Soil salinization threatens ecosystem health, yet quantitative impacts on bacterial diversity and function remain unclear. Here we integrate a global meta-analysis with a regional field study. Salinization increased soil pH (2.9%) and bulk density (7.2%) while reducing clay content (28%). Beyond a threshold of 2.58 dS/m, bacterial Shannon diversity declined nonlinearly and richness decreased sharply. Communities shifted toward salt-tolerant Bacteroidetes (36.4% increase) and Firmicutes (34.2%), while sensitive Acidobacteria and Actinobacteria declined (95.3% and 18.3%). Random forest modeling identified sodium and magnesium ions as primary drivers. Functional gene analysis revealed nonlinear decreases in carbon, nitrogen, and phosphorus cycling genes past thresholds, but sulfur cycling genes were stimulated. Co-occurrence networks indicate environmental filtering and reduced complexity under salt stress, yet carbon metabolic functions maintain high connectivity, suggesting functional persistence among salt-adapted taxa. Collectively, salinization restructures bacterial communities via niche-based assembly ion-nutrient-physical interactions, creating microbial critical transition threshold for predicting ecosystem stimulation.

Yield is one of the core goals of crop breeding. By predicting the potential yield of different breeding materials, breeders can screen these materials at various growth stages to select the best performing. Based on unmanned aerial vehicle remote sensing technology, high-throughput crop phenotyping data in breeding areas is collected to provide data support for the breeding decisions of breeders. However, the accuracy of current yield predictions still requires improvement, and the usability and user-friendliness of yield forecasting tools remain suboptimal. To address these challenges, this study introduces a hybrid method and tool for crop yield prediction, designed to allow breeders to interactively and accurately predict wheat yield by chatting with a large language model (LLM). First, the newly designed data assimilation algorithm is used to assimilate the leaf area index into the WOFOST model. Then, selected outputs from the assimilation process, along with remote sensing inversion results, are used to drive the time-series temporal fusion transformer model for wheat yield prediction. Finally, based on this hybrid method and leveraging an LLM with retrieval augmented generation technology, we developed an interactive yield prediction Web tool that is user-friendly and supports sustainable data updates. This tool integrates multi-source data to assist breeding decision-making. This study aims to accelerate the identification of high-yield materials in the breeding process, enhance breeding efficiency, and enable more scientific and smart breeding decisions.

Vicia villosa Roth var. glabrescens (smooth vetch) is an economically important legume cover crop valued for its nitrogen-fixing capacity, high biomass yield, and adaptability across diverse agroecosystems. Here, we present a chromosome-scale, high-quality genome assembly of V. villosa var. glabrescens, constructed using PacBio HiFi sequencing combined with Hi-C scaffolding. The assembly spans 3.70 Gb with a scaffold N50 of 4.69 Mb and exhibits lower heterozygosity (0.9%) compared to V. villosa Roth (3.1%). Genome analysis revealed significant expansion of long terminal repeat retrotransposons (LTR-RTs), as well as lineage-specific proliferation of miniature inverted-repeat transposable elements (MITEs) in V. villosa var. glabrescens. Comparative genomics with V. villosa Roth highlighted gene family expansions associated with trichome development, providing insights into the genetic basis of morphological and adaptive differences within the Vicia species. This reference genome provides a foundational resource for accelerating the breeding of V. villosa varieties with enhanced agronomic traits and contributes to a broader understanding of legume genomics and plant genome evolution.

