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title: "Understanding yield differences through soil microbiome analysis – Case Study – Biomcare"
description: "A field trial designed to evaluate the effect of a new product in organic maize production showed highly variable yield responses across different sections of the field. While some areas performed well, others delivered lower yields, making it important to understand whether these differences reflected variation in soil biology, field conditions, or how the product interacted with the existing soil system."
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3.  Yield Differences & Soil Microbiome 

Agriculture & Environment

# Understanding yield differences through soil microbiome analysis

Client:  European Manufacturer of soil amendment 

Services used: 

Soil Microbiome Analysis

Bioinformatics & Statistics

Study & Trial Support

Interpretation & Decision Reports

## Problem

A field trial designed to evaluate the effect of a new product in organic maize production showed highly variable yield responses across different sections of the field. While some areas performed well, others delivered lower yields, making it important to understand whether these differences reflected variation in soil biology, field conditions, or how the product interacted with the existing soil system.

## Question

Can differences in the soil biology explain the yield differences between high-yield and low-yield areas of the field?

## What we did

Soil samples were collected from each plot in the field trial and analysed using microbiome sequencing. The resulting data underwent extensive bioinformatic processing to generate profiles of both the taxonomic composition and the functional capacity of the soil microbial communities. Biomcare integrated the microbiome data with information on treatment, yield, and other measured soil properties. Statistical analyses were then used to identify microbial differences associated with crop performance and to explore whether biological patterns could help explain why yield responses differed across the field.

## Insight

The analysis identified specific microbial species associated with higher yield across both treated and untreated plots, indicating that underlying differences in soil biology were linked to crop performance. When the functional microbiome data was explored in more detail, microbial functions related to the product's expected mode of action differed between high- and low-yielding areas within the treated part of the field. This helped provide a more biologically informed interpretation of the field trial results.

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