Hasil untuk "Plant culture"

E. Hewitt

I. I. Ozyigit, I. Dogan, Asli Hocaoglu-Ozyigit et al.

Plants are the sources of many bioactive secondary metabolites which are present in plant organs including leaves, stems, roots, and flowers. Although they provide advantages to the plants in many cases, they are not necessary for metabolisms related to growth, development, and reproduction. They are specific to plant species and are precursor substances, which can be modified for generations of various compounds in different plant species. Secondary metabolites are used in many industries, including dye, food processing and cosmetic industries, and in agricultural control as well as being used as pharmaceutical raw materials by humans. For this reason, the demand is high; therefore, they are needed to be obtained in large volumes and the large productions can be achieved using biotechnological methods in addition to production, being done with classical methods. For this, plant biotechnology can be put in action through using different methods. The most important of these methods include tissue culture and gene transfer. The genetically modified plants are agriculturally more productive and are commercially more effective and are valuable tools for industrial and medical purposes as well as being the sources of many secondary metabolites of therapeutic importance. With plant tissue culture applications, which are also the first step in obtaining transgenic plants with having desirable characteristics, it is possible to produce specific secondary metabolites in large-scale through using whole plants or using specific tissues of these plants in laboratory conditions. Currently, many studies are going on this subject, and some of them receiving attention are found to be taken place in plant biotechnology and having promising applications. In this work, particularly benefits of secondary metabolites, and their productions through tissue culture-based biotechnological applications are discussed using literature with presence of current studies.

Takumi Ohashi, Hitoshi Iyatomi

Large language models (LLMs) are increasingly deployed in multicultural settings; however, systematic evaluation of cultural specificity at the sentence level remains underexplored. We propose the Conceptual Cultural Index (CCI), which estimates cultural specificity at the sentence level. CCI is defined as the difference between the generality estimate within the target culture and the average generality estimate across other cultures. This formulation enables users to operationally control the scope of culture via comparison settings and provides interpretability, since the score derives from the underlying generality estimates. We validate CCI on 400 sentences (200 culture-specific and 200 general), and the resulting score distribution exhibits the anticipated pattern: higher for culture-specific sentences and lower for general ones. For binary separability, CCI outperforms direct LLM scoring, yielding more than a 10-point improvement in AUC for models specialized to the target culture. Our code is available at https://github.com/IyatomiLab/CCI .

Jinyu Xu, Tianqi Hu, Xiaonan Hu et al.

Visually cataloging and quantifying the natural world requires pushing the boundaries of both detailed visual classification and counting at scale. Despite significant progress, particularly in crowd and traffic analysis, the fine-grained, taxonomy-aware plant counting remains underexplored in vision. In contrast to crowds, plants exhibit nonrigid morphologies and physical appearance variations across growth stages and environments. To fill this gap, we present TPC-268, the first plant counting benchmark incorporating plant taxonomy. Our dataset couples instance-level point annotations with Linnaean labels (kingdom -> species) and organ categories, enabling hierarchical reasoning and species-aware evaluation. The dataset features 10,000 images with 678,050 point annotations, includes 268 countable plant categories over 242 plant species in Plantae and Fungi, and spans observation scales from canopy-level remote sensing imagery to tissue-level microscopy. We follow the problem setting of class-agnostic counting (CAC), provide taxonomy-consistent, scale-aware data splits, and benchmark state-of-the-art regression- and detection-based CAC approaches. By capturing the biodiversity, hierarchical structure, and multi-scale nature of botanical and mycological taxa, TPC-268 provides a biologically grounded testbed to advance fine-grained class-agnostic counting. Dataset and code are available at https://github.com/tiny-smart/TPC-268.

Binchi Zhang, Xujiang Zhao, Jundong Li et al.

Large language models (LLMs) are increasingly deployed in culturally sensitive real-world tasks. However, existing cultural alignment approaches fail to align LLMs' broad cultural values with the specific goals of downstream tasks and suffer from cross-culture interference. We propose CultureManager, a novel pipeline for task-specific cultural alignment. CultureManager synthesizes task-aware cultural data in line with target task formats, grounded in culturally relevant web search results. To prevent conflicts between cultural norms, it manages multi-culture knowledge learned in separate adapters with a culture router that selects the appropriate one to apply. Experiments across ten national cultures and culture-sensitive tasks show consistent improvements over prompt-based and fine-tuning baselines. Our results demonstrate the necessity of task adaptation and modular culture management for effective cultural alignment.

