Nitrogen (N) and potassium (K) are key elements for crop growth, yet studies on the impact of N–K interactions on plant N and K status and yield are lacking.  This study aimed to develop effective indicators for diagnosing N and K nutrition and predicting the yield of wheat under N–K interactions based on the theoretical framework of a critical nutrient dilution curve.  A 4-year N–K interaction experiment involving three wheat cultivars was employed for building and validating nutrient indices (NIs) based on the critical N dilution curve (CNDC) and the critical K dilution curve (CKDC).  In addition, relevant data from the literature were collected for supplementary validation.  The results revealed that changes in parameter A1 of the critical K dilution curves (CKDCs) can reflect the impact of nitrogen application on K absorption and utilization.  However, the difference in K nutrition index (KNI) values calculated by CKDC under different N levels was not significant.  Based on the aboveground biomass (AGB), a universal CKDC was established and defined as K_c=3.63AGB^–0.37 under N–K interactions.  The results showed that the direct effects of N or K deficiency on crops could be quantified by the N–K interaction index (NKI) calculated by integrating CNDC and CKDC, and the changes in crop growth in response to proportional N and K concentrations could be determined by NKI as well.  In addition, topdressing N fertilizer at the jointing stage significantly improved the N–K interaction effect on the N nutrition index (NNI) and NKI at the booting stage (P<0.05), but it had no significant N–K interaction effect on the KNI.  All indicators at the heading stage demonstrated the best predictive capability for relative yield (RY) compared to other stages.  Compared with NNI and KNI, the prediction accuracy of yield with NKI improved by 11.63 and 17.44%, respectively.  The NKI has better performance in diagnosing N and K nutrition and predicting yield under N–K interactions than either NNI or KNI.  This result enhances our understanding of the effects of N–K interactions on wheat growth and has important applications for improving the accuracy of N and K nutrition diagnosis and yield prediction.

To evaluate the impact of climate change on maize production, accurately measuring the radiation use efficiency (RUE) of maize is critical.  This study focused on three maize cultivars in Jilin Province, China: Zhengdan 958 (ZD958), Xianyu 335 (XY335), and Liangyu 99 (LY99).  Under the optimal growing conditions for high density planting (9 plants m^–2), the maize RUE was determined during the vegetative and reproductive phases, and the entire growth period.  The results showed that the canopy light interception for maize peaked during anthesis.  After anthesis, maize plant biomass continued to accumulate.  The maize RUE was calculated based on the absorbed photosynthetically active radiation (APAR).  During the entire growth period, maize RUE averaged 5.71 g MJ^–1 APAR among the three cultivars, with a high-to-low order of ZD958 (5.85 g MJ^–1 APAR)>XY335 (5.64 g MJ^–1 APAR)>LY99 (5.07 g MJ^–1 APAR).  Within the vegetative and reproductive growth periods, maize RUE averaged 6.85 and 5.64 g MJ^–1 APAR, respectively.  When utilizing maize models that depend on RUE to predict aboveground biomass accumulation, such as APSIM, the current RUE value of 3.6 g MJ^–1 APAR is considerably lower than the measured value obtained under high-density optimal growing conditions.  Consequently, to derive the optimal potential yield for maize in such planting conditions, we recommend adjusting the RUE to a range of 5.07–5.85 g MJ^–1 APAR.

