Hasil untuk "Plant culture"

Darshan Singh, Arsha Nagrani, Kawshik Manikantan et al.

Recent advancements in video models have shown tremendous progress, particularly in long video understanding. However, current benchmarks predominantly feature western-centric data and English as the dominant language, introducing significant biases in evaluation. To address this, we introduce MINERVA-Cultural, a challenging benchmark for multicultural and multilingual video reasoning. MINERVA-Cultural comprises high-quality, entirely human-generated annotations from diverse, region-specific cultural videos across 18 global locales. Unlike prior work that relies on automatic translations, MINERVA-Cultural provides complex questions, answers, and multi-step reasoning steps, all crafted in native languages. Making progress on MINERVA-Cultural requires a deeply situated understanding of visual cultural context. Furthermore, we leverage MINERVA-Cultural's reasoning traces to construct evidence-based graphs and propose a novel iterative strategy using these graphs to identify fine-grained errors in reasoning. Our evaluations reveal that SoTA Video-LLMs struggle significantly, performing substantially below human-level accuracy, with errors primarily stemming from the visual perception of cultural elements. MINERVA-Cultural will be publicly available under https://github.com/google-deepmind/neptune?tab=readme-ov-file\#minerva-cultural

Ghasem Eghlima, Hanifeh Seyed Hajizadeh, Meisam Mohammadi et al.

Thymus vulgaris L. is widely recognized for its medicinal and aromatic qualities, largely attributed to the diverse healing effects found in its essential oils and extracts. Factors such as genetic makeup, environmental variables, and agronomic practices play crucial roles in shaping the plant’s development, biomass production, and the quantity and chemical profile of its oils and extracts. Ozone water irrigation is emerging as a sustainable and novel approach in horticulture, offering potential to enhance plant development and stimulate the synthesis of key secondary metabolites and bioactive constituents. This study investigated the physiological, biochemical, and phytochemical responses of T. vulgaris to irrigation with ozone water at varying concentrations (0, 2.0, 4.0, 6.0, and 8.0 mg/L). Enhanced irrigation with ozone water significantly influenced plant growth metrics, including plant height, diameter, and biomass accumulation, with the most pronounced improvements observed at 6.0 and 8.0 mg/L concentrations. Although leaf dimensions remained unaffected, higher ozone levels promoted increased chlorophyll content and substantially elevated essential oil yield. Antioxidant-related traits, including total phenolic and flavonoid contents and FRAP activity, were notably amplified, whereas proline accumulation declined, indicating a reduction in oxidative stress. Despite elevated levels of oxidative stress markers (MDA, H₂O₂) under higher ozone water treatments, antioxidant enzymes such as CAT, POD, and SOD were significantly activated, particularly at 6.0 mg/L. Furthermore, GC–MS profiling revealed that while the proportion of beneficial compounds like acetovanillone and β-caryophyllene rose with ozone water application, key monoterpenoid phenols (e.g., thymol, carvacrol) declined at the highest ozone levels. The diverse responses of essential oil components, including monoterpenes and alcohols, suggest a dose-dependent modulation of secondary metabolism. These findings propose ozone-enriched irrigation as a potential agronomic strategy for enhancing growth and certain bioactive constituents of thyme, while cautioning its impact on specific oil components.

Fengguang He, Fengguang He, Sili Zhou et al.

