binding with MIP cavities. The quenched fluorescence of UCNPs@MIP was recovered once the template carbendazim was eluted from the probe system. Under the optimized conditions, the proposed method offers a good linear correlation between 0.01 and 1 µg/mL, with a limit of detection (LOD) of 0.0036 µg/mL for carbendazim residues. The analytical utility and reliability of the developed biomimetic platform were examined in real food samples with good recoveries (88.790%∼102.675%) and relative standard deviation (RSD) values (0.491%∼3.779%). The method was further validated by a standard HPLC method in terms of student's t-test (p > 0.05) with no significant differences between the two methods. Hence, the proposed fluorescence sensor has prospects for rapid determination of carbendazim.

Across different instruments about tobacco quantitative analysis model of NIR spectroscopy based on transfer learning.

With the development of near-infrared (NIR) spectroscopy, various calibration transfer algorithms have been proposed, but such algorithms are often based on the same distribution of samples. In machine learning, calibration transfer between types of samples can be achieved using transfer learning and does not need many samples. This paper proposed an instance transfer learning algorithm based on boosted weighted extreme learning machine (weighted ELM) to construct NIR quantitative analysis models based on different instruments for tobacco in practical production. The support vector machine (SVM), weighted ELM, and weighted ELM-AdaBoost models were compared after the spectral data were preprocessed by standard normal variate (SNV) and principal component analysis (PCA), and then the weighted ELM-TrAdaBoost model was built using data from the other domain to realize the transfer from different source domains to the target domain. The coefficient of determination of prediction (R 2) of the weighted ELM-TrAdaBoost model of four target components (nicotine, Cl, K, and total nitrogen) reached 0.9426, 0.8147, 0.7548, and 0.6980. The results demonstrated the superiority of ensemble learning and the source domain samples for model construction, improving the models' generalization ability and prediction performance. This is not a bad approach when modeling with small sample sizes and has the advantage of fast learning.

Rapid identification and deployment of major genes for flowering time and awn traits in common wheat.

Molecular markers are developed to accelerate deployment of genes for desirable traits segregated in a bi-parental population of recombinant inbred lines (RILs) or doubled haplotype (DH) lines for mapping. However, it would be the most effective if such markers for multiple traits could be identified in an F2 population. In this study, single nucleotide polymorphisms (SNP) chips were used to identify major genes for heading date and awn in an F2 population without developing RILs or DH lines. The population was generated from a cross between a locally adapted spring wheat cultivar "Ningmaizi119" and a winter wheat cultivar "Tabasco" with a diverse genetic background. It was found that the dominant Vrn-D1 allele could make Ningmaizi119 flowered a few months earlier than Tabasco in the greenhouse and without vernalization. The observed effects of the allele were validated in F3 populations. It was also found that the dominant Ali-A1 allele for awnless trait in Tabasco or the recessive ali-A1 allele for awn trait in Ningmaizi119 was segregated in the F2 population. The allelic variation in the ALI-A1 gene relies not only on the DNA polymorphisms in the promoter but also on gene copy number, with one copy ali-A1 in Ningmaizi119 but two copies Ali-A1 in Tabasco based on RT-PCR results. According to wheat genome sequences, cultivar "Mattis" has two copies Ali-A1 and cultivar "Spelta" has four copies Ali-A in a chromosome that was uncharacterized (ChrUN), in addition to one copy on chromosome 5A. This study rapidly characterized the effects of the dominant Vrn-D1 allele and identified the haplotype of Ali-A1 in gene copy number in the F2 segregation population of common wheat will accelerate their deployment in cycling lines in breeding.

Recyclable flexible upconversion-luminescence sensing platform for quantifying sulfite based on inner filter effect.

The widespread applications of sulfur dioxide and its derivatives is a double-edged sword in terms of ensuring environmental and food safety. In this work, a recyclable flexible upconversion-luminescence sensor was developed for the determination of sulfite in environmental and foodstuff samples. The upconversion nanoparticles (UCNPs) were uniformly doped with polydimethylsiloxane (PDMS) prepolymer and moulded to prepare a flexible upconversion-luminescence substrate, which was further modified with pararosaniline (PRA) dye based on the typical carbodiimide coupling procedure. The principle of the work was based on the inner filter effect (IFE) mechanism between PRA dye and UCNPs. In the presence of target sulfite ions, it selectively binds to PRA moieties fixed on the surface of the flexible sensor, resulting in its bleaching and restoration of the upconversion fluorescence. Under the optimized conditions, a linear response for sulfite concentration in the range of 10-100 nM was obtained. The limit of detection was calculated as 2.24 nM, and the proposed sensor was successfully regenerated and recycled six times. The method was applied in real rainwater samples with spiked recoveries in the range of 94.85%-99.39%, and the coefficient of variation ranged from 1.65% to 4.93%. Hence, the proposed flexible upconversion-luminescence sensor held the attractive potential for efficient sulfite determination in real environmental and food samples.

