Porosity effects on red to far-red ratios of light transmitted in natural sands: implications for photoblastic seed germination
Notice bibliographique
Résumé
Seed germination corresponds to the first and crucial stage of a plant’s life cycle. It is directly affected by water availability and soil characteristics, notably porosity. The seeds of many plant species are known to be photoblastic, i.e., their germination is also significantly affected by light exposure. A comprehensive understanding about the interconnected effects of these abiotic factors on seed germination is essential for the success of a broad range of applied research initiatives in agriculture and ecology. These initiatives include, for example, studies involving the germination of stress-adapted seeds in arid regions, like perennial desert habitats and desertified landscapes, and the germination of weed seeds in arable fields that may be covered by sand-textured soils (commonly referred to as natural sands). The germination of photoblastic seeds depends not only on the amount, but also on the spectral quality of the impinging light. This radiometric parameter can be expressed in terms of the ratio between red and far-red light reaching these seeds. In this research, we unveil the impact of variations in the porosity of sand-textured soils on their red to far-red ratios of transmitted light. Although one may expect that porosity can affect these ratios and, consequently, the germination of photoblastic seeds in natural sands, no systematic study about these putative connections has been reported in the literature to date. To some extent, this can be attributed to testing limitations posed by the actual handling of these granular materials, such as grain breakage and pore space disturbance, during investigations based on traditional experimental procedures. Moreover, the scant available information on these connections has been mostly derived from analyses performed on laboratory-prepared samples, which often present morphological characteristics that conspicuously differ from those of naturally-occurring deposits of these soils. In order to overcome these constraints, we employ an in silico investigation framework to carry out controlled light transmission experiments considering realistic characterizations of dry and water-saturated samples of natural sands. This framework is supported by measured spectral data and the use of a first-principles light transport model that explicitly accounts for the particulate structure of these materials. Our in silico experimental results provide a comprehensive depiction of the changes in the red to far-red ratios of light transmitted through natural sand layers of variable thickness due to variations on their porosity. Moreover, they also show that these changes are markedly modulated by the presence of water in these layers. Thus, our findings establish a predictive relationship between porosity and the light-elicited germination of photoblastic seeds in sand-textured soils subject to distinct degrees of water saturation. Accordingly, they are expected to contribute to the development of innovative technologies aimed at the predictive assessment (in situ or remote) of the compound impact of these abiotic factors on seed germination. These technologies, in turn, are likely to lead to new costeffective solutions for ongoing challenges in agriculture (e.g., crop yield enhancement) and ecology (e.g., invasive plant detection and vegetation restoration), particularly with respect to regions susceptible to extreme environmental conditions.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».