The content of impurities in mechanically harvested sugarcane is a critical factor for evaluating harvest quality and determining market price. To enable intelligent detection of impurities in mechanically harvested sugarcane, this study proposes an impurity detection method based on an improved YOLOv11n-seg model. The method integrates four enhancement modules into the original YOLOv11n-seg architecture. Firstly, a lightweight C2_Ghost module is introduced into the high-channel feature extraction stages of both the backbone and neck, thereby reducing computational complexity and feature redundancy. Subsequently, a C2_FSAS module is designed to perform frequency-domain relationship modelling, enhancing long-range semantic dependency representation. An Efficient Channel Attention (ECA) mechanism is then applied to deep high-level semantic features to adaptively reweight salient feature channels. Finally, the traditional fixed interpolation-based upsampling operation is replaced with a dynamic DySample upsampling strategy to recover fine-grained edge features. Experimental results indicate that Improved YOLOv11n-seg achieves segmentation performance of 97.0%, 98.1%, 99.2%, and 82.9% in terms of P, R, mAP0.5, and mAP0.5:0.95, respectively. Compared with the original YOLOv11n-seg, the proposed model achieves a 1.8% improvement in mAP0.5:0.95, a 10.2% reduction in parameter count, and maintains a real-time inference speed of 34.8 FPS on the Jetson Xavier NX under TensorRT acceleration. Ablation studies validate the effectiveness of the four-module synergistic design, with C2_FSAS and DySample contributing most significantly to the improvement in mAP. Moreover, the model exhibits enhanced edge delineation accuracy and inter-class discrimination capability. In summary, the Improved YOLOv11n-seg achieves a favourable balance between segmentation accuracy and real-time performance, enabling precise segmentation of sugarcane segments and diverse impurity types. The proposed method provides reliable technical support for intelligent impurity rate detection in mechanically harvested sugarcane and practical deployment on edge computing platforms.

Dhanpati Keerthana, Vijay Kumar Yadav, Jitendra Kumar Tiwari et al.

Finger millet (Eleusine coracana L.) is a nutritionally rich but underutilized crop found in semi-arid regions and drylands worldwide. To identify their genetically diverse and well-adapted genotypes to local conditions, a total of 162 germplasm lines, along with eight check varieties, were assessed during the rainy seasons of 2023 and 2024. The morphological characterization adhered to the Distinctiveness, Uniformity, and Stability (DUS) guidelines established by the PPV & FR Authority. The data collection concentrated on 14 qualitative traits and 13 quantitative traits. Significant variation was observed across all the traits. Specific traits such as earhead length, finger length, number of productive tillers, stover yield, and grain yield exhibited high heritability and significant genetic advance. The diversity index ranged from 0.162 for seed shape to 1.436 for ear shape. Grain yield demonstrated the most significant positive correlations with flag leaf width (0.503) and finger number (0.320). Cluster analysis classified the genotypes into six distinct clusters, with cluster 6 being highly diverse and possessing early maturing genotypes. PCA identified five principal components with eigenvalues greater than 1, collectively accounting for 70.1% of the total variation. The study identified genetically diverse and promising genotypes, establishing a solid foundation for targeted selection and breeding. The enhanced integration of molecular tools like genome-wide association studies may facilitate the precise selection of genotypes. The findings offer critical insights for selecting high-performing genotypes appropriate for cultivation and for improving breeding programs in this region.

Srishti Yadav, Zhi Zhang, Daniel Hershcovich et al.

Investigating value alignment in Large Language Models (LLMs) based on cultural context has become a critical area of research. However, similar biases have not been extensively explored in large vision-language models (VLMs). As the scale of multimodal models continues to grow, it becomes increasingly important to assess whether images can serve as reliable proxies for culture and how these values are embedded through the integration of both visual and textual data. In this paper, we conduct a thorough evaluation of multimodal model at different scales, focusing on their alignment with cultural values. Our findings reveal that, much like LLMs, VLMs exhibit sensitivity to cultural values, but their performance in aligning with these values is highly context-dependent. While VLMs show potential in improving value understanding through the use of images, this alignment varies significantly across contexts highlighting the complexities and underexplored challenges in the alignment of multimodal models.

Sharifa Sultana, Hafsah Mahzabin Chowdhury, Zinnat Sultana et al.

Reproductive well-being education in the Global South is often challenged as many communities perceive many of its contents as misinformation, misconceptions, and language-inappropriate. Our ten-month-long ethnographic study (n=41) investigated the impact of sociocultural landscape, cultural beliefs, and healthcare infrastructure on Bangladeshi people's access to quality reproductive healthcare and set four design goals: combating misinformation, including culturally appropriate language, professionals' accountable moderation, and promoting users' democratic participation. Building on the model of `\textit{Distributive Justice,}' we designed and evaluated \textit{`Socheton,'} a culturally appropriate AI-mediated tool for reproductive well-being that includes healthcare professionals, AI-language teachers, and community members to moderate and run the activity-based platform. Our user study (n=28) revealed that only combating misinformation and language inappropriateness may still leave the community with a conservative mob culture and patronize reproductive care-seeking. This guides well-being HCI design toward being culturally appropriate in the context of reproductive justice with sensitive marginalized communities.