IntroductionAlfalfa is the most widely cultivated high-quality perennial leguminous forage crop in the world. In China, saline-alkali land represents an important yet underutilized land resource. Cultivating salt-tolerant alfalfa varieties is crucial for the effective development and utilization of saline-alkali soils and for promoting the sustainable growth of grassland-livestock farming in these regions. The NAC (NAM, ATAF, and CUC) family of transcription factors plays a key role in regulating gene expression in response to various abiotic stresses, such as drought, salinity and extreme temperatures, thereby enhancing plant stress tolerance.MethodsThis study evaluated the structure and evolutionary relationship of the members of the NAC-like transcription factor family in alfalfa using bioinformatics. We identified 114 members of the NAC gene family in the Zhongmu No.1 genome and classified them into 13 subclasses ranging from I to XIII. The bioinformatics analysis showed that subfamily V might be related to the response to salt stress. Gene expression analysis was conducted using RNA-seq and qRT-PCR, and MsNAC40 from subfamily V was chosen for further investigation into salt tolerance.ResultsMsNAC40 gene had an open reading frame of 990 bp and encoded a protein containing 329 amino acids, with a molecular weight of 3.70 KDa and a conserved NAM structural domain. The protein was hydrophilic with no transmembrane structure.After treating both the MsNAC40 overexpressing plants and the control group with 150 mmol/L NaCl for 15 days, physiological and biochemical measurements revealed that these plants had significantly greater height, net photosynthetic rate, stomatal conductance, and transpiration rate compared to the control group, while their conductivity was significantly lower. Additionally, the levels of abscisic acid in the roots and leaves, along with the activities of peroxidase, superoxide dismutase, and catalase in the leaves, were significantly higher in the overexpressing plants, whereas the malondialdehyde content was significantly lower. Moreover, the Na+ content in the overexpressing plants was significantly reduced, while the K+/Na+ ratio was significantly increased compared to the control group.DiscussionThese results indicated that the MsNAC40 gene improved the salt tolerance of Pioneer Alfalfa SY4D, but its potential mechanism of action still needs to be further explored.

As the last stage of leaf development, senescence is orchestrated by an intricate network of endogenous factors and external signals to ensure an efficient recycling of nutrients. Hydrogen sulfide (H2S) serves as an important gaseous signaling molecule in plants, mediating a myriad of physiological processes like leaf senescence. However, the molecular mechanisms underlying H2S accumulation and its regulation during leaf senescence in tobacco are still not fully elucidated. In this work, we demonstrate that NtWRKY75, a WRKY transcription factor in tobacco (Nicotiana tabacum), serves as a negative regulator of the expression of the key genes involved in H2S biosynthesis (l-cysteine desulfhydrase, NtLCD1; d-cysteine desulfhydrase, NtDCD1), thereby accelerating dark-induced leaf senescence. The transcript levels of NtWRKY75 are progressively upregulated during both dark-induced and natural leaf senescence. Transgenic tobacco plants overexpressing NtWRKY75 show premature leaf senescence, while ntwrky75 mutants generated through CRISPR/Cas9 exhibit delayed leaf senescence. Further molecular and biochemical analyses reveal that senescence-associated NtWRKY75 binds to the promoters of NtDCD1 and NtOASA1, downregulating NtDCD1 expression while upregulating NtOASA1, thereby leading to decreased H2S accumulation. NtWRKY75 also interacts with the promoters of multiple amino acid transporter genes, including NtAAP3, resulting in their upregulation and facilitating amino acid remobilization, which accelerates leaf senescence. Additionally, NtVQ47, a protein containing the VQ motif, physically interacts with NtWRKY75 in vivo and in vitro, thereby fine-tuning its transcriptional activity and influencing leaf senescence. In conclusion, our findings demonstrate that the regulatory network composed of NtVQ47, NtWRKY75, and H2S plays a crucial role in precisely modulating leaf senescence, offering promising candidates and strategies for future crop improvement.

Increasing combined heat and drought extremes due to climate change heighten the risk of crop failure, underscoring the need for improved stress diagnosis for effective management strategies. However, current plant physiology indicators struggle to differentiate crop stresses in hot-dry environments. This study proposes using specific leaf metabolites, detectable by leaf reflectance spectra, for more precise identification of heat and drought stress compared to traditional methods. We conducted two rounds of one-week drought treatments under heat stress on soybean seedlings. Throughout the experiment, we monitored stomatal conductance, reflectance spectra, and metabolites, including Abscisic Acid (ABA), Jasmonic Acid (JA), Salicylic Acid (SA), and proline (Pro), on a daily basis. Our findings revealed that ABA and JA exhibited differential sensitivities to drought and heat stress, respectively. In contrast, stomatal conductance was unable to differentiate between the two stressors. Using partial least-squares regression (PLSR), we determined that both ABA and JA could be detected via leaf spectroscopy with moderate predictive performance (R2 = 0.53, relative RMSE =14.28 %; R2 = 0.53, relative RMSE = 14.96 %) and exhibited distinct sensitive spectral signatures. The metabolite-derived, stress-specific spectral models enable more precise and earlier diagnosis and differentiation of stress in a hotdry environment than traditional physiological indicators (e.g., relying on stomatal conductance). This study provides an example of using metabolites as novel stress indicators, which could contribute to precision agriculture, offering the potential for accurate, stress-specific, and pre-physiological detection of crop health.

