Vermicompost Quality from Three Feedstock Blends: A Physico-Chemical and Germination-Index Study

What this study does. Vermicomposting turns campus and household organic waste into a marketable organic manure, and earthworm-processed compost is recommended by agricultural universities across Karnataka. But not every feedstock produces compost of equal quality: what goes in decides the nutrient content, stability and phytotoxicity of what comes out. This project runs a controlled, replicated vermicomposting trial that answers one question with numbers: does the feedstock blend measurably change the quality of vermicompost?

A two-member team operates nine 40-litre bins (three feedstock treatments × three replicates), each seeded with the same biomass of the epigeic earthworm Eisenia fetida. The three treatments are the blends a campus unit actually handles: (T1) cattle dung + paddy straw, (T2) cattle dung + garden leaf litter, (T3) cattle dung + vegetable-market waste. Over ten weeks the team logs temperature, moisture and appearance weekly, then analyses the finished compost for pH, electrical conductivity, moisture, total organic carbon (Walkley–Black method), total nitrogen (Kjeldahl method) and the C:N ratio, plus earthworm population and biomass change.

Quality is benchmarked in two independent ways: against the Schedule IV specifications for packaged vermicompost under the Fertiliser (Control) Order, 1985 (for example, organic carbon ≥ 14 %, C:N < 20, moisture ≤ 25 %), and by a germination-index bioassay — tomato seeds grown in compost extract against a water control — which detects phytotoxic compounds. One-way ANOVA with Tukey's HSD in Python decides which differences between treatments are real, so every claim is backed by a test statistic, not an impression.

Colleges, market committees and urban local bodies generate large quantities of paddy straw, leaf litter and vegetable-market waste, most of which is burnt or landfilled. Vermicomposting is repeatedly recommended as the remedy, and units are being set up, but extension material rarely answers the practical question a unit operator faces first: which locally available blend of waste should be fed to the worms to get compost of the highest quality? Published nutrient ranges for vermicompost are broad, unreplicated and not tied to feedstock, and most student-level comparisons rely on visual judgement — colour and smell — rather than measurement.

There is also a safety question that visual judgement cannot answer: immature or unstable compost carries phytotoxic compounds (ammonia, organic acids) that inhibit seed germination and can burn seedlings. Without a germination bioassay, poor compost can be sold or applied to nurseries unchecked.

This project therefore runs a randomised, replicated comparison of three feedstock blends under identical worm density, moisture and temperature conditions, measures the finished compost with standard analytical methods, tests phytotoxicity with a germination-index bioassay, and judges each blend against the Fertiliser (Control) Order Schedule IV specifications, so that the recommendation at the end is quantitative, statistically defensible and directly usable by a real vermicompost unit.

Abstract

This project compares vermicompost from three feedstock blends — cattle dung with paddy straw (T1), leaf litter (T2) and vegetable-market waste (T3) — in a randomised, replicated bin trial over ten weeks, followed by laboratory analysis and a seed bioassay. Physico-chemical parameters (pH, EC, moisture, organic carbon, total nitrogen, C:N), earthworm population change and the tomato-seed germination index are compared across treatments with one-way ANOVA and Tukey's HSD, and the best blend is benchmarked against the FCO Schedule IV specifications for packaged vermicompost.

Introduction

India generates enormous quantities of crop residue, leaf litter and market waste, and burning or dumping them creates pollution that vermicomposting can convert into a resource; Karnataka's universities promote units at colleges, KVKs and ward-level centres. A unit, however, is only as good as its feedstock: the C:N ratio of the input drives decomposition speed, product nitrogen and worm survival. The TNAU Agritech Portal's protocol prescribes pre-digestion with cattle-dung slurry, moisture around 60 % and seeding with Eisenia fetida — but not which local blend gives the best product.

