Hasil untuk "Plant culture"

F. Bourgaud, A. Gravot, S. Milesi et al.

Vynska Amalia Permadi, Xingwei Tan, Nafise Sadat Moosavi et al.

Understanding culture requires reasoning across context, tradition, and implicit social knowledge, far beyond recalling isolated facts. Yet most culturally focused question answering (QA) benchmarks rely on single-hop questions, which may allow models to exploit shallow cues rather than demonstrate genuine cultural reasoning. In this work, we introduce ID-MoCQA, the first large-scale multi-hop QA dataset for assessing the cultural understanding of large language models (LLMs), grounded in Indonesian traditions and available in both English and Indonesian. We present a new framework that systematically transforms single-hop cultural questions into multi-hop reasoning chains spanning six clue types (e.g., commonsense, temporal, geographical). Our multi-stage validation pipeline, combining expert review and LLM-as-a-judge filtering, ensures high-quality question-answer pairs. Our evaluation across state-of-the-art models reveals substantial gaps in cultural reasoning, particularly in tasks requiring nuanced inference. ID-MoCQA provides a challenging and essential benchmark for advancing the cultural competency of LLMs.

Yixin Wan, Xingrun Chen, Kai-Wei Chang

Large language models (LLMs) have unlocked a wide range of downstream generative applications. However, we found that they also risk perpetuating subtle fairness issues tied to culture, positioning their generations from the perspectives of the mainstream US culture while demonstrating salient externality towards non-mainstream ones. In this work, we identify and systematically investigate this novel culture positioning bias, in which an LLM's default generative stance aligns with a mainstream view and treats other cultures as outsiders. We propose the CultureLens benchmark with 4000 generation prompts and 3 evaluation metrics for quantifying this bias through the lens of a culturally situated interview script generation task, in which an LLM is positioned as an onsite reporter interviewing local people across 10 diverse cultures. Empirical evaluation on 5 state-of-the-art LLMs reveals a stark pattern: while models adopt insider tones in over 88 percent of US-contexted scripts on average, they disproportionately adopt mainly outsider stances for less dominant cultures. To resolve these biases, we propose 2 inference-time mitigation methods: a baseline prompt-based Fairness Intervention Pillars (FIP) method, and a structured Mitigation via Fairness Agents (MFA) framework consisting of 2 pipelines: (1) MFA-SA (Single-Agent) introduces a self-reflection and rewriting loop based on fairness guidelines. (2) MFA-MA (Multi-Agent) structures the process into a hierarchy of specialized agents: a Planner Agent(initial script generation), a Critique Agent (evaluates initial script against fairness pillars), and a Refinement Agent (incorporates feedback to produce a polished, unbiased script). Empirical results showcase the effectiveness of agent-based methods as a promising direction for mitigating biases in generative LLMs.

Herve Goeau, Pierre Bonnet, Alexis Joly

The 2017-th edition of the LifeCLEF plant identification challenge is an important milestone towards automated plant identification systems working at the scale of continental floras with 10.000 plant species living mainly in Europe and North America illustrated by a total of 1.1M images. Nowadays, such ambitious systems are enabled thanks to the conjunction of the dazzling recent progress in image classification with deep learning and several outstanding international initiatives, such as the Encyclopedia of Life (EOL), aggregating the visual knowledge on plant species coming from the main national botany institutes. However, despite all these efforts the majority of the plant species still remain without pictures or are poorly illustrated. Outside the institutional channels, a much larger number of plant pictures are available and spread on the web through botanist blogs, plant lovers web-pages, image hosting websites and on-line plant retailers. The LifeCLEF 2017 plant challenge presented in this paper aimed at evaluating to what extent a large noisy training dataset collected through the web and containing a lot of labelling errors can compete with a smaller but trusted training dataset checked by experts. To fairly compare both training strategies, the test dataset was created from a third data source, i.e. the Pl@ntNet mobile application that collects millions of plant image queries all over the world. This paper presents more precisely the resources and assessments of the challenge, summarizes the approaches and systems employed by the participating research groups, and provides an analysis of the main outcomes.