UAV remote sensing technology has become a key technology in crop breeding, which can achieve high-throughput and non-destructive collection of crop phenotyping data. However, the multidisciplinary nature of breeding has brought technical barriers and efficiency challenges to knowledge mining. Therefore, it is important to develop a smart breeding goal tool to mine cross-domain multimodal data. Based on different pre-trained open-source multimodal large language models (MLLMs) (e.g., Qwen-VL, InternVL, Deepseek-VL), this study used supervised fine-tuning (SFT), retrieval-augmented generation (RAG), and reinforcement learning from human feedback (RLHF) technologies to inject cross-domain knowledge into MLLMs, thereby constructing multiple multimodal large language models for wheat breeding (WBLMs). The above WBLMs were evaluated using the newly created evaluation benchmark in this study. The results showed that the WBLM constructed using SFT, RAG and RLHF technologies and InternVL2-8B has leading performance. Then, subsequent experiments were conducted using the WBLM. Ablation experiments indicated that the combination of SFT, RAG, and RLHF technologies can improve the overall generation performance, enhance the generated quality, balance the timeliness and adaptability of the generated answer, and reduce hallucinations and biases. The WBLM performed best in wheat yield prediction using cross-domain data (remote sensing, phenotyping, weather, germplasm) simultaneously, with R2 and RMSE of 0.821 and 489.254 kg/ha, respectively. Furthermore, the WBLM can generate professional decision support answers for phenotyping estimation, environmental stress assessment, target germplasm screening, cultivation technique recommendation, and seed price query tasks.

Protein kinases play important roles in regulating the response to various abiotic stress in plants, of which Calcineurin B-like protein-interacting protein kinases (CIPKs) are important components of Ca2 + signaling pathway under abiotic stress. Here we characterized an abiotic stress-induced CIPK gene (MsCIPK4) from alfalfa (Medicago sativa), which was predominantly expressed in the roots. The deduced MsCIPK4 protein encodes 410 amino acids, and contains four conserved domains (e.g. ATP binding site, NAF motif, activation loop, and PPI motif). Subcellular localization assay revealed that MsCIPK4 was targeted to the endoplasmic reticulum. Furthermore, yeast two-hybrid assays showed that MsCIPK4 was able to interact with several CBL proteins (e.g. MsCBL2, MsCBL6, MsCBL7, and MsCBL10). Over-expression of MsCIPK4 in Arabidopsis elevated root length, seed germination and plant growth under NaCl and drought treatment as well as increased SOD, POD and CAT activity and decreased MDA content. Elevated expression of stress-related genes (e.g. ATPase, P5CS, CYP705A5, COR47, HAK5, and RD2) was also observed in the MsCIPK4-over-expressing alfalfa lines. In the transgenic alfalfa, the enzymatic activity of SOD, POD, and CAT increased, whereas MDA content decreased under 200 mM NaCl and 20 % PEG treatments. Collectively, these results suggested that MsCIPK4 was positively associated with the abiotic stress tolerance, which provides valuable reference for molecular breeding of stress tolerance alfalfa.

Background: Alfalfa (Medicago sativa) is one of the most valuable forages in the world. As an outcrossing species, it needs bright flowers to attract pollinators to deal with self-incompatibility. Although various flower colors have been observed and described in alfalfa a long time ago, the biochemical and molecular mechanism of its color formation is still unclear. Methods: By analyzing alfalfa lines with five contrasting flower colors including white (cream-colored), yellow, lavender (purple), dark purple and dark blue, various kinds and levels of anthocyanins, carotenoids and other flavonoids were detected in different colored petals, and their roles in color formation were revealed. Results: Notably, the content of delphinidin-3,5-O-diglucoside in lines 3, 4 and 5 was 58.88, 100.80 and 94.07 times that of line 1, respectively. Delphinidin-3,5-O-diglucoside was the key factor for purple and blue color formation. Lutein and β-carotene were the main factors for the yellow color formation. By analyzing differentially expressed genes responsible for specific biochemical pathways and compounds, 27 genes were found to be associated with purple and blue color formation, and 14 genes were found to play an important role in yellow color formation. Conclusions: The difference in petal color between white, purple and blue petals was mainly caused by the accumulation of delphinidin-3,5-O-diglucoside. The difference in petal color between white and yellow petals was mainly affected by the production of lutein and β-carotene. These findings provide a basis for understanding the biochemical and molecular mechanism of alfalfa flower color formation.

