Effects of Micronutrients on the Nutritional Status of Clonal Tea Replanted in Areas Where Old Tea Was Uprooted
Bibliographic record
Abstract
Tea yields peak is 21-30 years after which yields decline. The declining productivity and moribuncy has been reported in many tea fields due to prolonged period of monoculture under tea, physicochemical and biological properties of soil deteriorate considerably causing diseases, pests, acidic soils among others which leads to uprooting of old tea bushes. Deficiency of micronutrients in some tea sections has been reported which has been corrected by foliar application. Though the deficiency could be corrected through foliar application, this mode of application has its shortcomings including leaf burn and the mobility of nutrients from the leaves to the roots is very slow. This study aimed at determining the effect of soil application and variation of micronutrients on the nutritional status of clonal tea replanted in old tea lands.Leaf and soil samples were collected in a random complete block design and the micromutrient levels determined using Inductively Coupled Plasma Emission (ICPE). Data analysis was done using MSTAT-C software.The changes in the levels of micronutrients with varied eight micronutrient combinations subjected on different clones were studied. Clone 12/28 significantly (P≤0.05) varied with the other clones indicating that different clones have varied abilities to absorb nutrients. Clone 303/577 gave a significantly higher uptake of B in the order TRFK303/577 >S15/10 >12/28 >31/8. Clone 12/28 recorded a higher uptake of N with mean levels of 3.075, clone 31/8 had significantly higher uptakes of Fe and Zn. None of the micronutrients subjected on the clones brought an impact in the uptake of N and Mg. This study therefore recommends the use of soil application of micronutrients as an alternative to foliar application in areas where old tea bushes were uprooted.
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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 | 0.000 |
| 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".