Rengasamy Anbazhakan, Xin-Meng Zhu, Neng-Qi Li et al.

<i>Malania oleifera</i> Chun & S.K. Lee, an endemic monotypic species that belongs to the family Olacaceae, is under continuous pressure of decline owing to several ecological and physiological factors. The present study aimed to establish an efficient in vitro protocol for callus-mediated indirect somatic embryogenesis in <i>M. oleifera</i> by alleviating tissue browning. Internodes and leaves obtained from seedlings were used as explants. Antioxidant pre-treatment (ascorbic acid, AA) followed by different carbon sources (sucrose, maltose, glucose, and fructose) and plant growth regulators in various concentrations and combinations were employed in Woody Plant Medium (WPM) to alleviate explant browning and induce callus formation from the explants. AA pre-treatment and subsequent culture on maltose at a concentration of 116.8 mM were optimal for controlling phenolic exudation on >90% of both explants. The highest responses of 53.77% and 57.43% for embryogenic calli were induced from internode and leaf explants, respectively. The highest responses, 85.22% and 93.80%, were observed for somatic embryos that matured into the globular, heart-shaped and torpedo stages at different percentages on NAA 2.5 mg/L in combination with BA 1.0 mg/L for both explants. The matured somatic embryos were finally germinated at a maximum concentration of GA₃, 2.0 mg/L. All plantlets were successfully hardened and acclimatized under culture room conditions and then transferred to the greenhouse. The current study suggests an efficient protocol for indirect somatic embryogenesis by alleviating phenolic exudation from the explants of <i>M. oleifera</i>. This first successful report of in vitro culture establishment in <i>M. oleifera</i> may offer an effective alternative measure to conserve this species and provide a system for analyzing bioactive chemicals and for use in the oil industry.

Fabrice Mayran de Chamisso, Loïc Cotten, Valentine Dhers et al.

With the advent of multispectral imagery and AI, there have been numerous works on automatic plant segmentation for purposes such as counting, picking, health monitoring, localized pesticide delivery, etc. In this paper, we tackle the related problem of automatic and selective plant-clearing in a sustainable forestry context, where an autonomous machine has to detect and avoid specific plants while clearing any weeds which may compete with the species being cultivated. Such an autonomous system requires a high level of robustness to weather conditions, plant variability, terrain and weeds while remaining cheap and easy to maintain. We notably discuss the lack of robustness of spectral imagery, investigate the impact of the reference database's size and discuss issues specific to AI systems operating in uncontrolled environments.

Siddhesh Pawar, Junyeong Park, Jiho Jin et al.

Large-scale deployment of large language models (LLMs) in various applications, such as chatbots and virtual assistants, requires LLMs to be culturally sensitive to the user to ensure inclusivity. Culture has been widely studied in psychology and anthropology, and there has been a recent surge in research on making LLMs more culturally inclusive in LLMs that goes beyond multilinguality and builds on findings from psychology and anthropology. In this paper, we survey efforts towards incorporating cultural awareness into text-based and multimodal LLMs. We start by defining cultural awareness in LLMs, taking the definitions of culture from anthropology and psychology as a point of departure. We then examine methodologies adopted for creating cross-cultural datasets, strategies for cultural inclusion in downstream tasks, and methodologies that have been used for benchmarking cultural awareness in LLMs. Further, we discuss the ethical implications of cultural alignment, the role of Human-Computer Interaction in driving cultural inclusion in LLMs, and the role of cultural alignment in driving social science research. We finally provide pointers to future research based on our findings about gaps in the literature.