Renqiang Li, Muhammad Usama Hameed, Koen Geuten

From slow, non-uniform germination to pre-harvest sprouting (PHS), both extremes of seed dormancy have posed challenges for plant breeders. Because this trait needs to be genetically tuned in relation to environmental cues, controlling the problem of pre-harvest sprouting can only be realized through a better understanding of the biological mechanisms of seed dormancy. Yet studying seed dormancy poses challenges, because of its complexity in the different modes of regulation (physical, chemical, developmental, physiological and genetic) in interaction with environmental cues (light, temperature, water and nutrients) and lack of natural variation in the commercial crop genetic resources. Building information from model systems can help guide our research efforts. While phylogenetically distant from temperate cereals, the available information for Arabidopsis is much more elaborate and can, to a certain extent, be translated. We therefore provide a comprehensive comparison of the mechanisms and pathways and indicate similarities, differences and knowledge gaps. While knowledge from Arabidopsis is highly valuable to guide seed dormancy studies in temperate cereals, effective knowledge translation that includes functional validation will often require the use of the more closely related “model system” Brachypodium. This model will also allow us to unravel derived or unique mechanisms in temperate cereals. As an indication of such derived mechanisms, we also discuss the genetic factors involved in seed dormancy control discovered in cereals, often through natural variation studies.

Naitian Zhou, David Bamman, Isaac L. Bleaman

The field of cultural NLP has recently experienced rapid growth, driven by a pressing need to ensure that language technologies are effective and safe across a pluralistic user base. This work has largely progressed without a shared conception of culture, instead choosing to rely on a wide array of cultural proxies. However, this leads to a number of recurring limitations: coarse national boundaries fail to capture nuanced differences that lay within them, limited coverage restricts datasets to only a subset of usually highly-represented cultures, and a lack of dynamicity results in static cultural benchmarks that do not change as culture evolves. In this position paper, we argue that these methodological limitations are symptomatic of a theoretical gap. We draw on a well-developed theory of culture from sociocultural linguistics to fill this gap by 1) demonstrating in a case study how it can clarify methodological constraints and affordances, 2) offering theoretically-motivated paths forward to achieving cultural competence, and 3) arguing that localization is a more useful framing for the goals of much current work in cultural NLP.

Daniel Mwesigwa

AI is flattening culture. Evaluations of "culture" are showing the myriad ways in which large AI models are homogenizing language and culture, averaging out rich linguistic differences into generic expressions. I call this phenomenon "softmaxing culture,'' and it is one of the fundamental challenges facing AI evaluations today. Efforts to improve and strengthen evaluations of culture are central to the project of cultural alignment in large AI systems. This position paper argues that machine learning (ML) and human-computer interaction (HCI) approaches to evaluation are limited. I propose two key conceptual shifts. First, instead of asking "what is culture?" at the start of system evaluations, I propose beginning with the question: "when is culture?" Second, while I acknowledge the philosophical claim that cultural universals exist, the challenge is not simply to describe them, but to situate them in relation to their particulars. Taken together, these conceptual shifts invite evaluation approaches that move beyond technical requirements toward perspectives that are more responsive to the complexities of culture.

Henri Gouin

Since Charles Darwin's time, the study of climbing plants on a cylindrical stake has been the subject of numerous articles in plant biology. One of the main ideas for studying the coiling of an elastic plant stem is to consider the growth of the plant stem in terms of evolution over time. However, as this development takes place over a long time scale, the static study alone has not been studied independently. Our static approach requires us to take into account elasticity, turgor pressure and gravity forces in a first analysis. The aim of this article is to present a simplified model demonstrating why plant stems climb mainly on their circular helix-shaped stakes, with the diameter of the stake playing an important role in plant stem ascent, as does the fineness of the stem. To perform this calculation, for a given mass density, we consider the variational principle of minimum energy. For thin plant stems, we can see, in first approximation, that the effect of gravity and turgor pressure can be neglected with respect to the energy of elasticity, and that the bulk of the calculation concerns elasticity terms.

James Luther, Donald Brown

Culture is the bedrock of human interaction; it dictates how we perceive and respond to everyday interactions. As the field of human-computer interaction grows via the rise of generative Large Language Models (LLMs), the cultural alignment of these models become an important field of study. This work, using the VSM13 International Survey and Hofstede's cultural dimensions, identifies the cultural alignment of popular LLMs (DeepSeek-V3, V3.1, GPT-5, GPT-4.1, GPT-4, Claude Opus 4, Llama 3.1, and Mistral Large). We then use cultural prompting, or using system prompts to shift the cultural alignment of a model to a desired country, to test the adaptability of these models to other cultures, namely China, France, India, Iran, Japan, and the United States. We find that the majority of the eight LLMs tested favor the United States when the culture is not specified, with varying results when prompted for other cultures. When using cultural prompting, seven of the eight models shifted closer to the expected culture. We find that models had trouble aligning with Japan and China, despite two of the models tested originating with the Chinese company DeepSeek.