Existing knowledge and the gap

Published extension material gives how to run a vermicompost unit and quotes wide nutrient ranges — organic carbon 9.5–17.98 %, nitrogen 0.5–1.5 % — without tying them to specific blends, and most student projects stop at "the compost looked black and crumbly". The gap this project fills is controlled comparison with statistics: equal worm biomass, equal starting weights, replicate bins, defined sampling days, and an analysis plan that separates real differences from bin-to-bin noise. It also adds two tests rarely seen in student reports: a germination-index bioassay (adapted from the classical compost-toxicity test of Zucconi and co-workers) that detects phytotoxic ammonia and organic acids, and a regulatory benchmark against FCO Schedule IV so the result is expressed in the units a fertiliser dealer would quote.

Proposed study

1. Build nine 40-litre bins (three treatments × three replicates) on the college vermicompost unit, randomised in position to equalise shade and drainage.
2. Pre-digest each feedstock for 15 days with cattle-dung slurry, then start with a fixed wet mass (10 kg) per bin and a fixed worm density; log temperature and moisture weekly for ten weeks.
3. Harvest, air-dry, sieve (4 mm), and analyse: pH and EC (1:10 suspension), moisture (oven), organic carbon (Walkley–Black), total nitrogen (Kjeldahl), C:N, earthworm counts and biomass.
4. Germination-index bioassay with tomato seeds in 10 % extract versus distilled water, three dishes of ten seeds per replicate.
5. One-way ANOVA and Tukey's HSD per parameter; correlation between feedstock C:N and product nitrogen; benchmark against FCO Schedule IV.

Feasibility

• Technical: the trial needs only bins, worms, a pH/EC meter, an oven, a balance and the chemistry lab for titrations.
• Economic: worms, tomato seeds and reagents cost well under ₹1,500; the finished compost can be sold to the college garden.
• Operational: ten weeks of composting fits a 14-week semester if bins start in Week 2.

In scope

• Three feedstock blends built around cattle dung (paddy straw, garden leaf litter, vegetable-market waste) composted with Eisenia fetida in 40-litre bins for ten weeks.
• Physico-chemical analysis of the finished compost: pH, EC, moisture, organic carbon, total nitrogen, C:N ratio; earthworm population and biomass change.
• Germination-index bioassay with tomato seeds at one extract concentration (10 % w/v).
• Statistical comparison by one-way ANOVA + Tukey's HSD, and benchmarking against FCO Schedule IV specifications.

Out of scope

• Micronutrients, heavy metals and pathogen counts (coliforms, Salmonella) — these need instruments the college lab does not have; listed under future scope.
• Continuous monitoring of gas emissions or carbon-nitrogen dynamics during composting.
• Cost-of-production modelling for a commercial unit (a business plan is a different project).
• Field response trials of the compost on crops.

Research design: a completely randomised design (CRD) laboratory-and-field study with one factor (feedstock blend, 3 levels) and three replicates per level, followed by laboratory analysis and a bioassay. The response variables are analysed with one-way ANOVA; the treatment effect is reported with F and p values and Tukey's HSD separates pairs.

Treatments (each bin starts with 10 kg wet pre-digested feedstock + 250 g Eisenia fetida, mixed species biomass excluded):

• T1: cattle dung + paddy straw, 1:1 by weight (shredded to 2–3 cm)
• T2: cattle dung + garden leaf litter, 1:1 by weight
• T3: cattle dung + vegetable-market waste, 1:1 by weight (drained)

All feedstocks are pre-digested for 15 days with cattle-dung slurry (following the TNAU protocol) to avoid heat damage to worms, and moisture is maintained at 60–70 % by sprinkling.

Weekly observations (Weeks 3–12): bin temperature (probe thermometer at 5 cm depth), ambient temperature, moisture (gravimetric sub-sample weekly), colour/odour stage notes, worm escape counts.

End-of-trial analysis (Week 13): harvest, air-dry in shade, sieve through 4 mm; pH and EC in a 1:10 compost–water suspension; moisture by oven-drying at 105 °C to constant weight; organic carbon by Walkley–Black rapid titration (recovery factor 1.32 applied); total nitrogen by Kjeldahl digestion–distillation and titration; C:N computed; worm counts and wet biomass per bin at harvest.