Xiaoyu Zhang, Saurabh Gupta

Autonomous agriculture applications (e.g., inspection, phenotyping, plucking fruits) require manipulating the plant foliage to look behind the leaves and the branches. Partial visibility, extreme clutter, thin structures, and unknown geometry and dynamics for plants make such manipulation challenging. We tackle these challenges through data-driven methods. We use self-supervision to train SRPNet, a neural network that predicts what space is revealed on execution of a candidate action on a given plant. We use SRPNet with the cross-entropy method to predict actions that are effective at revealing space beneath plant foliage. Furthermore, as SRPNet does not just predict how much space is revealed but also where it is revealed, we can execute a sequence of actions that incrementally reveal more and more space beneath the plant foliage. We experiment with a synthetic (vines) and a real plant (Dracaena) on a physical test-bed across 5 settings including 2 settings that test generalization to novel plant configurations. Our experiments reveal the effectiveness of our overall method, PPG, over a competitive hand-crafted exploration method, and the effectiveness of SRPNet over a hand-crafted dynamics model and relevant ablations.

Trent Blare, Victor Contreras, Fredy H. Ballen et al.

Esta publicación examina los costos estimados y los rendimientos de una plantación de maracuyá morada establecida en el sur de Florida. La información presentada en este documento se recopiló a través de entrevistas de campo con productores y especialistas en la industria. Se basa en una variedad de prácticas de producción en producciones a pequeña escala (1-2 acres). La información en este documento está destinada solo como una guía para estimar los requisitos financieros de una plantación ya establecida de maracuyá. Estimamos un rendimiento neto de $ 2,772/acre/año, o $ 0. 98/libra, el cual es un retorno económico muy atractivo comparado al de otras frutas tropicales de la zona.

Serge Kernbach

This paper briefly describes the device - the phytosensor - for measuring physiological and electrophysiological parameters of plants. This system is developed as a bio-physiological sensor in precise agriculture, as a tool in plant research and environmental biology, and for plant enthusiasts in smart home or entertainment applications. The phytosentor measures main physiological parameters such as the leaf transpiration rate, sap flow, tissue conductivity and frequency response, biopotentials (action potentials and variation potentials), and can conduct electrochemical impedance spectroscopy with organic tissues. Soil moisture and temperature, air quality (CO2, NO2, O3 and other sensors on I2C bus), and general environmental parameters (light, temperature, humidity, air pressure, electromagnetic and magnetic fields) are also recorded in real time. In addition to phytosensing, the device can also perform phytoactuation, i.e. execute electrical or light stimulation of plants, control irrigation and lighting modes, conduct fully autonomous experiments with complex feedback-based and adaptive scenarios in robotic or biohybrid systems. This article represents the revised and extended version of original paper and includes some descriptions and images from the FloraRobotica and BioHybrids projects.

Andres Ferraro, Gustavo Ferreira, Fernando Diaz et al.

Recommender systems have become the dominant means of curating cultural content, significantly influencing the nature of individual cultural experience. While the majority of research on recommender systems optimizes for personalized user experience, this paradigm does not capture the ways that recommender systems impact cultural experience in the aggregate, across populations of users. Although existing novelty, diversity, and fairness studies probe how systems relate to the broader social role of cultural content, they do not adequately center culture as a core concept and challenge. In this work, we introduce commonality as a new measure that reflects the degree to which recommendations familiarize a given user population with specified categories of cultural content. Our proposed commonality metric responds to a set of arguments developed through an interdisciplinary dialogue between researchers in computer science and the social sciences and humanities. With reference to principles underpinning non-profit, public service media systems in democratic societies, we identify universality of address and content diversity in the service of strengthening cultural citizenship as particularly relevant goals for recommender systems delivering cultural content. Taking diversity in movie recommendation as a case study in enhancing pluralistic cultural experience, we empirically compare systems' performance using commonality and existing utility, diversity, and fairness metrics. Our results demonstrate that commonality captures a property of system behavior complementary to existing metrics and suggest the need for alternative, non-personalized interventions in recommender systems oriented to strengthening cultural citizenship across populations of users. In this way, commonality contributes to a growing body of scholarship developing 'public good' rationales for digital media and ML systems.

