Sustainable extraction of personalized plant nano-stimulants from conspecific donor plants to induce mirror biostimulant activity in identical host plants
Bibliographic record
Abstract
Conventional agrochemical plant biostimulants have been used to increase crop yield and stress resistance, and this strategy continues to be integral to today's farming. While effective, the large-scale implantations of these products are not without environmental, ecological, and cost concerns and the associated climate-change challenges. To alleviate this long-standing pressure on agriculture, designing and developing more biocompatible and sustainable plant stimulants are among the primary focuses of agricultural management. Over the recent decades, the field has witnessed significant progress in emerging naturally derived or nature-inspired nano-biostimulants with large-active-surface areas, including bio-compounds, biopolymers, and nanocarbons. However, the extraction/preparation of these products may apply additional costs or require specific equipment. More recently, the field's attention has shifted to the sustainable application of chemical-additive-free biostimulants towards practical applications in nano-agriculture. Herein, we rationally designed and reported the first evidence and elucidation on biostimulant impacts of plant-self-derived nano-extracts from donor Arabidopsis thaliana as a model for inducing mirror biostimulant activities in conspecific host seeds, seedlings, and plants. Moreover, we assessed the effect of donor plants' age on short--, mid-, and long-term biocompatibility, growth, and development/maturation of the recipient plants for up to around 30 days. As a proof-of-concept, we found these autologous bio-extracts could effectively promote seed sprouting, seedling germination, and the development of soil-drenched plants of the same types. Our transmission-electron microscopy characterization of root/shoot pieces shows the presence of multiple phyto-compounds, including microtubules/actin filaments, cell vacuoles, Golgi stacks/endoplasmic reticulum, cell wall polysaccharide-based cellulose fibers, and organic amorphous nanoparticles and clusters of carbon quantum dots in the structure of these extracts. This personalized plant stimulation may induce further growth/defense-related mechanisms, setting new paradigms toward reducing the agrochemical inputs. Graphical Abstract • A proof-of-concept is presented to extract low-dimensional biostimulants from conspecific donor plants for identical host plants. • These water-based nano extracts encompass autologous phyto-compounds with excellent biocompatibility to conspecific plants. • These sustainable biostimulants could promote the seed-to-seedling transition/maturation and plant growth of the same type. • The physicochemical properties of these plant nano-stimulants are comparably characterized. • This innovative, facile, economical, and eco-friendly strategy benefit seed germination and plant stimulation in agriculture.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".