Sara Ruiz-Moreno, Antonio J. Gallego, Manuel Macías et al.

This paper presents a novel method to optimize thermal balance in parabolic trough collector (PTC) plants. It uses a market-based system to distribute flow among loops combined with an artificial neural network (ANN) to reduce computation and data requirements. This auction-based approach balances loop temperatures, accommodating varying thermal losses and collector efficiencies. Validation across different thermal losses, optical efficiencies, and irradiance conditions-sunny, partially cloudy, and cloudy-show improved thermal power output and intercept factors compared to a no-allocation system. It demonstrates scalability and practicality for large solar thermal plants, enhancing overall performance. The method was first validated through simulations on a realistic solar plant model, then adapted and successfully tested in a 50 MW solar trough plant, demonstrating its advantages. Furthermore, the algorithms have been implemented, commissioned, and are currently operating in 13 commercial solar trough plants.

Manoel M. E. Oliveira, Viviane Felix Moraes Lima, Gisela Lara da Costa et al.

The emerging fungal pathogen Candida palmioleophila (C. palmioleophila) has been increasingly detected in environmental and animal samples, although studies in this regard are still scarce, especially in fisheries contexts. This study reports the first-time detection of C. palmioleophila in a commercially relevant fish species belonging to the Sciaenidae family (Cynoscion sp.), indicating its potential emergence as a pathogen in Brazil. We applied CHROMagar Candida Plus medium identification associated to Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF MS) for the identification of C. palmioleophila isolates. Although only one fish specimen was shown to be contaminated by C. palmioleophila, this study provides the first evidence of this yeast circulating in commercially relevant fish species in Brazil, highlighting the potential risks associated with this emerging pathogen.

Yong Cao, Min Chen, Daniel Hershcovich

The cultural landscape of interactions with dialogue agents is a compelling yet relatively unexplored territory. It's clear that various sociocultural aspects -- from communication styles and beliefs to shared metaphors and knowledge -- profoundly impact these interactions. To delve deeper into this dynamic, we introduce cuDialog, a first-of-its-kind benchmark for dialogue generation with a cultural lens. We also develop baseline models capable of extracting cultural attributes from dialogue exchanges, with the goal of enhancing the predictive accuracy and quality of dialogue agents. To effectively co-learn cultural understanding and multi-turn dialogue predictions, we propose to incorporate cultural dimensions with dialogue encoding features. Our experimental findings highlight that incorporating cultural value surveys boosts alignment with references and cultural markers, demonstrating its considerable influence on personalization and dialogue quality. To facilitate further exploration in this exciting domain, we publish our benchmark publicly accessible at https://github.com/yongcaoplus/cuDialog.

Shuhei Kitamura

While connections between climate and the human mind and culture are widely acknowledged, they are not thoroughly quantified. Analyzing 100,000 paintings and data on 2,000 artists from the 13th to 21st centuries, the study reveals that the lightness of the paintings exhibited an interesting U-shaped pattern mirroring global temperature trends. There is a significant association between the two, even after controlling for various factors. Event study analysis using the artist-level data further reveals that high-temperature shocks resulted in brighter paintings in later periods for artists who experienced them compared to the control group. The effect is particularly pronounced in art genres that rely on artists' imaginations, indicating a notable influence on artists' minds. These findings underscore the enduring impact of climate on the human mind and culture throughout history and highlight art as a valuable tool for understanding people's minds and cultures.

Yuanjun Xu, Zhu An, Ning Huang et al.

This paper introduces the necessity and significance of the investigation of cultural heritage objects. The multi-technique method is useful for the study of cultural heritage objects, but a comprehensive analytical instrument is a better choice since it can guarantee that different types of information are always obtained from the same analytical point on the surface of cultural heritage objects, which may be crucial for some situations. Thus, the X-ray fluorescence (XRF)/X-ray diffraction (XRD) and X-ray fluorescence (XRF)/Raman spectroscopy (RS) comprehensive analytical instruments are more and more widely used to study cultural heritage objects. The two types of comprehensive analytical instruments are discussed in detail and the XRF/XRD instruments are further classified into different types on the basis of structure, type and number of detectors. A new comprehensive analytical instrument prototype that can perform XRF, XRD and RS measurements simultaneously has been successfully developed by our team and the preliminary application has shown the analysis performance and application potential. This overview contributes to better understand the research progress and development tendency of comprehensive analytical instruments for the study of cultural heritage objects. The new comprehensive instruments will make researchers obtain more valuable information on cultural heritage objects and further promote the study on cultural heritage objects.