Byunghyun Ban

An easier and intuitive interface architecture is necessary for digital twin of plant factory. I suggest an immersive and interactive mixed reality interface for digital twin models of smart farming, for remote work rather than simulation of components. The environment is constructed with UI display and a streaming background scene, which is a real time scene taken from camera device located in the plant factory, processed with deformable neural radiance fields. User can monitor and control the remote plant factory facilities with HMD or 2D display based mixed reality environment. This paper also introduces detailed concept and describes the system architecture to implement suggested mixed reality interface.

Sareh Farahani, Abbas Akhavanesepahi, Sayed abbas Shojaosadati et al.

Introduction: Due to the increasing trend of industrial development and also the industrial production, the presence of heavy metals along with industrial wastewater is undeniable. Despite the various ways to remove heavy metals, choosing biological methods can be the best way to control them. Using bacteria in this field can be very useful and inexpensive with less harm. Materials and Methods: In the present study, various aquatic environments including rivers, ponds, industrial effluents, and activated sludge were sampled. Bacteria were identified based on the growth in iron-specific culture medium in terms of shape and 16S rRNA gene. These bacteria were cultured in specific culture media for iron-oxidizing bacteria, Luria-Bertoni (LB) and PHG II, containing 2 ppm of mercury chloride and cadmium chloride. The samples were then examined for the reduction or non-change of mercury and cadmium concentrations by atomic absorption spectrometry. Results: The results of the present study showed that the isolated bacteria were rod-shaped and chemoorganotrophic belonging to the genus Bacillus. The average percentages of mercury and cadmium removal by the isolated bacteria were about 95% and 40%, respectively.  The highest percentage of the removal of both heavy metals was observed in the effluent sample of iron factory wastewater. Discussion and Conclusion: Iron oxidizing bacteria were identified as reducing agents of heavy metals in the laboratory environment. These bacteria grew in both LB medium and iron-specific culture medium. The highest percentage of the removal of both heavy metals was observed in the effluent sample of the iron processing plant. Based on the results, it can be said that the bacteria of each environment have adapted to the compounds of that place and are the best option to remove compounds such as heavy metals.

Daria Krefft, Maciej Prusinowski, Paulina Maciszka et al.

Abstract Background The widespread usage of protein expression systems in Escherichia coli (E. coli) is a workhorse of molecular biology research that has practical applications in biotechnology industry, including the production of pharmaceutical drugs. Various factors can strongly affect the successful construction and stable maintenance of clones and the resulting biosynthesis levels. These include an appropriate selection of recombinant hosts, expression systems, regulation of promoters, the repression level at an uninduced state, growth temperature, codon usage, codon context, mRNA secondary structure, translation kinetics, the presence/absence of chaperons and others. However, optimization of the growth medium’s composition is often overlooked. We systematically evaluate this factor, which can have a dramatic effect on the expression of recombinant proteins, especially those which are toxic to a recombinant host. Results Commonly used animal tissue- and plant-based media were evaluated using a series of clones in pET vector, containing expressed Open Reading Frames (ORFs) with a wide spectrum of toxicity to the recombinant E. coli: (i) gfpuv (nontoxic); (ii) tp84_28—which codes for thermophilic endolysin (moderately toxic); and (iii) tthHB27IRM—which codes for thermophilic restriction endonuclease-methyltransferase (REase-MTase)—RM.TthHB27I (very toxic). The use of plant-derived peptones (soy peptone and malt extract) in a culture medium causes the T7-lac expression system to leak. We show that the presence of raffinose and stachyose (galactoside derivatives) in those peptones causes premature and uncontrolled induction of gene expression, which affects the course of the culture, the stability of clones and biosynthesis levels. Conclusions The use of plant-derived peptones in a culture medium when using T7-lac hybrid promoter expression systems, such as Tabor-Studier, can lead to uncontrolled production of a recombinant protein. These conclusions also extend to other, lac operator-controlled promoters. In the case of proteins which are toxic to a recombinant host, this can result in mutations or deletions in the expression vector and/or cloned gene, the death of the host or highly decreased expression levels. This phenomenon is caused by the content of certain saccharides in plant peptones, some of which (galactosides) may act as T7-lac promoter inducer by interacting with a Lac repressor. Thus, when attempting to overexpress toxic proteins, it is recommended to either not use plant-derived media or to use them with caution and perform a pilot-scale evaluation of the derepression effect on a case-by-case basis.

