Background: Evidence suggests that plants can behave intelligently by exhibiting the ability to learn, make associations between environmental cues, engage in complex decisions about resource acquisition, memorize, and adapt in flexible ways. However, plant intelligence is a disputed concept in the scientific community. Reasons for lack of consensus can be traced back to the history of Western philosophy, interpretation of terminology, and due to plants lacking neurons and a central nervous system. Plant intelligence thus constitutes a novel paradigm in the plant sciences. Therefore, the perspectives of scientists in plant-related disciplines need to be investigated in order to gain insight into the current state and future development of this concept.
Methods: This study analyzed opinions of plant intelligence held by scientists from different plant-related disciplines, including ethnobiology and other biological sciences, through an online questionnaire.
Results: Our findings show that respondents' personal belief systems and the frequency of taking into account other types of knowledge, such as traditional knowledge, in their own field(s) of study, were associated with their opinions of plant intelligence. Meanwhile, respondents' professional expertise, background (discipline), or familiarity with evidence provided on plant intelligence did not affect their opinions.
Conclusions: This study emphasizes the influential role of scientists' own subjective beliefs. In response, two approaches could facilitate transdisciplinary understanding among scientists: (1) effective communication designed to foster change in agreement based on presented information; and (2) holding space for an interdisciplinary dialogue where scientists can express their own subjectivities and open new opportunities for collaboration.
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http://dx.doi.org/10.1186/s13002-022-00539-3 | DOI Listing |
Front Plant Sci
December 2024
Institute of Technology, Anhui Agricultural University, Hefei, China.
Introduction: The rapid urbanization of rural regions, along with an aging population, has resulted in a substantial manpower scarcity for agricultural output, necessitating the urgent development of highly intelligent and accurate agricultural equipment technologies.
Methods: This research introduces YOLOv8-PSS, an enhanced lightweight obstacle detection model, to increase the effectiveness and safety of unmanned agricultural robots in intricate field situations. This YOLOv8-based model incorporates a depth camera to precisely identify and locate impediments in the way of autonomous agricultural equipment.
Org Lett
January 2025
Engineering Research Center of Tropical Medicine Innovation and Transformation of Ministry of Education, International Joint Research Center of Human-machine Intelligent Collaborative for Tumor Precision Diagnosis and Treatment of Hainan Province, Hainan Provincial Key Laboratory of Research and Development on Tropical Herbs, School of Pharmacy, Hainan Medical University, Haikou 571199, China.
A condition-controlled Rh(III)-catalyzed selective synthesis of CF-substituted indoles and pyrido[2,1-]isoindoles from 2-arylpyridines and CF-imidoyl sulfoxonium ylides has been developed. The Cp*Rh(MeCN)(SbF)/HFIP system afforded CF-substituted indoles via triple C-H activation, while the [Cp*RhCl]/MeCN condition selectively furnished CF-substituted pyrido[2,1-]isoindoles through C-H [4 + 1] annulation. The notable advantages of this developed method included readily available starting materials, broad substrate scope, and excellent chemoselectivity.
View Article and Find Full Text PDFMol Plant
January 2025
Center for Applied Genetic Technologies, University of Georgia, Athens, USA.
Soybean, the fourth most important crop in the world, uniquely serves as a source of both plant oil and plant protein for the world's food and animal feed. Although soybean production has increased approximately 13-fold over the past 60 years, the continually growing global population necessitates further increases in soybean production. In the past, especially in the last decade, significant progress has been made in both functional genomics and molecular breeding.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Centre for the Research and Technology of Agro-Environmental and Biological Sciences, University of Trás-os-Montes e Alto Douro, 5000-801 Vila Real, Portugal.
Grapevines ( L.) are one of the most economically relevant crops worldwide, yet they are highly vulnerable to various diseases, causing substantial economic losses for winegrowers. This systematic review evaluates the application of remote sensing and proximal tools for vineyard disease detection, addressing current capabilities, gaps, and future directions in sensor-based field monitoring of grapevine diseases.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Hubei Province Engineering Technology Research Center for Construction Quality Testing Equipments, College of Computer and Information Technology, China Three Gorges University, Yichang 443002, China.
With the widespread use of autonomous guided vehicles (AGVs), avoiding collisions has become a challenging problem. Addressing the issue is not straightforward since production efficiency, collision avoidance, and energy consumption are conflicting factors. This paper proposes a novel edge computing method based on vehicle edge intelligence to solve the energy-efficient collision-free machine/AGV scheduling problem.
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