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Record W2319742893 · doi:10.1021/jf403245c

Characterizations of Structural, Biochemical, and Nutritive Profiles in Silage among Cool-Season Corn Cultivars in Relation to Heat Units (aCHU, dCHU) with Curvilinear Response and Multivariate Analyses

2013· article· en· W2319742893 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Soil, Plant Science
Canadian institutionsUniversity of Saskatchewan
FundersNational Science Council
KeywordsSilageCultivarMultivariate statisticsAgronomyCurvilinear coordinatesBiologyChemistryMathematics

Abstract

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Molecular spectroscopy is able to reveal structural features of biomaterials. Corn grown in Canadian prairies is known as cool-season corn, which is different from warm-season corn varieties. To our knowledge, to date, there has been no study on the magnitude difference in structure on a molecular basis among cultivars, no study on biochemical and nutritive profiles associated with heat unit, and no study on how heat unit affects the molecular structure and biochemical and nutritive profiles. This study investigates how corn varieties grown in cooler climates are affected by crop heat units (CHU) in relation to molecular spectral profiles, nutrient storage, biochemical composition, and nutritive value of silage among different cool-season corn cultivars. Corn cultivars (Pioneer and Dekalb) were from seven farm locations, and samples were analyzed for major nutrients (digestible and metabolic energy and protein). The Fourier transform infrared (FT/IR) spectroscopic technique was applied to understand and differentiate molecular structural spectral profiles in silage. A correlation (P < 0.05) of CHU with some nutrients (mean ± SD, %DM) (CP, 8.1 ± 1.3, r = 0.56; NDF, 56.3 ± 3.5, r = -0.54; ADF, 33.6 ± 2.3, r = -0.71; NDICP, 1.6 ± 0.4, r = -0.66; SCP, 4.2 ± 1.3, r = 0.61), protein and carbohydrate fractions (mean ± SD, %DM) (PB1 (= fast degradable protein fraction), 1.3 ± 0.4, r = 0.54; PB3 (= slowly degradable protein fraction), 1.5 ± 0.4, r = -0.74; CB2 (= medium degradable carbohydrate fraction), 45.1 ± 2.8, r = -0.65; CB3 (= slowly degradable carbohydrate fraction), 13.9 ± 0.9, r = -0.54) and intestinal availability of ruminally degraded fractions (mean ± SD, %DM) (rdPB1, 1.1 ± 0.3, r = 0.54; rdPB3, 1.0 ± 0.3, r = -0.74; RDP, 6.6 ± 1.2, r = 0.59; rdCB2, 40.0 ± 2.5, r = -0.65; rdCB3, 8.9 ± 0.6, r = 0.54; RDCHO, 50.1 ± 2.9, r = -0.65) was found contentious. Molecular spectral data indicated many similarities and few differences among the cultivars. However, CHU correlated (r = -0.4, P < 0.05) with molecular spectral intensity ratio of carbohydrate to amide I. This result indicates that molecular structural differences may be influenced by epiphytic bacterial compounds. Cool corn cultivars were grown acceptably well in cooler dry climates, and those silages had acceptable nutrient levels for cattle. Cultivars that reached target CHU were found to be optimal in nutrient and energy synchronization aspect.

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 score0.737
Threshold uncertainty score0.279

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.018
GPT teacher head0.228
Teacher spread0.210 · 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