Seed Testing Methods: A Comprehensive Overview

Introduction

Quality seed is the basic and most critical agricultural input determining plant stand establishment, growth, productivity and profitability. Seed testing enables objective assessment of seed quality parameters through systematic scientific examination of seed samples in a laboratory (AOSA, 2022). It serves as an integral tool for seed certification, regulatory control, trading, variety protection and performance prediction.

Reliable seed testing provides benefits throughout the seed value chain including:

1. Enabling seed producers make improvements based on quality feedback.

2. Guiding seed processing, conditioning, packaging and labelling.

3. Supporting seed distribution, marketing and price establishment.

4. Assuring quality to farmers and minimizing crop losses and risks.

5. Settling disputes regarding seed lot standards and values.

6. Tracking origin and checking claims of varietal identity and purity.

This blog provides comprehensive coverage of all key aspects of seed testing including:

• Role and organization of seed testing laboratories

• Seed sampling considerations and procedures

• Physical purity analysis methods and interpretation

• Germination testing protocols and evaluation

• Moisture testing principles and techniques

• Other viability, vigour and health testing assays

• Quality control and precision measures

• Automation and technological advancements

• Scope for improvements in seed testing systems

Understanding seed testing concepts and procedures enables stakeholders to derive full benefits from this quality control tool that forms the gateway to high productivity through quality seed.

Organization of Seed Testing Laboratories

Seed testing involves specialized techniques and requires expert analysts trained to follow standardized international procedures prescribed by bodies like the International Seed Testing Association (ISTA, 2022) and Association of Official Seed Analysts (AOSA, 2022). Testing is performed in accredited laboratories with dedicated sections for:

1. Physical Purity Analysis: Examines the composition of seed samples to verify varietal identity and assess presence of physical contaminants and level of seed cleaning operation.

2. Moisture Testing: Determines the water content of fresh seed samples which impacts storability.

3. Germination Testing: Predicts the field emergence potential under optimum conditions.

4. Vigour Testing: Evaluates seedling growth characteristics and stress tolerance.

5. Seed Health Testing: Detects seed borne diseases that can transmit infections.

 6. Biochemical Testing: Measures viability parameters like enzyme activity, conductivity, respiration rate etc.

The laboratories maintain optimal infrastructure, equipment calibration and trained personnel adhering to precise testing protocols and quality standards. This ensures accurate, reproducible test results and data integrity. External check samples and audits validate reliability.

In India, the Central and State Seed Testing Laboratories form the national seed testing system responsible for quality assurance under the regulatory framework of the Seeds Act, 1966 and Seed Rules, 1968. The State Seed Testing Laboratories (SSTLs) are ISO 9001 certified and accredited by the National Accreditation Board for Testing Calibration Laboratories (NABL) which accredits labs under the ISO IEC 17025:2005 EC, for reliability. This basic structure is applicable to any seed testing laboratory and ISO 17025 is the primary guideline for accreditation for STLs.

Objectives and Importance of Seed Testing

The fundamental goals served by seed testing include:

1. Determining if seed samples meet prescribed quality standards for certification and truth-in-labelling (Elias and Copeland, 1997).

2. Providing information on seed viability, vigour, storage needs, dormancy, planting value and field performance expectations.

3. Detecting quality defects and probable causes to guide seed conditioning procedures.

4. Supporting quality regulation and commerce through objective data for decision making.

5. Settling disputes regarding seed lot standards and value.

6. Tracking origin and verifying varietal identity and purity claims.

7. Monitoring quality deterioration for regeneration and disposal decisions.

Reliable seed testing safeguards farmers against poor quality planting material susceptible to poor germination, delayed emergence, inadequate stands and low productivity. It prevents introduction and spread of low quality seeds and diseases to new areas. Test data supports seed distribution, pricing and trade based on transparent quality benchmarks. Seed testing is thus pivotal for seed quality assurance.

