A Review on the Challenges for Increased Production of Castor
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Castor ( Ricinus communis L.) is one of the oldest cultivated crops, but currently it represents only 0.15% of the vegetable oil produced in the world. Castor oil is of continuing importance to the global specialty chemical industry because it is the only commercial source of a hydroxylated fatty acid. Castor also has tremendous future potential as an industrial oilseed crop because of its high seed oil content (more than 480 g kg −1 ), unique fatty acid composition (900 g kg −1 of ricinoleic acid), potentially high oil yields (1250–2500 L ha −1 ), and ability to be grown under drought and saline conditions. The scientific literature on castor has been generated by a relatively small global community of researchers over the past century. Much of this work was published in dozens of languages in journals that are not easily accessible to the scientific community. This review was conducted to provide a compilation of the most relevant historic research information and define the tremendous future potential of castor. The article was prepared by a group of 22 scientists from 16 institutions and eight countries. Topics discussed in this review include: (i) germplasm, genetics, breeding, biotic stresses, genome sequencing, and biotechnology; (ii) agronomic production practices, diseases, and abiotic stresses; (iii) management and reduction of toxins for the use of castor meal as both an animal feed and an organic fertilizer; (iv) future industrial uses of castor including renewable fuels; (v) world production, consumption, and prices; and (vi) potential and challenges for increased castor production.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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 it