Timely and accurate forecasting of crop yields is critical for food management and trade.  However, only limited research has explored the impact of integrating crop phenotypic parameters (CPPs) with unmanned aerial vehicle (UAV) data across different phenological stages on maize yield prediction.  The extent to which multi-temporal data enhances the accuracy and reliability of yield projections compared to mono-temporal data has yet to be systematically investigated.  To attain the proper balance between accuracy and cost in crop yield estimation, this study proposed a structured framework for identifying the optimal phenological periods for summer maize yield prediction using UAV-based multispectral data.  Three classical methods of custom mean decrease accuracy (C-MDA), optimal parameters-based geographical detector (OPGD), and grey relational analysis (GRA) were first used to sort and screen both the CPPs and vegetation indices (VIs) derived from UAV-based information over six growth stages.  Ridge regression models based on multi-temporal data combinations and mono-temporal data were established separately, and their performance in yield prediction were compared to identify the optimal phenological stages and the corresponding key factors.  Our results showed that C-MDA was much better at factor screening and ranking compared to OPGD and GRA.  The green normalized difference vegetation index (GNDVI), normalized difference vegetation index (NDVI), and normalized difference red edge index (NDRE) emerged as the top-performing VIs, while the leaf area index (LAI) and above ground biomass (AGB) proved to be the most effective CPPs.  When predicting yield using only mono-temporal data, the dough stage delivered the highest predictive accuracy (R²=0.871, RMSE=0.407 t ha^–1), while the tasseling stage was the earliest that achieved yield estimates with acceptable precision (R²=0.810, RMSE=0.493 t ha^–1).  In contrast, the integration of UAV data from different crop growth stages markedly enhanced the accuracy of yield estimation.  Combinations of data from the tasseling, silking, and dough stages were recommended as the best option (R²=0.942, RMSE=0.291 t ha^–1).  These findings indicate that the precise estimation of maize yields in smallholder fields may be attainable, and present both substantial theoretical insights and practical benefits for the advancement of precision agriculture.

Flowering is a necessary condition and basis for yield in the life cycle of woody fruit trees.  Although there has been considerable interest in the regulatory mechanisms underlying floral induction and flowering, the associated epigenetic modifications remain poorly characterized.  We identified genome-wide DNA methylation changes and the transcriptional responses in axillary buds of ‘Qinguan’ (QA) and ‘Fuji’ (FA) varieties with contrasting flowering behaviors.  The DNA methylation levels were 19.35, 62.96 and 17.68% in FA, and 19.64, 62.49 and 17.86% in QA in the CG, CHG and CHH contexts, respectively.  The number of hypermethylated and hypomethylated differentially methylated regions (DMRs) in different regions contributed to significantly up- and downregulated gene expression.  DNA methylation can positively or negatively regulate gene expression depending on the CG, CHG and CHH contexts and their locations in different regions.  Additionally, the huge differences in transcription of MIKC^c-type MADS-box genes, and multiple flowering genes in multiple flowering pathways (i.e., light, aging, GA and sugar) by changing DNA methylation, contributed to contrasting flowering behaviors in both QA and FA.  Specifically, the floral meristem identity genes (i.e., FT, LEAFY, AP1 and SOC1) exhibited significantly higher expression in QA than FA, but the floral repressors (i.e., SVP, AGL15, and AGL18) showed the opposite trend.  Significant differences in multiple hormone levels were due to differentially expressed genes (DEGs) and their DMRs in hormone synthesis pathways, leading to both contrasting axillary bud outgrowth and flowering behaviors.  These findings reflect the diversity in the epigenetic regulation of gene expression and may be helpful for elucidating the epigenetic regulatory mechanism underlying the axillary bud flowering in apple.

Vapor pressure deficit (VPD), defined as the difference between the actual water vapor pressure and the saturation vapor pressure in the air, is a core indicator of atmospheric aridity.  High VPD induces intensified water loss via plant transpiration, thereby constraining water uptake and photosynthetic capacity.  The dynamic functions and molecular regulatory mechanisms of plasma membrane intrinsic proteins (PIPs), key aquaporins mediating rapid transmembrane water transport, remain unclear during plant responses to high VPD stress.  In this study, we elucidated the regulatory role of SlPIP1;7 in regulating the multi-level adaptation strategy of tomato (Solanum lycopersicum) at the morphological, physiological, and molecular levels under high VPD conditions.  The results indicate that, compared to wild-type (WT) plants, SlPIP1;7 overexpressing (OE) plants exhibit superior growth performance under high VPD conditions.  The overexpression of SlPIP1;7 significantly enhances the reactive oxygen species (ROS) scavenging efficiency, effectively protecting plant cells from oxidative damage.  This protective mechanism for maintaining ROS homeostasis is closely associated with stomatal function.  The overexpression of SlPIP1;7 can regulate stomatal morphology, size, and aperture dynamics, thereby promoting efficient utilization of water and carbon dioxide and enhancing the overall physiological regulatory capacity of plants under stress conditions.  Additionally, we identified the ethylene response factor SlERF4 as an upstream regulatory factor in this adaptive network.  Yeast one-hybrid (Y1H) and dual-luciferase (LUC) assays demonstrate that the transcription factor SlERF4 can bind to the SlPIP1;7 promoter, enhancing its expression and functionality.  This interaction further underscores the pivotal role of SlPIP1;7 in combating high VPD stress.  In summary, our study elucidates the crucial function of SlPIP1;7 in plant response and acclimation to high VPD stress.  These findings expand our understanding of the molecular mechanisms underlying plant acclimation to environmental stresses and provide a reference for future breeding strategies aimed at developing drought-resistant crops.

