The Feasibility of Rice Bags and Ground Tarp Plastics as Low-Cost and Locally-Available Alternatives to Greenhouse Glazing
Bibliographic record
Abstract
Greenhouses can help farmers increase their yields and improve their livelihoods while reducing spoilage and furthering food security. As farms are getting smaller and access to water is getting more difficult, greenhouses are gradually gaining popularity in the agrarian economies of sub-Saharan Africa. Most greenhouses sold in the market are designed for commercial farmers and are beyond the reach of smallholders. The Humanitarian Engineering and Social Entrepreneurship (HESE) program at the Pennsylvania State University has developed and commercialized affordable greenhouses that utilize locally-sourced materials. The only exception is the glazing - the plastic covering on the greenhouse structure - which is imported from abroad. The cost of this glazing is too high, and is subject to foreign exchange fluctuations and supply chain anomalies. In an effort to further decrease the cost of the greenhouse, and thereby increase its accessibility in the market, this article investigates the feasibility of locally-available, inexpensive materials that can be used as substitutes for typical glazing materials. The primary emphasis of this paper is on rice bags and a Polyethylene ground tarp, which are both abundant, inexpensive materials found commonly in developing countries. Two properties of the materials were tested: light transmission and UV resistance, and a third test, water conservation, was performed on the ground tarp material. Results indicated that while rice bags are not an ideal substitute for standard glazing, they may be appropriate as low-cost shade nets, and the ground tarp plastic may prove appropriate as a potential greenhouse glazing replacement.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".