Elias Marks, Jonas Bömer, Federico Magistri et al.

Agricultural production is facing severe challenges in the next decades induced by climate change and the need for sustainability, reducing its impact on the environment. Advancements in field management through non-chemical weeding by robots in combination with monitoring of crops by autonomous unmanned aerial vehicles (UAVs) and breeding of novel and more resilient crop varieties are helpful to address these challenges. The analysis of plant traits, called phenotyping, is an essential activity in plant breeding, it however involves a great amount of manual labor. With this paper, we address the problem of automatic fine-grained organ-level geometric analysis needed for precision phenotyping. As the availability of real-world data in this domain is relatively scarce, we propose a novel dataset that was acquired using UAVs capturing high-resolution images of a real breeding trial containing 48 plant varieties and therefore covering great morphological and appearance diversity. This enables the development of approaches for autonomous phenotyping that generalize well to different varieties. Based on overlapping high-resolution images from multiple viewing angles, we compute photogrammetric dense point clouds and provide detailed and accurate point-wise labels for plants, leaves, and salient points as the tip and the base. Additionally, we include measurements of phenotypic traits performed by experts from the German Federal Plant Variety Office on the real plants, allowing the evaluation of new approaches not only on segmentation and keypoint detection but also directly on the downstream tasks. The provided labeled point clouds enable fine-grained plant analysis and support further progress in the development of automatic phenotyping approaches, but also enable further research in surface reconstruction, point cloud completion, and semantic interpretation of point clouds.

Li Zhou, Antonia Karamolegkou, Wenyu Chen et al.

The increasing ubiquity of language technology necessitates a shift towards considering cultural diversity in the machine learning realm, particularly for subjective tasks that rely heavily on cultural nuances, such as Offensive Language Detection (OLD). Current understanding underscores that these tasks are substantially influenced by cultural values, however, a notable gap exists in determining if cultural features can accurately predict the success of cross-cultural transfer learning for such subjective tasks. Addressing this, our study delves into the intersection of cultural features and transfer learning effectiveness. The findings reveal that cultural value surveys indeed possess a predictive power for cross-cultural transfer learning success in OLD tasks and that it can be further improved using offensive word distance. Based on these results, we advocate for the integration of cultural information into datasets. Additionally, we recommend leveraging data sources rich in cultural information, such as surveys, to enhance cultural adaptability. Our research signifies a step forward in the quest for more inclusive, culturally sensitive language technologies.

Wentao Sheng, Jianlan Deng, Chao Wang et al.

Garden asparagus (Asparagus officinalis L.) is a horticultural crop with high nutritional and medical value, considered an ideal plant for sex determination research among many dioecious plants, whose genomic information can support genetic analysis and breeding programs. In this research, the entire mitochondrial genome of A. officinalis was sequenced, annotated and assembled using a mixed Illumina and PacBio data. The garden asparagus circular mitochondrial genome measures 492,062 bp with a GC value of 45.9%. Thirty-six protein-coding genes, 17 tRNA and 6 rRNA genes were annotated, among which 8 protein-coding genes contained 16 introns. In addition, 254 SSRs with 10 complete tandem repeats and 293 non-tandem repeats were identified. It was found that the codons of edited sites located in the amino acids showed a leucine-formation trend, and RNA editing sites mainly caused the mutual transformation of amino acids with the same properties. Furthermore, 72 sequence fragments accounting for 20,240 bp, presentating 4.11% of the whole mitochondrial genome, were observed to migrate from chloroplast to mitochondrial genome of A. officinalis. The phylogenetic analysis showed that the closest genetic relationship between A. officinalis with onion (Allium cepa) inside the Liliaceae family. Our results demonstrated that high percentage of protein-coding genes had evolutionary conservative properties, with Ka/Ks values less than 1. Therefore, this study provides a high-quality garden asparagus mitochondrial genome, useful to promote better understanding of gene exchange between organelle genomes.