Soil salinisation poses a significant threat to alfalfa (Medicago sativa L.) growth and development, limiting its productivity and hindering its widespread cultivation. Hydrogen sulphide (H2S) serves as an important gaseous signalling molecule in plants, mediating a myriad of physiological processes like salt tolerance. However, the molecular mechanisms underlying H2S accumulation and its regulation under salinity stress in alfalfa are still not fully elucidated. In this study, we demonstrated that MsNAC2a, a NAC transcription factor, is a negative modulator of salt stress resistance in alfalfa. Constitutive overexpression of MsNAC2a downregulated the expression of H2S biosynthesis-related genes, such as L-CYSTEINE DESULFHYDRASE1 (MsLCD1), and upregulated the O-ACETYLSERINE(THIOL)LYASE ISOFORM A1 (MsOASA1) gene, a key gene involved in H2S metabolism, while also suppressing the expression of reactive oxygen species (ROS) scavenging genes like MsCOX11, leading to a reduction in hydrogen sulphide levels and an increase in ROS accumulation, ultimately impairing the plant's salt tolerance. Furthermore, the AP2/EREBP-type transcription factor MsEREBP1 physically interacts with MsNAC2a both in vivo and in vitro, influencing its transcriptional activity and modulating salt stress responses in alfalfa. Conversely, silencing MsNAC2a enhanced salt stress resistance without affecting plant growth or yield. Collectively, our study highlights that MsNAC2a precisely regulates the homeostasis of salt stress responses and provides new insights into the mechanisms by which the cooperative interaction between MsNAC2a and MsEREBP1 fine-tunes the homeostasis of endogenous H2S levels, thereby influencing alfalfa's salt tolerance and offering valuable strategies for improving crop resilience under saline stress.

Soil salinization is an abiotic stress that hinders crop growth, agricultural productivity, and environmental protection. In this study, alfalfa (Medicago sativa) and tall fescue (Festuca arundinacea) were sown in seven inter-cropping ratios, with monocultures as controls to explore the effects of inter-cropping grasses on yield, water-soluble salt content, pH, and total nitrogen in saline-alkali land, and to establish whether inter-cropping can alleviate salinity and alkalinity. In addition, this study aimed to screen and identify the best alfalfa and tall fescue inter-cropping ratio. The results revealed that (1) Alfalfa and tall fescue had the best productivity and the highest crude protein content at an inter-cropping ratio of M6F4, M7F3, and M8F2, respectively. Besides, inter-cropping improved the land-use efficiency of saline land by altering the plant stem-leaf ratio to adapt to the resource competition. (2) Alfalfa and tall fescue inter-cropping at M3F7, M4F6, and M7F3 decreased the 21% soil salt and 7.8% pH and increased the 34.7% total nitrogen content. (3) Correlation analysis revealed significant correlations among soil salt content, pH, nitrogen, inter-cropping yield, stem-leaf ratio, and plant competition rate. These findings indicate that inter-cropping alfalfa and tall fescue in the ratio M6F4, M7F3, and M8F2 best improves the utilization efficiency of saline land.

Fractional Vegetation Cover (FVC) is a crucial indicator for assessing the vegetation status of terrestrial ecosystems. However, challenges remain in analyzing FVC time series changes and influencing factors. This study tries to address key challenges in FVC assessment by analyzing over 300 wheat germplasms using UAV remote sensing, multispectral imaging, and semantic segmentation. The Transformer-based PoolFormer model outperformed convolutional neural networks, achieving a two-year average mIoU of 93.1% using full-band multispectral data. Visualization confirmed the ability of PoolFormer to track FVC changes over time. While wheat germplasms exhibited consistent growth trends across regions, environmental factors influenced growth rates and durations. High sampling frequencies were essential for capturing dynamic FVC trends. FVC trends in wheat germplasms varied across growth stages, with Argentinian germplasm declining the least. European germplasms exhibited the highest maximum FVC, Oceanic germplasms showed high variability, and Asian and American germplasms had intermediate maximum FVC. Early-stage FVC correlated strongly with plant height, but this correlation weakened over time, while the leaf area index shifted from a positive to a negative correlation. Lodging led to FVC overestimation, with errors increasing over time, and weed interference significantly affected accuracy. These findings provide insights for smart breeding, supporting sustainable wheat ecosystems.