Seed Sampling and Submitting Protocols

Seed testing accuracy fundamentally relies on representative sampling. Small submitted samples are tested to predict the field performance of large seed lots. Meticulous sampling is vital as quality is seldom uniform within a seed lot and tests are sensitive to sampling errors. Key steps in seed sampling include:

1. Defining the Seed Lot

The seed lot must be physically identifiable and distinct based on uniform origin, variety, markings, container etc. Seed lot size and heterogeneity determine subsequent sampling protocols.

A seed lot, according to ISTA, is a quantity of seed of a single species and cultivar, put up under identical conditions, identified by a unique lot number or other mark, and submitted to an ISTA laboratory for a purity analysis or other test(s) listed in the International Rules for Seed Testing (ISTA Rules).

 In essence, a seed lot is a specific batch or quantity of seeds that is uniform in terms of species, cultivar, and conditions of production. It is identified by a unique lot number or marking and is subject to testing to determine its quality and adherence to the standards specified by ISTA. Seed lots are important in the seed industry to ensure consistency and quality of seeds for agricultural and horticultural purposes.

2. Collecting Primary Samples

Multiple primary samples are drawn evenly across the entire seed lot using triers or manually. Sample number, size and distribution depends on lot volume and heterogeneity. (more info)

3. Preparing Composite Sample

All primary samples are combined and thoroughly mixed to obtain a homogeneous composite sample representing the seed lot.

4. Obtaining Submitted Sample

The submitted sample of specified size for different tests is derived from the composite sample through methods like repeatedly halving/quartering or withdrawing random portions.

5. Packaging, Labelling and Submission

Submitted samples are securely packed to avoid damage or contamination in transit and accurately labeled with details like variety, lot number, test requirements, sender etc. before prompt submission to the testing laboratory.

6. Working Sample Preparation

The laboratory prepares uniform working samples from the submitted samples for conducting the various tests.

Following standardized sampling and sample reduction protocols minimizes errors and enhances test result reliability. The sample size requirements prescribed by ISTA for various crops and tests serve as international benchmarks.

Physical Purity Analysis

Physical purity refers to the percentage by weight of pure seeds of the specified kind in a seed lot along with data on contaminants like inert matter, weed seeds, other crop seeds etc. Determining sample purity is the first step in seed testing with the following workflow: (more info)

1. Drawing Working Sample

The prescribed working sample size is drawn from the submitted sample based on crop type. For large seeds like cereals and legumes, the working sample size is around 10-100 grams. For small seeds like vegetables it may be only 1-2 grams.

2. Fractionating Sample Components

The working sample is fractionated by physical separation into pure seeds, inert matter, other crop seeds, weed seeds and damaged/deteriorated seeds.

3. Weighing the Fractions

Each fractionated component is carefully weighed to determine the percentage by weight it constitutes in the working sample. Weighing is performed to the prescribed number of decimal places based on sample size for accuracy.

4. Identification of Contaminants

Seed contaminants like individual weed species and other crop seeds are identified and enumerated as their presence above threshold levels may affect field performance.

5. Calculating Percentages

Using the weights of each fraction and total sample, percentages of pure seeds and contaminants are calculated using the formula:

Percentage of component = Weight of component x 100 / Total weight of all components

6. Duplicate Tests and Tolerances

Duplicate tests are conducted on independently drawn working samples. The difference in results must fall within accepted tolerances.

Purity analysis results determine the need for seed conditioning besides verifying if statutory quality standards are met. Seed certifying agencies utilize purity data to decide on seed lot approval and labeling.

Germination Testing

Germination testing aims to predict the field emergence potential of a seed lot under favorable moisture, temperature, soil and light conditions. It estimates the percentage of seeds capable of producing normal seedlings in a laboratory test. Key steps include:

1. Drawing Working Sample

Appropriate working sample size in terms of number of seeds tested depends on seed size and shape. For large seeds like cereals and legumes, 4 replicates of 100 seeds are tested. Small seeds may require 8-16 replicates of 25-50 seeds for accuracy.

2. Equipping Replicates

The replicates are placed equidistantly on moist germination substrate like filter paper, top of sand or between paper towels. The substrate, spacing and orientation is optimized for the crop type.

