Investigating Nano-Titanium Dioxide on the Morphological and Biochemical Characteristics of Some Strawberry Cultivars under Hydroponic Cultivation Conditions
Bibliographic record
Abstract
Introduction Today, in the commercial production of strawberries, short day cultivars are used due to having large fruits of desirable quality. Among the short day cultivars available in Iranare Camarosa, Atabaki, Gaviota, Queen Aliza, Paros and McDonance, which can be cultivated at greenhouse. Titanium dioxide (TiO2) nanoparticles are one of the metal oxides that exist in three forms of rutile, brookite and anatase, which affect growth, enzymatic activity and photosynthesis. Reported titanium nano dioxide in the highest concentration used (11.5 mg/l) increases fruit formation percentage, leaf chlorophyll content, vitamin C content, fruit ripening index, fresh and dry weight of roots and shoots and yield of strawberries. In another study, it was shown that titanium dioxide treatment under drought stress can increase photosynthetic pigments, total soluble solids, vitamin C, phenol, flavonoid, anthocyanin, and antioxidant activity, and it also improved plant performance. increase the strawberry cultivar Ventana compared to the control treatment. In a research found that spraying titanium increases the biomass, fertility and quality of peach fruit. It has alsow been showed that the pomegranate size of flowers and fruits increased with using titanium nano dioxide, and this can increase the quantity and quality of Alberta peach cultivar. Foliar application of titanium nano dioxide in cucumber has been reported to increase photosynthesis and phenolic content and reduce lipid peroxidation. In a research, it was shown that titanium dioxide nanoparticles increased photosynthesis rate, water conductivity and transpiration rate in tomato leaves. Despite the effect of titanium dioxide nanoparticles on the quantitative and qualitative improvement of some agricultural products, the researches conducted on strawberry plants were not complete or were only conducted on a specific variety. Therefore, with the aim of investigating and comparing the morphological and biochemical traits of some commercial strawberry cultivars under the effect of foliar spraying with titaniumdioxide, the above research was conducted. Materials and Methods This research was conducted to investigate the effect of nano titanium dioxide foliar spraying on four strawberry cultivars in the hydroponic greenhouse of the Department of Horticultural Sciences, Faculty of Agriculture, Ferdowsi University of Mashhad in 2020-2021. Experimental treatments included 4 levels of titanium nano dioxide (0, 5, 10 and 20 mg/l) and 4 strawberry cultivars (Sabrina, Paros, Gaviota and Camarosa) with 4 replications. The research was done in a factorial manner based on a completely random design. JMP 8 software was used to perform variance analysis and compare the averages of the measured traits. Means were compared using Tukey test at 5% probability level and graphs were drawn using Excel 2010 software. Results and Discussion According to the tables of mutual effects of titanium dioxide nano treatments and varieties, it can be found that the application of titanium dioxide nanoparticles had a positive effect on the desired characteristics in all four studied strawberry varieties. So that the application of different levels of titanium dioxide nano particles causes a significant increase in quantitative traits (number of leaves, leaf area, root length, fresh and dry weight of aerial and root parts, photosynthetic pigments) The yield-dependent traits compared to the control plants were found in strawberry-strawberry cultivars. Nano titanium dioxide had an effect in increasing the number of fruits and vegetative traits of all investigated cultivars, in such a way that, on the one hand, with a balanced increase in vegetative growth, and on the other hand, improving the efficiency of photosynthesis and absorption through the roots and increasing the percentage of fruit formation. , increased the yield per plant. Also, sprinkling of titanium nanoparticles on all levels caused a significant increase in juice pH, TSS, TA, vitamin C, anthocyanin, total phenol, flavonoid and in general qualitative traits compared to the control. In the treatment of nano titanium dioxide, especially at the level of 10 mg/liter, better results were observed. Conclusion According to the results, the use of Paros and Gaviota cultivars is recommended to farmers and agricultural researchers due to its high yield and good quality.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".