Leymus chinensis is a grass species in the family Triticeae that is found in the Eurasian grassland region and is known for its outstanding ecological advantages and economic value. However, the increasing adoption of photovoltaic agriculture has modified the light environment for the grass, markedly inhibiting its photosynthesis, growth, and yield. This study used physiological and transcriptomic analyses to investigate the complex response mechanisms of two L. chinensis genotypes (Zhongke No. 3 [Lc3] and Zhongke No. 5 [Lc5]) under shading stress. Growth phenotype analysis revealed the superior growth performance of Lc3 under shading stress, evidenced by enhanced plant height and photosynthetic parameters. Additionally, differentially expressed genes (DEGs) were predominantly enriched in starch and sucrose metabolism and glycolysis/gluconeogenesis pathways, which were the most consistently enriched in both L. chinensis genotypes. However, the flavonoid biosynthesis and galactose metabolism pathways were more enriched in Lc3. Weighted gene co-expression network analysis identified the LcGolS2 gene, which encodes galactinol synthase, as a potential hub gene for resistance to shade stress in comparisons across different cultivars and shading treatments. The use of qRT-PCR analysis further validated the genes involved in these pathways, suggesting that they may play critical roles in regulating the growth and development of L. chinensis under shading conditions. These findings provide new insights into the molecular mechanisms underlying the growth and development of L. chinensis under different shading stress conditions.

ABSTRACT The integration of cover crops during forage establishment represents a widely adopted agronomic strategy to suppress weed emergence, enhance stand establishment, and improve grassland community stability. In this study, a two‐year field experiment (2023–2024) was conducted in Jiaozhou, Shandong Province, China, to evaluate the effects of varying sowing proportions of oat (Avena sativa), employed as a protective cover crop, on forage productivity and weed dynamics in alfalfa (Medicago sativa) and tall fescue (Festuca arundinacea) mixed grasslands. The oat sowing ratios were set at 0%, 15%, 30%, 45%, and 60% in 2023, and subsequently refined to 0%, 10%, 20%, 30%, and 40% in 2024, based on first‐year performance. Two spatial configurations (same‐row and inter‐row sowing) were examined to assess resource partitioning effects. Results demonstrated that inter‐row sowing combined with moderate oat inclusion (15%–20%) significantly improved system performance. In 2023, inter‐row sowing with 15% oat yielded 16.57 t/ha, while in 2024, inter‐row sowing with 20% oat achieved the maximum dry matter yield of 18.4 t/ha. Crude protein concentration also improved by 25.6%, reaching 20.13%. Meanwhile, grass and broadleaf weed biomass decreased by 87.2% and 83.4%, respectively, with total weed biomass and coverage reduced by 64.5% and 60.8%. Additionally, the land equivalent ratio (LER) peaked at 1.48, reflecting a 48% increase in land‐use efficiency compared to monoculture systems. Collectively, these findings indicate that incorporating 15%–20% oat as a cover crop, particularly under inter‐row sowing patterns, offers a practical and ecologically sound strategy for optimizing forage yield, improving nutritional quality, and achieving robust weed suppression. This approach contributes to sustainable intensification and reduced dependence on chemical herbicides in temperate forage systems.

Multiprotein bridging factor 1 (MBF1) is a transcription factor family playing crucial roles in plant development and stress responses. In this study, we analyzed MBF1 genes in Medicago truncatula and Medicago sativa under abiotic stresses, revealing evolutionary patterns and functional differences. Four MBF1 genes were identified in M. truncatula and two in M. sativa, with conserved MBF1 and HTH domains, similar exon/intron structures, and stress-related cis-elements in their promoters. Subcellular localization showed that MtMBF1a.1 is predominantly localized in the nucleus, while MtMBF1a.2, MtMBF1b, MtMBF1c, and MsMBF1a localize to both the nucleus and cytoplasm. In contrast, MsMBF1c is exclusively localized in the cytoplasm. An expression analysis revealed distinct stress responses: salt stress-induced MtMBF1b and MtMBF1c expression but repressed MsMBF1a and MsMBF1c. In contrast, PEG stress did not affect M. truncatula MBF1 genes but repressed both M. sativa MBF1 genes. These findings provide insights into MBF1-mediated stress adaptation and inform strategies for the molecular breeding of stress-tolerant alfalfa.

