Nutrients Uptake and Accumulation in Plant Parts of Fragrant Rosa Species Irrigated with Treated and Untreated Wastewater
Bibliographic record
Abstract
Water scarcity has critically augmented the need for the exploration of alternative irrigation sources mainly in water-scarce regions. This water scarcity has put tremendous pressure on the agri-based economy of countries such as Pakistan. The reuse of sewage wastewater has been appearing as the only alternative water source, which can lessen our dependence upon freshwater (FW). The current study aimed to scrutinize the influence of treated wastewater (TWW) and untreated wastewater (UTWW) irrigation on the nutrient (N, P, K, Ca, and Na) concentration in different plant parts, i.e., roots, stems, leaves, and flowers, of four scented Rosa species (R. bourboniana, R. centifolia, R. Gruss-an-telpitz, and R. damascena) during the first week of 2018 to the last week of 2019. The experiment was arranged according to the two-factor factorial arrangement i.e., factor I was the irrigation source, while factor II was the Rosa species. The experimental water analysis showed that mineral and chemical concentrations in FW and TWW were within permissible limits of national environmental quality standards (NEQSs) for wastewater. The UTWW of this study possessed a higher electrical conductivity (EC), chemical oxygen demand (COD), biological oxygen demand (BOD), total nitrogen (TN), and metals (Cd, Co, and Pb) than recommended levels. The results revealed that P, K, Ca, and Na contents significantly increased in all studied plant parts of Rosa species as the duration of irrigation with TWW and UTWW increased and vice versa in the case of N contents, while the ratio of N content elevation by applying TWW and UTWW were also not increased compared to other studied nutrients. The nutrients (except Ca) were found as maximum in all plant parts with UTWW compared to FW and TWW irrigation in roses. These stimulations were accredited to the presence of higher essential nutrients and some metals in UTWW. This experiment confirmed the disparities in nutrient contents of scented Rosa species due to the different absorbability of each element in every plant part. Regarding the nutrient accumulation in rose plant tissues, the results of the present study confirm that untreated wastewater must be treated to some extent to grow scented roses where water is scarce.
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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".