Haoyun Sun, Jingzhao Mei, Weiwei Zhao et al.

As a major plant-specific transcription factor family, SPL genes play a crucial role in plant growth, development, and stress tolerance. The SPL transcription factor family has been widely studied in various plant species; however, systematic studies on SPL genes in the genus Ipomoea are lacking. Here, we identified a total of 29, 27, 26, and 23 SPLs in Ipomoea batatas, Ipomoea trifida, Ipomoea triloba, and Ipomoea nil, respectively. Based on the phylogenetic analysis of SPL proteins from model plants, the Ipomoea SPLs were classified into eight clades, which included conserved gene structures, domain organizations and motif compositions. Moreover, segmental duplication, which is derived from the Ipomoea lineage-specific whole-genome triplication event, was speculated to have a predominant role in Ipomoea SPL expansion. Particularly, tandem duplication was primarily responsible for the expansion of SPL subclades IV-b and IV-c. Furthermore, 25 interspecific orthologous groups were identified in Ipomoea, rice, Arabidopsis, and tomato. These findings support the expansion of SPLs in Ipomoea genus, with most of the SPLs being evolutionarily conserved. Of the 105 Ipomoea SPLs, 69 were predicted to be the targets of miR156, with seven IbSPLs being further verified as targets using degradome-seq data. Using transcriptomic data from aboveground and underground sweet potato tissues, IbSPLs showed diverse expression patterns, including seven highly expressed IbSPLs in the underground tissues. Furthermore, the expression of 11 IbSPLs was validated using qRT-PCR, and two (IbSPL17/IbSPL28) showed significantly increased expression during root development. Additionally, the qRT-PCR analysis revealed that six IbSPLs were strongly induced in the roots under phytohormone treatments, particularly zeatin and abscisic acid. Finally, the transcriptomic data of storage roots from 88 sweet potato accessions were used for weighted gene co-expression network analysis, which revealed four IbSPLs (IbSPL16/IbSPL17/IbSPL21/IbSPL28) clusters with genes involved in “regulation of root morphogenesis,” “cell division,” “cytoskeleton organization,” and “plant-type cell wall organization or biogenesis,” indicating their potential role in storage root development. This study not only provides novel insights into the evolutionary and functional divergence of the SPLs in the genus Ipomoea but also lays a foundation for further elucidation of the potential functional roles of IbSPLs on storage root development.

Qing Liu, Jierong Ding, Wenjie Huang et al.

Abstract Although type 2C protein phosphatases (PP2Cs) have been demonstrated to play important roles in regulating plant development and various stress responses, their specific roles in rice abiotic stress tolerance are still largely unknown. In this study, the functions of OsPP65 in rice osmotic and salt stress tolerance were investigated. Here, we report that OsPP65 is responsive to multiple stresses and is remarkably induced by osmotic and salt stress treatments. OsPP65 was highly expressed in rice seedlings and leaves and localized in the nucleus and cytoplasm. OsPP65 knockout rice plants showed enhanced tolerance to osmotic and salt stresses. Significantly higher induction of genes involved in jasmonic acid (JA) and abscisic acid (ABA) biosynthesis or signaling, as well as higher contents of endogenous JA and ABA, were observed in the OsPP65 knockout plants compared with the wild-type plants after osmotic stress treatment. Further analysis indicated that JA and ABA function independently in osmotic stress tolerance conferred by loss of OsPP65. Moreover, metabolomics analysis revealed higher endogenous levels of galactose and galactinol but a lower content of raffinose in the OsPP65 knockout plants than in the wild-type plants after osmotic stress treatment. These results together suggest that OsPP65 negatively regulates osmotic and salt stress tolerance through regulation of the JA and ABA signaling pathways and modulation of the raffinose family oligosaccharide metabolism pathway in rice. OsPP65 is a promising target for improvement of rice stress tolerance using gene editing.