Alfalfa (Medicago sativa) is one of the most widely cultivated forage crops in the world. However, alfalfa yield and quality are adversely affected by salinity stress. Nodulin 26-like intrinsic proteins (NIPs) play essential roles in water and small molecules transport and response to salt stress. Here, we isolated a salt stress responsive MsNIP2 gene and demonstrated its functions by overexpression in alfalfa. The open reading frame of MsNIP2 is 816 bp in length, and it encodes 272 amino acids. It has six transmembrane domains and two NPA motifs. MsNIP2 showed high identity to other known NIP proteins, and its tertiary model was similar to the crystal structure of OsNIP2-1 (7cjs) tetramer. Subcellular localization analysis showed that MsNIP2 protein fused with green fluorescent protein (GFP) was localized to the plasma membrane. Transgenic alfalfa lines overexpressing MsNIP2 showed significantly higher height and branch number compared with the non-transgenic control. The POD and CAT activity of the transgenic alfalfa lines was significantly increased and their MDA content was notably reduced compared with the control group under the treatment of NaCl. The transgenic lines showed higher capability in scavenging oxygen radicals with lighter NBT staining than the control under salt stress. The transgenic lines showed relative lower water loss rate and electrolyte leakage, but relatively higher Na+ content than the control line under salt stress. The relative expression levels of abiotic-stress-related genes (MsHSP23, MsCOR47, MsATPase, and MsRD2) in three transgenic lines were compared with the control, among them, only the expression of MsCOR47 was up-regulated. Consequently, this study offers a novel perspective for exploring the function of MsNIP2 in improving salt tolerance of alfalfa.

Abstract Background Sweet yellow clover (Melilotus officinalis) is a diploid plant (2n = 16) that is native to Europe. It is an excellent legume forage. It can both fix nitrogen and serve as a medicine. A genome assembly of Melilotus officinalis that was collected from Best corporation in Beijing is available based on Nanopore sequencing. The genome of Melilotus officinalis was sequenced, assembled, and annotated. Results The latest PacBio third generation HiFi assembly and sequencing strategies were used to produce a Melilotus officinalis genome assembly size of 1,066 Mbp, contig N50 = 5 Mbp, scaffold N50 = 130 Mbp, and complete benchmarking universal single-copy orthologs (BUSCOs) = 96.4%. This annotation produced 47,873 high-confidence gene models, which will substantially aid in our research on molecular breeding. A collinear analysis showed that Melilotus officinalis and Medicago truncatula shared conserved synteny. The expansion and contraction of gene families showed that Melilotus officinalis expanded by 565 gene families and shrank by 56 gene families. The contacted gene families were associated with response to stimulus, nucleotide binding, and small molecule binding. Thus, it is related to a family of genes associated with peptidase activity, which could lead to better stress tolerance in plants. Conclusions In this study, the latest PacBio technology was used to assemble and sequence the genome of the Melilotus officinalis and annotate its protein-coding genes. These results will expand the genomic resources available for Melilotus officinalis and should assist in subsequent research on sweet yellow clover plants.

Calcium is a crucial macronutrient and functions as a wide-spread signal in eukaryotes,ranging from yeast,plants to animals.As crucial second messengers,calcium ions(Ca2+)play indispens-able roles in plant growth and development,response to external stressors,and signal transduction by modulating downstream cel-lular responses,including gene expression,metabolic activities,and transport functions[1,2].

Epicauta gorhami is a hypermetamorphic insect that mainly forage soybeans during the adult stage. However, the lack of appropriate references hinders our studying of the gene function in E. gorhami. In this study, referring to five computational tools (Ct value, geNorm, NormFinder, BestKeeper and RefFinder), the stability of 10 housekeeping genes (GAPDH, ACT, RPL4, RPL27, α-TUB, RPS18, EF1α, RPS28, RPL13 and SOD) was assessed by qRT-PCR under three different conditions (adult ages, tissues/organs and temperatures). The findings suggested that SOD and RPS18 were the most ideal references for examine gene transcripts among diverse adult ages and at various temperatures; a pair of RPS18 and RPS28 was the most reliable genes to assess gene expressions in diverse adult tissues. Finally, the relative expression levels of EgUAP were computed after normalization RPS18 and RPS28 with across diverse adult tissues. As expected, EgUAP expression was abundant in the foregut, trachea and antenna and scarce in the midgut, hindgut and epidermis. These findings will lay a solid foundation for analyzing the gene expression of E. gorhami.