TaCol-B5 modifies spike architecture and enhances grain yield in wheat.

Spike architecture influences grain yield in wheat. We report the map-based cloning of a gene determining the number of spikelet nodes per spike in common wheat. The cloned gene is named TaCOL-B5 and encodes a CONSTANS-like protein that is orthologous to COL5 in plant species. Constitutive overexpression of the dominant TaCol-B5 allele but without the region encoding B-boxes in a common wheat cultivar increases the number of spikelet nodes per spike and produces more tillers and spikes, thereby enhancing grain yield in transgenic plants under field conditions. Allelic variation in TaCOL-B5 results in amino acid substitutions leading to differential protein phosphorylation by the protein kinase TaK4. The TaCol-B5 allele is present in emmer wheat but is rare in a global collection of modern wheat cultivars.

Tunable multiplexed fluorescence biosensing platform for simultaneous and selective detection of paraquat and carbendazim pesticides.

The monitoring of multiple pesticides commonly used in food is a prerequisite for public health safety. Herein, a multiplexed biosensor based on fluorescence resonance energy transfer (FRET) from multicolor upconversion nanoparticles (UCNPs)to single black phosphorus nanosheets (BPNSs) was successfully developed for simultaneous and selective detection of paraquat and carbendazim pesticides. Due to the strong π-π stacking interactions, aptamers functionalized UCNPs may adsorb on the BPNSs surface, allowing strong upconversion fluorescence quenching. In the presence of paraquat and carbendazim, the aptamers preferentially integrated with their corresponding targets and altered the aptamer's conformation, restoring the fluorescence. An excellent linear correlation was observed from 1.0 to 1.0 × 105 ng/mL, with a limit of detection of 0.18 ng/mL for paraquat and 0.45 ng/mL for carbendazim. The developed aptasensor was further validated by commercial enzyme-linked immunoassays without significant differences in practical detection. Additionally, this work offers new insights into monitoring multiple targets simultaneously.

Physicochemical indicators coupled with multivariate analysis for comprehensive evaluation of matcha sensory quality.

The sensory quality of matcha is a pivotal factor in determining consumer acceptance. However, the human sensory panel test is difficult to popularize by virtue of professional requirements and inability to evaluate large samples. The analysis showed that physicochemical indicators of matcha were significantly related to sensory quality. Hence, principal component analysis (PCA) based on selected key physicochemical indicators was proposed to evaluate the sensory quality of matcha in this research. The eight key indicators were selected from twenty-four physicochemical indicators based on least absolute shrinkage and selection operator (LASSO) for the establishment of the PCA comprehensive evaluation model. The results demonstrated that the PCA comprehensive evaluation model achieved superior performance, with -0.895 rc (correlation coefficient in calibration set) and -0.883 rp (correlation coefficient in prediction set) for overall sensory quality. This work demonstrated that LASSO-PCA comprehensive evaluation as an objective protocol has great potential in predicting matcha sensory quality.

Overexpression of TaSTT3b-2B improves resistance to sharp eyespot and increases grain weight in wheat.

STAUROSPORINE AND TEMPERATURE SENSITIVE3 (STT3) is a catalytic subunit of oligosaccharyltransferase, which is important for asparagine-linked glycosylation. Sharp eyespot, caused by the necrotrophic fungal pathogen Rhizoctonia cerealis, is a devastating disease of bread wheat. However, the molecular mechanisms underlying wheat defense against R. cerealis are still largely unclear. In this study, we identified TaSTT3a and TaSTT3b, two STT3 subunit genes from wheat and reported their functional roles in wheat defense against R. cerealis and increasing grain weight. The transcript abundance of TaSTT3b-2B was associated with the degree of wheat resistance to R. cerealis and induced by both R. cerealis and exogenous jasmonic acid (JA). Overexpression of TaSTT3b-2B significantly enhanced resistance to R. cerealis, grain weight, and JA content in transgenic wheat subjected to R. cerealis stress, while silencing of TaSTT3b-2B compromised resistance of wheat to R. cerealis. Transcriptomic analysis showed that TaSTT3b-2B affected the expression of a series of defense-related genes and JA biosynthesis-related genes, as well as genes coding starch synthase and sucrose synthase. Application of exogenous JA elevated expression levels of the abovementioned defense- and grain weight-related genes, and rescuing the resistance of TaSTT3b-2B-silenced wheat to R. cerealis, while pretreatment with sodium diethyldithiocarbamate, an inhibitor of JA synthesis, attenuated the TaSTT3b-2B-mediated resistance to R. cerealis, suggesting that TaSTT3b-2B played critical roles in regulating R. cerealis resistance and grain weight via JA biosynthesis. Altogether, this study reveals new functional roles of TaSTT3b-2B in regulating plant innate immunity and grain weight, and illustrates its potential application value for wheat molecular breeding.