Bacterial blight (BB) of rice caused by the phytopathogenic bacterium Xanthomonas oryzae pv. oryzae (Xoo) is a disease of global importance.  Xoo utilizes the type III secretion system (T3SS) and its effectors for virulence, and XopM is a conserved T3SS effector in Xanthomonas spp.  However, the virulence function of XopM is largely unknown.  In this study, we show that XopM contributes to Xoo virulence in rice.  We demonstrate that XopM interacts with allene oxide synthase OsAOS3, a key enzyme involved in jasmonic acid (JA) biosynthesis.  The expression levels of OsAOS3 and three homologues of OsAOS were elevated after Xoo infection.  Knockout mutants of OsAOS3 exhibited decreased JA accumulation and reduced resistance to Xoo and X. oryzae pv. oryzicola.  Moreover, JA-related defense genes were downregulated in osaos3 mutants during Xoo infection.  Based on our results, we propose a model showing how XopM hijacks OsAOS3 to interfere with JA-mediated defenses, leading to a suppression of rice immunity.  Our findings reveal a novel virulence strategy where Xanthomonas pathogens interfere with the JA pathway and modulate the host defense response.

The efficient colonization of plant-beneficial Pseudomonas spp. is a prerequisite for their biocontrol capacity.  Prior work revealed that the PcoI/PcoR quorum-sensing (QS) system plays a pivotal role in the root colonization of P. fluorescens 2P24.  During the colonization, strain 2P24 has faced diverse impacts from plant-derived reactive oxygen species and other environmental stress.  However, the molecular mechanism by which the PcoI/PcoR QS system is regulated under unfavored conditions remains unclear.  Thus, in this study, the role of the (p)ppGpp synthetase RelA and the bifunctional (p)ppGpp synthase/hydrolase SpoT in the PcoI/PcoR QS system of P. fluorescens was investigated.  Our data indicated that the deficiency of relA and spoT genes remarkably improved the expression of the pcoI gene, whereas the mutation of the spoT gene significantly repressed the expression of the pcoI gene.  We further demonstrated that the regulation of the PcoI/PcoR QS system by (p)ppGpp was dependent on the function of the trmE gene, which encodes a tRNA modification GTPase.  Furthermore, the mutation of relA, spoT, or both significantly influenced the motility, biofilm formation, oxidative stress, osmotic tolerance, and rhizosphere colonization.  Collectively, our data indicated that the (p)ppGpp signaling pathway mediated by the relA gene and spoT gene was important to the function of the PcoI/PcoR QS system and had important implications for the understanding of the molecular mechanism of (p)ppGpp in epiphytic fitness via TrmE of P. fluorescens.

