Dry Matter Content and Stability of Carotenoids in Kale and Spinach During Drying
Bibliographic record
Abstract
Drying of spinach ( Spinacia oleracea L.) and kale ( Brassica oleracea L. var. acephala D.C.) is required to determine percentage of dry matter (%DM) and pigment concentration of fresh leaves. ‘Melody’ spinach and ‘Winterbor’ kale were greenhouse-grown in hydroponic nutrient solutions containing 13 or 105 mg·L −1 N. Using vacuum freeze dryers and convection ovens, plant tissues were dried for 120 h at five different temperature treatments: 1) freeze drying at −25 °C; 2) freeze drying at 0 °C; 3) vacuum drying at +25 °C; 4) oven drying at +50 °C; and 5) oven drying at +75 °C. Spinach leaf tissue %DM was affected, but kale %DM was unaffected by drying temperature. Spinach and kale leaf tissue %DM were both affected by N level. The high N spinach decreased from 7.3 to 6.4%DM when drying temperature increased from +25 to +75 °C. The low N spinach decreased from 12.7 to 9.6%DM as the drying temperature increased from −25 to +50 °C. Kale averaged from 14.8%DM for the high N treatment and from 21.8%DM for the low N treatment. However, drying temperature did not have a significant impact on measured %DM in kale. Lutein, β-carotene, and chlorophyll levels for both spinach and kale leaf tissue were affected by drying temperature. Measured concentrations of all pigments decreased over 70% as the drying temperature increased from −25 to 75 °C. The largest pigment fresh and dry weight concentrations for spinach and kale were measured at drying temperatures below +25 °C. The spinach and kale samples dried between −25 and +25 °C were not significantly different from each other in %DM or pigment concentration measured on a dry or fresh weight basis. Thus, drying leaf tissue for accurate pigment analysis requires temperatures below +25 °C using vacuum or freeze drying technology.
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.
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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".