How to Interpret Your Soil Test Results and Recommendations?

Neoperk Technologies
7 min readJan 21, 2025

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Sample Soil Test Report by Neoperk

Soil testing is a cornerstone of precision agriculture, enabling farmers to understand their soil’s nutrient status and make informed decisions about fertilizer application. Over the years, various recommendation and advisory methods have been developed to optimize the use of soil test results for agricultural practices. These methods aim to increase crop productivity, enhance nutrient use efficiency (NUE), and promote sustainable farming.

Today, let’s simplify these methods for you and explore different recommendation methods based on soil test results, referencing key systems and methodologies in practice.

General Fertilizer Recommendations (GFR)

The traditional approach of General Fertilizer Recommendations relies on results from multi-locational trials conducted across various soil types and environmental conditions. These trials establish an average fertilizer recommendation that is applied universally, assuming moderate or medium soil fertility levels.

While simple to implement and a good starting point for soil nutrient management, GFR lacks precision, as it doesn’t account for variability in soil fertility within regions or fields.

Limitations:

  • Over-fertilization in high-fertility soils, which wastes resources and risks environmental pollution.
  • Under-fertilization in low-fertility soils, resulting in suboptimal yields and inefficient nutrient use.
  • In regions with diverse agro-climatic conditions and soil types, GFR often fails to meet the specific needs of individual farms.

As agriculture evolves, the need for more precise, data-driven methods has become evident.

Soil Fertility Ratings and 3 / 5 / 6-Tier Systems

Different classification systems for soil fertility levels have been developed to ensure better precision in fertilizer recommendations. Let’s break down these systems:

The 3-Tier System

This method categorizes soils into three fertility levels:

  • Low Fertility: 125% or +25% of the normal recommended dose.
  • Medium Fertility: 100% of the normal recommended dose.
  • High Fertility: 75% or -25% of the normal recommended dose.

This system provides a basic yet effective approach to tailoring fertilizer recommendations based on general soil fertility status. It is particularly useful for smallholder farmers with limited access to advanced testing facilities and is widely implemented in India, including under the Soil Health Card Scheme, for macronutrient management.

The 5 / 6-Tier System

State Agricultural Universities (SAUs) play a critical role in refining these national-level limits and categories. Depending on regional agro-climatic conditions and cropping systems, some states have adopted a more nuanced classification system. For instance, states like West Bengal and Maharashtra have expanded the categorization to include five levels: very low, low, medium, high, and very high. This refinement provides a more precise understanding of soil nutrient status and is better suited for tailored soil fertility management practices.

  • Very Low Fertility: 150% or +50% of the recommended dose.
  • Low Fertility: 125% or +25% of the recommended dose.
  • Medium Low Fertility: 110% or +10% of the recommended dose.
  • Medium Fertility: 100% of the recommended dose.
  • Medium High Fertility: 90% or -10% of the recommended dose.
  • High Fertility: 75% or -25% of the recommended dose.
  • Very High Fertility: 50% or half of the recommended dose.
3-tier and 6-tier soil fertility rating systems

Challenges and Limitations:

  • Available Potassium (K): The testing methods and threshold limits for available potassium often do not align well with actual soil conditions, leading to inaccuracies.
  • Available Nitrogen (N): In many chemical labs, Organic Carbon (OC) is commonly used as a proxy for available nitrogen. However, this approach lacks a direct correlation with soil nitrogen levels, reducing its reliability.
  • Need for Micronutrient Testing: With the intensification of agriculture, micronutrient deficiencies have become a significant concern but are not fully addressed by this system.

Note that even within state, these ranges vary from district to district. For example, in Maharashtra, four major state agriculture universities (SAUs) — MPKV Rahuri, PDKV Akola, VNMKV Parbhani and BSKKV Dapoli refine these ranges based on local conditions.

Critical Limit Concept

The Critical Limit Concept determines the threshold concentration of specific nutrients in the soil, below which supplementation through fertilization is needed for optimal plant growth. If nutrient levels fall below this critical limit, plants are likely to respond positively to added fertilizers, while above it, the response becomes minimal.

Examples of Critical Limits:

  • Zinc (Zn): Below 0.6 ppm is considered deficient.
  • Boron (B): Below 0.5 ppm is considered deficient.
  • Iron (Fe): Below 4.5 ppm of DTPA-extractable iron.
  • Manganese (Mn): Below 2.0 ppm.
  • Copper (Cu): Below 0.2 ppm.
  • Molybdenum (Mo): Below 0.1 ppm.
Image Credit: ICAR-Indian Institute of Water Management

Advantages:

  • Efficient Fertilizer Use: Ensures micronutrients are applied only when and where necessary.
  • Custom Recommendations: Tailored supplementation based on actual soil deficiencies.

This concept plays a crucial role in micronutrient management, ensuring precision agriculture practices that minimize waste and promote sustainable nutrient use.

