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Record W4413009161 · doi:10.1016/j.clwas.2025.100382

Kiwi peel waste enhances manure protein degradation: Statistical optimization using Box-Behnken design and response surface methodology

2025· article· en· W4413009161 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCleaner Waste Systems · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Waste Reduction and Sustainability
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of CanadaNewfoundland and Labrador
KeywordsBox–Behnken designResponse surface methodologyDegradation (telecommunications)ManureStatistical analysisChemistryFood sciencePulp and paper industryMathematicsChromatographyAgronomyComputer scienceBiologyEngineeringStatistics

Abstract

fetched live from OpenAlex

Anaerobic digestion (AD) of protein-rich waste is challenged by ammonia accumulation. This study explores the potential of Kiwi peel waste (KPW)-derived proteases (actinidin) to enhance manure protein degradation. It used Box–Behnken response surface design to optimize the protein quantity and ammonia reduction in batch experiments. It studied the individual and interactive effects of the manure degradation parameters (manure dosage, KPW dosage, and time). The optimal manure protein quantity reduction (39 ± 0.54 %) was obtained at manure dosages of 4 g VS L −1 , KPW dosage of 7.5 g VS L −1 , and 48 h. However, the optimum conditions for reducing ammonia by 64 ± 0.65 % are manure dosage of 9 g VS L −1 , KPW dosage of 7.5 g VS L −1 , and 48 h. A highly predictive second-order polynomial model predicted reduction consistent with those observed experimentally ( R 2 = 0.99). Change and decrease in FTIR peak intensity from 3200 to 3400 cm −1 confirmed the disturbance of hydrogen bonds and the breaking of amide or N-H bonds within side chains in the hydrolyzed manure sample. The tests characterizing the hydrolyzed substrate and the statistical model data affirm that employing KPW for manure degradation is a feasible strategy to tackle ammonia buildup. This approach can potentially enhance protein degradation in manure and increase methane yield in AD. Future studies may explore the effects of using different types of manure or other slaughterhouse waste to understand the model’s viability on various protein-rich wastes. The stability of actinidin needs to be investigated under different environmental conditions, such as temperature, pH, nutrients, etc. • Kiwi peel waste (KPW) enhances manure protein hydrolysis, reduces ammonia buildup. • A 2nd-order polynomial model accurately predicted NH 3 reductions ( R 2 = 0.99). • KPW proteases reduce manure protein by 39 ± 0.54 % and NH 3 by 64 ± 0.65 %. • FTIR confirms functional group changes in the Amide region during hydrolysis. • SEM revealed fibrils with cross-striations became smoother after 48 h hydrolysis.

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)0.002
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.606
Threshold uncertainty score0.417

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.059
GPT teacher head0.296
Teacher spread0.237 · 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