Yuying Shen, Huan Yang, Zheng Lin et al.

Bacillus bacteria can produce abundant secondary metabolites that are useful for biocontrol, especially in maintaining plant root microecology, and for plant protection. In this study, we determine the indicators of six Bacillus strains for colonization, promotion of plant growth, antimicrobial activity, and other aspects, with the aim of obtaining a compound bacteriological agent to construct a beneficial Bacillus microbial community in plant roots. We found that there was no significant difference in the growth curves of the six Bacillus strains over 12 h. However, strain HN-2 was found to have the strongest swimming ability and the highest bacteriostatic effect of n-butanol extract on the blight-causing bacteria Xanthomonas oryzae pv. oryzicola. The hemolytic circle produced by the n-butanol extract of strain FZB42 was the largest (8.67 ± 0.13 mm) and had the greatest bacteriostatic effect on the fungal pathogen Colletotrichum gloeosporioides, with a bacteriostatic circle diameter of 21.74 ± 0.40 mm. Strains HN-2 and FZB42 can rapidly form biofilms. Time-of-flight mass spectrometry and hemolytic plate tests showed that strains HN-2 and FZB42 may have significantly different activities because of their ability to produce large quantities of lipopeptides (i.e., surfactin, iturin, and fengycin). Different growth-promoting experiments revealed that the strains FZB42, HN-2, HAB-2, and HAB-5 had better growth-promoting potential than the control, and therefore these four strains were compounded in an equal ratio and used to treat pepper seedlings through root irrigation. We found an increase in the stem thickness (13%), leaf dry weight (14%), leaf number (26%), and chlorophyll content (41%) of pepper seedlings treated with the composite-formulated bacterial solution compared to the optimal single-bacterial solution treatment. Furthermore, several of these indicators increased by an average of 30% in the composite solution-treated pepper seedlings compared with the control water treatment group. In conclusion, the composite solution obtained by compounding strains FZB42 (OD600 = 1.2), HN-2 (OD600 = 0.9), HAB-2 (OD600 = 0.9), and HAB-5 (OD600 = 1.2) in equal parts highlights the advantages of a single bacterial solution, which includes achieving good growth promotion and antagonistic effects against pathogenic bacteria. The promotion of this compound-formulated Bacillus can reduce the application of chemical pesticides and fertilizers; promote plant growth and development; avoid the imbalances of soil microbial communities and thus reduce the risk of plant disease; and provide an experimental basis for the production and application of various types of biological control preparations in the future.

Qian Long, Kaushik Das, Poul Sørensen

Frequency control (FC) enables utility-scale grid-connected hybrid power plants (HPPs) to operate in compliance with grid code requirements while to capture value streams from provision of frequency control services (FCSs). In this paper, a novel hierarchical FC approach is proposed to allow HPPs to provide three types of FCSs, namely fast frequency response (FFR), frequency containment response (FCR) and frequency restoration response (FRR). To accommodate state-of-the-art fast FC, controllers for fast FCSs, such as FFR and FCR, are implemented at asset controllers, while controllers for slow FCSs like FRR are implemented at plant controllers or the HPP controller (HPPC). Control counteraction issue, which arises across control hierarchy, is then discussed. To solve this issue, an innovative frequency response observer (FROB) is proposed. Inspired by the concept of disturbance observer (DOB), FROB at plant controllers and the HPPC accurately estimates frequency response initiated at asset controllers, and the obtained estimation is used for control compensation at plant controllers and the HPPC to avoid control counteraction. This scheme achieves robust performance even when there are system uncertainties existing in HPPs, such as parameter uncertainty, unknown control malfunction, and time-varying communication delays. The proposed approach is implemented in a power system dynamic model in MATLAB/Simulink to highlight its effectiveness and robustness.