Germination index (Week 13–14): 10 g compost + 100 ml distilled water, shaken 1 h, filtered; 5 ml extract on filter paper in Petri dishes with 10 tomato seeds, 3 dishes per replicate bin, 5 days at room temperature. GI = (germination % × mean root length, as % of water control)/100.

Analysis plan: normality (Shapiro–Wilk) and equal-variance (Levene) checks, one-way ANOVA per parameter, Tukey's HSD where ANOVA is significant, Pearson correlation between feedstock C:N and product N, all in Python (pandas, SciPy) with α = 0.05; every table is cross-checked once in Excel.

Timeline (14 weeks, team of two): Weeks 1–2 design, bin construction, feedstock collection and pre-digestion; Weeks 3–12 weekly monitoring (alternating duty); Week 12–13 harvest and lab analysis (Member A: pH/EC/moisture/OC; Member B: Kjeldahl N, worms, bioassay); Week 14 statistics, report, slides and viva preparation.

The study is organised as a linear pipeline from feedstock to recommendation, with a parallel statistics and benchmarking stage. Each stage produces a numbered log-sheet or CSV so the report can reproduce every table.

flowchart TD
  A["Collect feedstocks: dung, paddy straw, leaf litter, market waste"] --> B["Pre-digest 15 days with dung slurry (TNAU protocol)"]
  B --> C["Fill 9 bins: T1 straw, T2 litter, T3 market waste x 3 replicates"]
  C --> D["Seed 250 g Eisenia fetida per bin, randomised placement"]
  D --> E["Weekly log: temperature, moisture, stage notes, worm escapes"]
  E --> F["Week 12-13: harvest, shade-dry, sieve 4 mm"]
  F --> G["Physico-chemical lab: pH, EC, moisture, Walkley-Black OC, Kjeldahl N"]
  F --> H["Bioassay: tomato germination index, 10 pct extract vs control"]
  F --> I["Worm counts and biomass per bin"]
  G --> J["Python: ANOVA, Tukey HSD, correlations"]
  H --> J
  I --> J
  J --> K["Benchmark vs FCO Schedule IV specifications"]
  K --> L["Report, slides and recommendation to the college unit"]

Data organisation

Each bin has an identity (treatment, replicate), and every measurement carries the bin ID and date, stored in one tidy CSV per parameter — weekly_monitoring.csv, compost_chemistry.csv, worm_counts.csv, germination_index.csv. The analysis script joins them on bin ID, so a re-measurement only needs one row corrected, not the whole table rebuilt. Empty result tables are provided in the bundle in the exact format the report needs; no numbers are pre-filled, because the numbers must come from the team's own run.

Quality control

• Titration blanks are run with every Walkley–Black and Kjeldahl batch.
• One bin per treatment is analysed in duplicate to check repeatability of the lab methods.
• The compost chemistry of each replicate is measured from a composite sample (four subsamples per bin mixed), which is standard practice for heterogeneous material.
• The statistics script prints the raw per-bin values, so outliers can be traced back to a physical cause (bin disturbed, leak, moisture crash) before any data point is excluded — and an excluded point is reported as excluded, never silently dropped.

• Heavy-metal and pathogen testing of the finished compost (with a partner laboratory) to complete the FCO quality picture.
• Continuous parameter logging with a low-cost temperature–moisture datalogger to model decomposition kinetics rather than weekly snapshots.
• Enrichment trials: vermicompost fortified with biofertilisers (Azotobacter, PSB) and its effect on shelf life and microbial counts.
• Field response trial: the winning blend tested on a real crop (ragi or tomato) with yield and soil-organic-carbon responses over a season.
• Second cycle feeding — re-composting the sieve rejects and studying worm population dynamics over successive cycles.
• A unit cost model comparing feedstock options for a ward-level processing centre.