Umadini Ranasinghe, Abigail L. Stressinger, Guangpeng Xu et al.

Overcoming the strong chlorophyll background poses a significant challenge for measuring and optimizing plant growth. This research investigates the novel application of specialized quantum light emitters introduced into intact leaves of tobacco (Nicotiana tabacum), a well-characterized model plant system for studies of plant health and productivity. Leaves were harvested from plants cultivated under two distinct conditions: low light (LL), representing unhealthy leaves with reduced photosynthesis. and high light (HL), representing healthy leaves with highly active photosynthesis. Higher-order correlation data were collected and analyzed using machine learning (ML) techniques, specifically a Convolutional Neural Network (CNN), to classify the photon emitter states. This CNN efficiently identified unique patterns and created distinct fingerprints for Nicotiana leaves grown under LL and HL, demonstrating significantly different quantum profiles between the two conditions. These quantum fingerprints serve as a foundation for a novel unified analysis of plant growth parameters associated with different photosynthetic states. By employing CNN, the emitter profiles were able to reproducibly classify the leaves as healthy or unhealthy. This model achieved high probability values for each classification, confirming its accuracy and reliability. The findings of this study pave the way for broader applications, including the application of advanced quantum and machine learning technologies in plant health monitoring systems.

Payman A. A. Zibari, Zhiyan A. Teli, Mohammed A. Hussain

Four genotypes of faba bean Vicia faba L. (Aknadcge, FlIP-17-078FB, FLIP-17-072FB and Fiedo were carried out during 2020-2021 winter season in year under four levels of phosphorus (0.0 18,36 and 54 Kg ha-1) at the farm of field crops department, college of Agricultural Engineering science, University of Duhok, the experiment unit ranged in factorial within randomized complete block design with three replications. The result show significant effect of faba bean genotypes for all studies traits except plant height and main branches per plant and number of seed per plant, while the phosphorus level exhibited highly significant effect on all studies traits except plant Height and main branches the interaction between genotypes and phosphorus levels show significant effect for days to flowering, pod length, 100 seed weight and number nodes per plant and the rest traits exhibited non-significant. The fedo genotypes was superior in pod weight, 100 seed weight, number of nodules plant-1 and number of pods plant-1. The seed yield gave positive correlation with number of nodules plant-1 (0.742, 0.751) phenotypic and genotypic and positive correlation with 100 seed weight (0.673 and 0.694).

Kazuya Murakami, Misao Sato, Momoki Kubota et al.

Plants display physical displacements during their growth due to photosynthesis, which converts light into chemical energy. This can be interpreted as plants acting as actuators with a built-in power source. This paper presents a method to create plant robots that move and perform tasks by harnessing the actuation output of plants: displacement and force generated from the growing process. As the target plant, radish sprouts are employed, and their displacement and force are characterized, followed by the calculation of power and energy densities. Based on the characterization, two different plant robots are designed and fabricated: a rotational robot and a gripper. The former demonstrates ground locomotion, achieving a travel distance of 14.6 mm with an average speed of 0.8 mm/h. The latter demonstrates the picking and placing of an object with a 0.1-g mass by the light-controlled open-close motion of plant fingers. A good agreement between the experimental and model values is observed in the specific data of the mobile robot, suggesting that obtaining the actuation characteristics of plants can enable the design and prediction of behavior in plant robots. These results pave the way for the realization of novel types of environmentally friendly and sustainable robots.

Pushpdeep Singh, Mayur Patidar, Lovekesh Vig

LLMs are increasingly being deployed for multilingual applications and have demonstrated impressive translation capabilities between several low and high-resource languages. An aspect of translation that often gets overlooked is that of cultural adaptation, or modifying source culture references to suit the target culture. While specialized translation models still outperform LLMs on the machine translation task when viewed from the lens of correctness, they are not sensitive to cultural differences often requiring manual correction. LLMs on the other hand have a rich reservoir of cultural knowledge embedded within its parameters that can be potentially exploited for such applications. In this paper, we define the task of cultural adaptation and create an evaluation framework to evaluate the performance of modern LLMs for cultural adaptation and analyze their cross-cultural knowledge while connecting related concepts across different cultures. We also analyze possible issues with automatic adaptation. We hope that this task will offer more insight into the cultural understanding of LLMs and their creativity in cross-cultural scenarios.