ICAR-AICRP (All India Coordinated Research Project) on Micronutrients regularly updates the critical limits for various regions and soil types based on extensive field research.

Targeted Yield Approach (STCR)

The Targeted Yield Approach (STCR) focuses on achieving a predefined yield target using soil test results and crop-specific nutrient requirements. It integrates three key parameters into a comprehensive equation:

  • Nutrient Requirement (NR): The amount of nutrient needed per unit of produce.
  • Contribution from Soil (CS): The percentage of nutrients supplied by the soil.
  • Contribution from Fertilizer (CF): The efficiency of applied fertilizer nutrients.

The formula helps optimize fertilizer application to ensure that yields stay within ±10% of the target.

Example: For rice in Raipur, Chhattisgarh:

  • FN = 3.73T — 0.55SN
  • FP2O5 = 1.45T — 5.61SP

Advantages:

  • Economic Efficiency: Ensures that fertilizer application is closely aligned with the crop’s nutrient needs.
  • Improved Yields: Helps achieve target yields with optimized fertilizer use.

Limitations:

  • Region and Crop Specific: The equations used in STCR are tailored to specific crop varieties and regions, and the necessary equations may not be available for all crops or areas, making scaling challenging.
  • Data Dependency: The effectiveness of STCR relies on accurate soil testing data, and any inaccuracies in the data can lead to suboptimal recommendations.

Despite these limitations, STCR offers a more targeted, efficient, and sustainable approach towards precision agriculture.

Decision-Support Tools (DSTs)

Modern Decision-Support Tools (DSTs) leverage technology to enhance soil test-based recommendations. These tools integrate soil data with environmental factors, providing real-time insights for better decision-making.

Key Features:

  • Integration with Weather Data: Optimizes nutrient application timing based on weather patterns.
  • Real-Time Analytics: Provides actionable insights via mobile apps.
  • Geospatial Mapping: Identifies intra-field variability for precision agriculture.

Example: In Maharashtra, DSTs are used for crops like rice and wheat, combining soil test results with Integrated Plant Nutrition Systems (IPNS) to recommend precise fertilizer applications.

Global Practices in Soil and Plant Test-Based Advisory

Globally, advanced tools and frameworks are being used to make soil test results actionable. Among the most influential concepts is the 4R Nutrient Stewardship, which emphasizes applying the Right source of nutrients, at the Right rate, at the Right time, and in the Right place. This holistic framework ensures sustainable nutrient management by aligning fertilizer use with crop needs, environmental safety, and economic viability.

Another example is NutriLOGIC, a web-based tool developed for cotton farmers in Australia which integrates soil and plant tissue test data with weather and crop growth information, providing real-time fertilizer recommendations. It has been particularly effective in optimizing nutrient management and enhancing yields, demonstrating how technology can bridge the gap between data and actionable insights.

Neoperk’s Approach

At Neoperk, we use a combination of these recommendation systems to provide our end-to-end soil testing solutions. In fact, we go a step further by integrating farmer user data to customize the recommendations. We collect essential information from farmers, such as the crop they want to grow, preferred fertilizer types (single-nutrient or mixed-nutrient), expected yield, irrigation sources, and previous crops (such as nitrogen-fixing plants). This data helps generate more accurate, practical recommendations, thus increasing adoption.

Why This Matters: Through our primary research, we learned that farmers are often hesitant to ask for help in understanding soil test reports unless they receive simple, actionable numbers. Neoperk simplifies this process through technology and ensures post-service support is available. For example, if a farmer decides to change their crop due to changing weather conditions, Neoperk’s reports can be updated without any additional costs, providing farmers with relevant advice in real-time.

Conclusion

Soil test-based recommendation systems have evolved from generalized approaches to highly sophisticated, technology-driven frameworks. Methods like the STCR and DSTs ensure precision, sustainability, and profitability for farmers. By leveraging these systems, we can achieve the dual goals of maximizing crop productivity and preserving soil health for future generations.

References:

  1. Methods Manual Soil Testing in India”, Department of Agriculture & Cooperation, Ministry of Agriculture, Government of India, 2011
  2. Computation of Fertilizer Requirement Based on Soil Test Crop Response Concept,”, Abhijit Sarkar, ARS & Partha Deb Roy, ARS Scientist, Soil Science, ICAR-Indian Institute of Water Management, Bhubaneswar -751023.
  3. Four Decades of STCR Research — Crop Wise Recommendations”, AICRP on Soil Test Crop Response Correlation, Indian Institute of Soil Science, Bhopal-462038.
  4. Approaches for Giving Fertilizer Recommendations,” Dr. P.C. Patel, Retd. Scientist, Anand Agricultural University, Anand and Guest Faculty (Professor), Parul University, Vadodara, Gujarat, India.

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Neoperk Technologies
Neoperk Technologies

Written by Neoperk Technologies

Farming agricultural insights from Soil! We are a tech start-up which leverages Advanced Spectroscopy and AI/ML to solve complex problems!

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