Growing Temperature Influence Lignocellulose in Sorghum and Could Lead to a Significant Variation in Feed Value of Fodder Sorghum Genotypes
Bibliographic record
Abstract
Sorghum (Sorghum bicolor (L.) Moench) presents a suitable source of green fodder in the livestock sector. However, its use as livestock feed is limited by a high concentration of lignocellulose. A study was conducted to evaluate the influence of environment and developmental stage of harvesting on lignin, cellulose, and hemicellulose concentration of selected fodder sorghum cultivars. A field experiment was laid in a randomized complete block design and replicated three times at Egerton University (0°22′S; 35°55′E in Nakuru county), Rongai (0°23′N; 35°51′E in Nakuru county) and Marigat (0°46′N; 35°98′E in Baringo county) in Kenya in the years 2019 and 2020. Twenty different genotypes of sorghum were grown in a randomized complete block design and sampled at the booting and dough stages of development. The samples were analyzed for cellulose, lignin, and hemicellulose content. Plant growth, number of days to 50% heading, and daily average temperatures were recorded. Cellulose, hemicellulose, and lignin content varied among genotypes and across the three environments. The lowest cellulose content was recorded in line E6518 when sampled at the booting stage at Egerton (17.02%) while the highest concentration was recorded in IS11442 (43.87%) from Marigat at the dough stage. Lignin was highest in sorghum grown at Marigat than at Egerton and Rongai while sorghum harvested at dough stage had higher cellulose, hemicellulose, and lignin concentration than at booting stage. Location which distinctively varied on average daily temperature had a significant (p > 0.05) effect on the three parameters with sorghum grown at Egerton showing the lowest lignocellulose content followed by Rongai and Marigat, respectively. Lignin was positively correlated with plant height and days to 50% heading. However, regression analysis showed a negative relationship between days to 50% heading and the total sum of temperature. Crop developmental stage, genotype, and environment determine the lignin, cellulose, and hemicellulose concentration in fodder sorghum. The recommendation of suitable sorghum fodder for a region should consider local growing temperature and the developmental stage of harvesting.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".