Soil Health Analytics Using Microbial Composition
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Solution Overview
Problem
It is challenging to determine the impact of microbe species in soil on crop yield and disease pressure, and to predict whether a field will produce high or low crop yields and whether crops will develop diseases.
Innovation Solution
An analytics system that uses soil health indicators to determine metrics for soil samples by receiving metadata, determining nucleic acid sequence reads, and calculating microbial composition and reference metrics to provide insights on crop performance and disease susceptibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional soil analysis methods are used, then the analysis process is simple, but the ability to predict crop yield and disease pressure is insufficient
Solution Approach 1:
The patent replaces traditional mechanical/chemical soil analysis methods with metagenomic sequencing technology. Instead of using conventional laboratory techniques to analyze soil composition, the system uses DNA sequencing to profile the microbial community, enabling precise prediction of crop yield and disease pressure through biological data rather than chemical analysis.
Solution Approach 2:
The patent introduces metagenomic sequencing as an intermediary between soil sampling and prediction. The sequencing technology serves as a mediator that transforms complex microbial community structures into readable genetic data, which then feeds into predictive models. This intermediary layer enables the transition from raw soil samples to actionable agricultural insights.
2Measurement precision
If metagenomic sequencing is used to profile the microbiome, then prediction accuracy improves, but the difficulty of determining microbe species impact increases
Solution Approach 1:
The patent segments the complex task of determining microbe species impact into manageable components. Instead of attempting to assess all microbial interactions simultaneously, the system divides the microbiome into taxonomic groups and functional categories, analyzing each segment separately through metagenomic sequencing data. This segmentation makes the complex measurement task tractable and interpretable.
Solution Approach 2:
The patent focuses on measuring specific aspects of the microbiome that are most relevant to crop yield and disease prediction, rather than attempting to characterize every microbe species completely. By concentrating sequencing efforts on key functional genes and taxonomic markers, the system achieves sufficient measurement precision for agricultural prediction without the excessive complexity of complete microbial characterization.
3Reliability
If comprehensive microbial composition analysis is performed, then soil health indicators are improved, but the time and resources required increase
Solution Approach 1:
The patent performs preliminary action by preparing metagenomic sequencing libraries and conducting initial quality control assessments before full-scale sequencing. This preliminary processing ensures that samples are properly prepared and that sequencing will yield reliable soil health indicators, while also identifying samples that may need reprocessing, thereby optimizing overall analysis time and resource utilization.
Data Source
AI summary
An analytics system uses soil health indicators to determine metrics for soil samples. In an embodiment, the analytics system receives metadata describing a soil sample, where the metadata indicates one or more types of crops grown in a geographical location having the soil sample. The analytics system determines nucleic acid sequence reads of the soil sample. The analytics system determines taxonomic information of the nucleic acid sequence reads. The analytics system determines microbial composition of the soil sample using the taxonomic information. The analytics system determines reference metrics of soil samples from geographical locations in which the one or more types of crop were grown. The analytics system determines a metric of the soil sample using the microbial composition and the reference metrics. The analytics system transmits the metric to a client device.