Impact of Climate Change on Sugarcane and Wheat Crops in District Hyderabad Sindh, Pakistan
Bibliographic record
Abstract
Present research was conducted to observe the effect of climatically changes on agricultural crops, especially focusing on major climatic variable changes such as (temperature and rainfall) on wheat and sugarcane productions. Therefore this study is attempt to examine the climate change impact on production of wheat and sugarcane crops in Hyderabad district to measure the fluctuations every month during last 12 years from 2002 to 2014. Thus the following objectives were studied. To examine climate change (temperature and rainfall) scenario in the study area. To observe climate change impact on sugarcane and wheat crops of Hyderabad district, and to see the effect of temperature on the growth performance of wheat and sugarcane crop since 2002 to 2014. Findings of the study shows positive impact on sugarcane and wheat crop. Moreover 1 oC temperature increases then wheat yield increases 30.04 kgs/acre. Similarly 1oC increase temperature increases sugarcane yield rise by the amount of 450 kgs/acre respectively. Additional, to see the average growth rate from 2002 to 2014, where it reveals that the temperature growth rate was increased 0.6 0C in April. While 1 oC increased in June which is highest growth rate, similarly in July and August were 0.5 0C and 0.5 0C was increased respectively, Kharif temperature having increasing trend. Moreover in Rabi season there is high fluctuation in February which was 0.4 oC. It Is concluded that in last the trend of temperature fluctuations from 2002 to 2014. in the Kharif season temperature in April, May, June, July, August and September were 2.4, 1.25, 6.1, 0.85, 2.75, 3.55, moreover the fluctuations of Rabi season in October, November, December, January, February, March were average 2, 1.42, 1, 2.3, 1.1, and 2.2 respectively.
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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 | 0.001 | 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 | 0.001 | 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".