Jiahao Yuan, Zixiang Di, Shangzixin Zhao et al.

Large language models (LLMs) face challenges in aligning with diverse cultural values despite their remarkable performance in generation, which stems from inherent monocultural biases and difficulties in capturing nuanced cultural semantics. Existing methods struggle to adapt to unknown culture after fine-tuning. Inspired by cultural geography across five continents, we propose Cultural Palette, a multi-agent framework that redefines cultural alignment as an adaptive "color-blending" process for country-specific adaptation. Our approach harnesses cultural geography across five continents through three key steps: First, we synthesize the Pentachromatic Cultural Palette Dataset using GPT-4o, refining continental-level dialogues with Hofstede's cultural dimensions to establish foundational cultural representations. Second, five continent-level alignment agents form specialized cultural communities that generate region-specific draft responses. Third, a Meta Agent employs Cultural MoErges to dynamically blend these cultural "colors" through attention-gated parameter merging, akin to mixing pigments on a palette, resolving conflicts while preserving cultural nuances to produce the final culturally-aligned response. Extensive experiments across various countries demonstrate that \textit{Cultural Palette} surpasses existing baselines in cultural alignment.

Allison Wickham, Jessica G. Davis

Bell peppers (<i>Capsicum annuum</i>) were grown in a greenhouse to evaluate organic fertilizer and foliar seaweed application effects on plant architecture, yield, and fruit quality. Many organic fertilizers contain phytohormones intrinsically. Hydrolyzed and non-hydrolyzed fish fertilizer and cyano-fertilizer treatments were applied in split applications every 7 days over a 135-day growing period. Control plants received no supplemental N. Each fertilizer treatment received applications of one of two different foliar seaweeds or no foliar seaweed in a 4 × 3 factorial design with three replications. Both hydrolyzed and non-hydrolyzed fish fertilizers and cyano-fertilizer increased the number of branches per plant compared to the N-deficient control. The plants receiving cyano-fertilizer or non-hydrolyzed fish fertilizer yielded more than the N-deficient control, and those treatments received 2–3 times the auxin application as the hydrolyzed fish fertilizer. In addition, the leaves from the plants treated with non-hydrolyzed fish fertilizer contained substantially higher levels of abscisic acid, although no abscisic acid was detected in the fertilizers. Both seaweed products decreased the number of fruits that were “bell”-shaped and increased the number of “long”-shaped fruits. Organic fertilizers are complex matrices of nutrients, phytohormones, and other metabolites, making it very challenging to determine the mechanisms behind the observations.

Marisol Ochoa-Villarreal, Susan Howat, Sunmi Hong et al.

Plants have evolved a vast chemical cornucopia to support their sessile lifestyles. Man has exploited this natural resource since Neolithic times and currently plant-derived chemicals are exploited for a myriad of applications. However, plant sources of most high-value natural products (NPs) are not domesticated and therefore their production cannot be undertaken on an agricultural scale. Further, these plant species are often slow growing, their populations limiting, the concentration of the target molecule highly variable and routinely present at extremely low concentrations. Plant cell and organ culture constitutes a sustainable, controllable and environmentally friendly tool for the industrial production of plant NPs. Further, advances in cell line selection, biotransformation, product secretion, cell permeabilisation, extraction and scale-up, among others, are driving increases in plant NP yields. However, there remain significant obstacles to the commercial synthesis of high-value chemicals from these sources. The relatively recent isolation, culturing and characterisation of cambial meristematic cells (CMCs), provides an emerging platform to circumvent many of these potential difficulties. [BMB Reports 2016; 49(3): 149-158]

M. I. Días, M. Sousa, R. C. Alves et al.

D. S. Batista, S. H. S. Felipe, Tatiane Dulcineia Silva et al.

R. Eibl, Philipp Meier, Irène Stutz et al.

The production of drugs, cosmetics, and food which are derived from plant cell and tissue cultures has a long tradition. The emerging trend of manufacturing cosmetics and food products in a natural and sustainable manner has brought a new wave in plant cell culture technology over the past 10 years. More than 50 products based on extracts from plant cell cultures have made their way into the cosmetics industry during this time, whereby the majority is produced with plant cell suspension cultures. In addition, the first plant cell culture-based food supplement ingredients, such as Echigena Plus and Teoside 10, are now produced at production scale. In this mini review, we discuss the reasons for and the characteristics as well as the challenges of plant cell culture-based productions for the cosmetics and food industries. It focuses on the current state of the art in this field. In addition, two examples of the latest developments in plant cell culture-based food production are presented, that is, superfood which boosts health and food that can be produced in the lab or at home.