Root-knot nematodes (RKNs) are the most economically damaging plant-parasitic nematodes globally.  Xinjiang, encompassing one-sixth of China’s landmass, currently lacks comprehensive data regarding the occurrence, distribution, and genetic variation of RKNs infecting vegetables within its borders.  Hence, identifying RKNs species and genetic diversity is crucial for devising comprehensive management strategies.  Between 2021 and 2023, we present a survey of 130 samples, collected from 86 counties across 14 cities in Xinjiang, China, aiming to comprehensively understand the occurrence, distribution, damage, and species of vegetable RKNs.  The results indicated that 57 out of 130 samples collected from the regions of Hami, Tulufan, Ili, Bayingol, Hotan, Aksu, Kashgar, and Kizilsu in Xinjiang were infected by RKNs, suggesting an expansion of RKN disease in the vegetable-producing regions of Xinjiang.  The infected vegetable roots were found to harbor Meloidogyne incognita and M. hapla, with M. incognita being the most prevalent species.  A phylogenetic analysis of the COI region revealed significant evolutionary divergence between M. incognita populations from Xinjiang and those from southeastern provinces.  Haplotype analysis of the COI gene revealed that M. incognita populations are categorized into three major lineages: Asia, Europe, and a combined lineage encompassing both America and Africa.  Notable gene flow patterns were observed among M. incognita populations, with significant migrations from Europe and America to Asia, specifically from the southeastern China towards Xinjiang.  This study’s findings indicate a consistent increase in the detrimental effects of vegetables production caused by RKNs in Xinjiang.  Implementing effective prevention and control measures is crucial to mitigate the spread of RKNs.

The diamondback moth, Plutella xylostella represents a worldwide threat to Brassicaceae crops and has developed substantial resistance to conventional insecticides.  Entomopathogenic fungi (EPF) have emerged as environmentally sustainable alternatives to chemical insecticides.  Since insect immunity constitutes the primary defense against fungal pathogens, understanding these mechanisms could advance biocontrol strategies.  Nevertheless, research on the immune functions of galectins in insects remains limited.  This study identifies a Galectin-4 homolog in P. xylostella (PxGalectin-4) and systematically examines its immunological functions against an EPF Isaria cicadae infection.  The open reading frame of PxGalectin-4 encoded 338 amino acids with a carbohydrate recognition domain (CRD).  PxGalectin-4 expression exhibited peak levels in late-instar larval stages and fat body, and increased significantly following I. cicadae challenge.  Functional characterization demonstrated that recombinant PxGalectin-4 (rPxGalectin-4) directly bound cells and cell wall components of microbes, and displayed Ca²⁺-dependent microbial agglutination.  Additionally, rPxGalectin-4 enhanced hemocyte-mediated immune responses by promoting nodulation and encapsulation, and increased phenoloxidase activity of hemolymph.  Knockdown of PxGalectin-4 significantly increased the susceptibility of P. xylostella larvae to I. cicadae infection.  In conclusion, PxGalectin-4 serves a vital immune function in P. xylostella defense against I.cicadae, and presents a potential target for novel pest control strategies.

The development of novel stimuli-responsive pesticide delivery systems is a highly effective strategy for improving pesticide utilization efficiency while minimizing environmental risks.  A pH-, glutathione-, and chitinase-responsive pesticide delivery system (PYR@MONs-COS) was designed by conjugating chitosan oligosaccharide (COS) with biodegradable disulfide bond-bridged mesoporous silica nanoparticles (MONs) loaded with pyraclostrobin (PYR).  The loading capacity of PYR in the nanoparticles was approximately 13.6%.  The covalent attachment of COS to the modified MONs could effectively protect the active ingredient from photodegradation and prevent premature release of PYR.  During the infection process, physiological and biochemical changes at the infection site, including reduced pH values, increased glutathione levels, and enhanced chitinase activity, facilitated the rapid degradation of disulfide bonds and COS in PYR@MONs-COS, resulting in the rapid release of PYR.  Furthermore, PYR@MONs-COS significantly enhanced the foliar penetration of PYR, improved the adhesion of pesticide droplets, and stimulated callose deposition in rice leaves, thereby enhancing rice immunity.  In antifungal activity assays, PYR@MONs-COS exhibited superior efficacy and prolonged efficacy against Magnaporthe oryzae compared to PYR microcapsules in both in vitro and in vivo experiments.  The phytotoxicity assessment indicated that PYR@MONs-COS was safe for rice plants.  More importantly, PYR@MONs-COS demonstrated a 7.3-fold reduction in acute toxicity to zebrafish compared to PYR technical.  Therefore, the triple-stimuli pesticide delivery system has great potential for rice disease management and provides a promising pathway for the development of sustainable agriculture.