MétaCan
Menu
Back to cohort
Record W4416795056 · doi:10.1155/sci5/9158280

Comprehensive Assessment of Local and Exotic Sorghum Genotypes for Forage Production and Quality Under Drought Conditions

2025· article· en· W4416795056 on OpenAlex

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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueScientifica · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCassava research and cyanide
Canadian institutionsnot available
FundersUniversity of Agriculture, FaisalabadAgricultural Research ServiceHigher Education Commission, PakistanAlberta Agricultural Research InstituteU.S. Department of Agriculture
KeywordsSorghumFodderBiplotDrought toleranceCropForageBiomass (ecology)Shoot

Abstract

fetched live from OpenAlex

Sorghum ( Sorghum bicolor L.), locally known as jowar, is a vital summer fodder crop in Pakistan, significantly contributing to livestock sustenance. However, drought stress poses a critical challenge by reducing plant biomass and elevating hydrogen cyanide (HCN) content, a toxic antiquality component that endangers livestock health. This study aimed to identify sorghum genotypes with improved fodder yield and reduced HCN content under drought stress. Seventy diverse genotypes were evaluated in a hydroponic system under three polyethylene glycol (PEG) levels (0%, 5%, and 10%) in a two‐factor factorial experiment arranged in a completely randomized design (CRD). Analysis of variance (ANOVA) revealed highly significant ( p < 0.05) genotype, treatment, and genotype × treatment interaction effects across all measured traits, indicating considerable genetic variability in drought responses. Drought stress significantly increased root length (RL) (3.2–13.2 cm) and decreased several morphological traits including shoot length (SL), shoot fresh and dry weights (SFW and SDW), and chlorophyll (23.4–42.8 μg cm −2 ) and fodder quality traits including crude protein (CP) (15.4%–24.1%) and crude fiber (CF). Principal component analysis (PCA) explained 72.4% of the total variance in the first three components, identifying SDW, SFW, RL, and SL as key contributors to drought tolerance. Correlation analysis revealed significant positive and negative correlations among the traits under all normal and drought conditions. Despite these reductions, genotypes such as Sorg‐60, Sorg‐66, and Sorg‐7 showed superior performance in both biomass and quality traits, while Sorg‐53 and Sorg‐56 exhibited high sensitivity to drought. Based on PCA biplot positioning and trait performance, 20 genotypes (10 highly tolerant and 10 highly sensitive) were selected for field evaluation under normal and drought conditions using a randomized complete block design (RCBD). Morphological, physiological, and fodder quality traits showed comparatively low reduction under drought conditions in tolerant genotype compared to drought‐sensitive genotypes. Statistical analyses supported the findings and highlighted promising genotypes for use in future sorghum breeding programs aimed at enhancing forage yield and nutritional safety under water‐limited environments.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.936
Threshold uncertainty score0.235

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.083
GPT teacher head0.354
Teacher spread0.271 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it