Nadhifa Zahira Ramadhani Mart, Terry Mart

A simple homemade greenhouse was constructed as a part of the high school project during the learning-from-home period. The greenhouse was used to show CO$_2$ absorption by Sansevieria trifasciata during the night, obeying Fick's law, while the CO$_2$ emission by the medium used to grow the plant does not. Although other plants can be used for this purpose, the use of Sansevieria is interesting and offers certain advantages because it absorbs CO$_2$ during the night. The project could also provide a simple tool for high school students to investigate the absorption and emission of CO$_2$ from home or in laboratory. Extension of this project to investigate the effect of plant respiration on the environmental parameters, such as decreasing temperature and increasing humidity, is also possible.

Yue Yang, Yue Yang, Yue Yang et al.

Current increases in not only the intensity and frequency but also the duration of drought events could affect the growth, physiology, and mortality of trees. We experimentally studied the effects of drought duration in combination with fertilization on leaf water potential, gas exchange, growth, tissue levels of non-structural carbohydrates (NSCs), tissue NSC consumption over-winter, and recovery after drought release in oak (Quercus petraea) and beech (Fagus sylvatica) saplings. Long drought duration (>1 month) decreased leaf water potential, photosynthesis, and NSC concentrations in both oak and beech saplings. Nitrogen fertilization did not mitigate the negative drought effects on both species. The photosynthesis and relative height increment recovered in the following rewetting year. Height growth in the rewetting year was significantly positively correlated with both pre- and post-winter root NSC levels. Root carbon reserve is critical for tree growth and survival under long-lasting drought. Our results indicate that beech is more sensitive to drought and fertilization than oak. The present study, in a physiological perspective, experimentally confirmed the view that the European beech, compared to oak, may be more strongly affected by future environmental changes.

Antonella Muto, Leonardo Bruno, Maria Letizia Madeo et al.

IntroductionPeach (Prunus persica (L.) Batsch,) and nectarine fruits (Prunus persica (L.) Batsch, var nectarine), are characterized by a rapid deterioration at room temperature. Therefore, cold storage is widely used to delay fruit post-harvest ripening and extend fruit commercial life. Physiological disorders, collectively known as chilling injury, can develop typically after 3 weeks of low-temperature storage and affect fruit quality.MethodsA comparative transcriptomic analysis was performed to identify regulatory pathways that develop before chilling injury symptoms are detectable using next generation sequencing on the fruits of two contrasting cultivars, one peach (Sagittaria) and one nectarine, (Big Top), over 14 days of postharvest cold storage.ResultsThere was a progressive increase in the number of differentially expressed genes between time points (DEGs) in both cultivars. More (1264) time point DEGs were identified in ‘Big Top’ compared to ‘Sagittaria’ (746 DEGs). Both cultivars showed a downregulation of pathways related to photosynthesis, and an upregulation of pathways related to amino sugars, nucleotide sugar metabolism and plant hormone signal transduction with ethylene pathways being most affected. Expression patterns of ethylene related genes (including biosynthesis, signaling and ERF transcription factors) correlated with genes involved in cell wall modification, membrane composition, pathogen and stress response, which are all involved later during storage in development of chilling injury.DiscussionOverall, the results show that common pathways are activated in the fruit of ‘Big Top’ nectarine and ‘Sagittaria’ peach in response to cold storage but include also differences that are cultivar-specific responses.

Giuseppina Adiletta, Milena Petriccione, Marisa Di Matteo

Fig is a very perishable fruit with short postharvest life. Low-cost postharvest techniques should be employed to reduce fresh fig postharvest losses. The purpose of this study was to design a passive modified atmosphere packaging (PMAP) to extend the shelf-life of fresh ‘Dottato’ figs stored at 4 °C for 21 days. Physico-chemical traits and enzymatic and non-enzymatic antioxidant systems were evaluated. Storage in PMAP reduced the losses of fruit weight as well as maintained physico-chemical traits and nutraceutical traits such as polyphenol and flavonoid contents and the antioxidant activity in fresh figs. PMAP reduced oxidative stress, inducing the activities of antioxidant enzymes such as ascorbate peroxidase and catalase, involved in reactive oxygen species scavenging. A reduction in browning process due to polyphenol oxidase and guaiacol peroxidase activities was observed in PMAP samples. Multivariate analysis indicated that storage conditions and storage time affected the responses of qualitative and enzymatic traits. Fig fruit storage in PMAP was suitable to delay its postharvest decay and to preserve nutraceutical traits and antioxidative enzymes during 21 days of cold storage.