Edyta Paulina Bogucka, Marios Constantinides, Luca Maria Aiello et al.

Throughout history, maps have been used as a tool to explore cities. They visualize a city's urban fabric through its streets, buildings, and points of interest. Besides purely navigation purposes, street names also reflect a city's culture through its commemorative practices. Therefore, cultural maps that unveil socio-cultural characteristics encoded in street names could potentially raise citizens' historical awareness. But designing effective cultural maps is challenging, not only due to data scarcity but also due to the lack of effective approaches to engage citizens with data exploration. To address these challenges, we collected a dataset of 5,000 streets across the cities of Paris, Vienna, London, and New York, and built their cultural maps grounded on cartographic storytelling techniques. Through data exploration scenarios, we demonstrated how cultural maps engage users and allow them to discover distinct patterns in the ways these cities are gender-biased, celebrate various professions, and embrace foreign cultures.

Changye Yang, Sriram Baireddy, Yuhao Chen et al.

Accurately phenotyping plant wilting is important for understanding responses to environmental stress. Analysis of the shape of plants can potentially be used to accurately quantify the degree of wilting. Plant shape analysis can be enhanced by locating the stem, which serves as a consistent reference point during wilting. In this paper, we show that deep learning methods can accurately segment tomato plant stems. We also propose a control-point-based ground truth method that drastically reduces the resources needed to create a training dataset for a deep learning approach. Experimental results show the viability of both our proposed ground truth approach and deep learning based stem segmentation.

Donald J. Docimo, Ziliang Kang, Kai A. James et al.

This article explores the optimization of plant characteristics and controller parameters for electrified mobility. Electrification of mobile transportation systems, such as automobiles and aircraft, presents the ability to improve key performance metrics such as efficiency and cost. However, the strong bidirectional coupling between electrical and thermal dynamics within new components creates integration challenges, increasing component degradation and reducing performance. Diminishing these issues requires novel plant designs and control strategies. The electrified mobility literature provides prior studies on plant and controller optimization, known as control co-design (CCD). A void within these studies is the lack of model predictive control (MPC), recognized to manage multi-domain dynamics for electrified systems, within CCD frameworks. This article addresses this through three contributions. First, a thermo-electro-mechanical hybrid electric vehicle (HEV) model is developed that is suitable for both plant optimization and MPC. Second, simultaneous plant and controller optimization is performed for this multi-domain system. Third, MPC is integrated within a CCD framework using the candidate HEV model. Results indicate that optimizing both the plant and MPC parameters simultaneously can reduce physical component sizes by over 60% and key performance metric errors by over 50%.

Qing Zhou, Qing Zhou, Qing Zhou et al.

Triploid breeding is a central way to improve growth traits, timber quality, and stress resistance in Populus. In the present study, the morphology and viability of colchicine-induced 2n pollen, triploid production by crossing induced 2n pollen, and identification of genetic constitution of colchicine-induced 2n pollen were conducted in Populus canescens based on optimizing technology for inducing chromosome doubling in pollen. We found that the meiotic stage, injection time, and the interaction between the meiotic stage and injection time had highly significant effects on the 2n pollen production rate. The most effective treatment for inducing 2n pollen was to give 11 injections of 0.5% colchicine solution when pollen mother cells (PMCs) were at the pachytene stage. The highest 2n pollen production rate was 30.27 ± 8.69%. Colchicine occasionally affected ectexine deposition, and some narrow furrows were detected in the ectexine structure. However, no significant difference was observed in the pollen germination rate between natural 2n pollen and colchicine-induced 2n pollen. Moreover, 5 triploids derived from FDR-type 2n pollen were generated by crossing induced 2n pollen, suggesting that colchicine does not eliminate the function of colchicine-induced 2n pollen. However, slower growth of 2n pollen tubes was responsible for a lower triploid production rate.