Review of Options for Horticultural Research and Development: A Case of Zambia
Bibliographic record
Abstract
This review focused on horticultural development as a key economic subsector sector. Although practiced by more than 60 % of the population, agriculture and horticulture largely remain small scale in Zambia. Partly due to the relatively high income generation potential of commodities, the horticultural sector holds immense potential to make significant contribution to the poverty reduction. It has been estimated that since 1960, worldwide demand for fresh produce has more than doubled compared to a 20 % increase in demand for cereals. However, in Africa per capita supply of fresh produce has been declining since 1970. The key challenge therefore remains how to expand horticultural production in a manner that is sustainable and beneficial to all players throughout the food system. A vision of ‘An efficient and dynamic horticulture sector responsive to changing needs of society’ is advanced. This article reviews the emergence of horticulture sub sector contributing significantly to the agricultural GDP and poverty reduction, outlines its limitations and explores options for improving the sector. While the traditional biotic and abiotic approaches are the primary focus (improved research and development to drive production, and reduce postharvest losses), emerging challenges such as globalization, and climate change are considered. The findings suggest poor production technologies, limited crop varietal choices, high postharvest loses and inadequate marketing infrastructure and low smallholder participation horticultural markets contributing to overall poor sector performance. To achieve sustained and environmentally safe horticultural performance there is need to establish effective linkages, networks and partnerships among different players throughout the horticulture value and supply chains, both from private and public sectors.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".