3. Incubation

The replicates are incubated for a prescribed duration at optimal constant temperature, humidity and light conditions specified for the crop.

4. Evaluation

At the end of the test period, seedlings from each replicate are categorized based on visual examination as normal, abnormal, hard, fresh or dead seeds using standardized criteria prescribed by ISTA and AOSA.

5. Calculation and Expression

The number of normal seedlings in each replicate is recorded. The average of replicates gives the percentage germination which is rounded off and reported.

Tolerances limit variability between replicated tests. Results guide seed labelling and determine potential crop stand and performance expectations. Low germination indicates need for conditioning or discontinuation.

Other Viability Testing

Besides standard germination, seed viability and planting potential is assessed through tests like:

1. Tetrazolium Test: Biochemical assay based on dehydrogenase enzyme activity which produces a red stain in living tissues. Often used for rapid viability estimation and analyzing seed damage (Lakon, 1949).

2. Excised Embryo Test: Removal of embryos and evaluating their germination separately to distinguish between seed and embryo dormancy.

3. Topographical Tetrazolium Test: Enables localization of weak, damaged or dead tissues in seeds through staining patterns.

4. Radiographic Test: X-ray imaging to detect internal mechanical damage, insect damage or developmental defects affecting viability.

5. Indirect Tests: Biomarkers like electrical conductivity, respiration rate, ATP content, amylase activity, DNA/RNA quantitation used to predict viability.

While not widely utilized in routine testing, these assays provide additional tools for viability assessment and seed physiology studies.

Moisture Testing

Seed moisture content is a key determinant of processing, storage, viability and planting value. Moisture testing measures the total water percentage in a seed sample. Standard laboratory methods include:

1. Air Oven Method

A 5-10 g seed sample is dried for a prescribed duration at 103 ̊C or 130 ̊C. Moisture percentage is calculated from loss in weight after reaching constant dry weight. Widely used for high accuracy.

2. Infrared Drying Method

Here moisture is removed by direct infrared heating and quantified based on energy consumption. Fast but less precise.

3. Resistive Measurement

Electrical resistance between electrodes varies with moisture content. Portable meters based on this enable rapid estimation.

Samples are tested in duplicates or triplicates and results averaged. Tolerances of 0.2-0.5% are prescribed between duplicates. Moisture data is vital for storage, packing and labeling decisions.

Vigour Testing

Seed vigour is an indicator of rapidity, uniformity and robustness of germination, seedling emergence and growth in the field (ISTA, 2022). It is assessed through assays like:

1. Seedling Growth Tests: Evaluate germination rate, root length, shoot length and seedling mass.

2. Tetrazolium Vigour Test: Assesses tissue viability and membrane integrity.

3. Conductivity Test: Leakage of electrolytes indicates membrane deterioration.

4. Stress Tolerance Tests: Exposure to adverse conditions like cold, high temperature or moisture stress.

5. Accelerated Aging: Exposure to high temperature and humidity stresses membranes and accelerates deterioration reactions.

Vigour predicts potential field performance. High vigour enables more rapid and uniform stand establishment and better seedling growth.

Seed Health Testing

Seed health testing detects seed borne diseases that can transmit serious crop infections. It is mandatory for several vegetatively propagated crops. Different testing approaches are:

1. Blotter Method: Seeds incubated on moist blotters and observed for fungal growth. Allows detection of surface and internally seed borne fungi.

2. Agar Plate Method: Seeds plated on specific fungal culture media. Growth indicates presence of pathogens.

3. Seed Wash Test: Washing seeds in water or buffer to isolate microbial inoculum for assay.

4. Grow-Out Test: Growing seedlings and examining for disease symptoms visually or through immunoassays.

5. Molecular Methods: DNA and RNA based techniques like PCR and LAMP allow rapid, sensitive pathogen detection.

Appropriate sample size, surface sterilization, media, incubation conditions and evaluation criteria enable accurate seed health testing. Results guide seed treatment requirements.

Quality Control in Seed Testing

Several measures are mandated to assure reproducibility, minimize variability among procedures and analysts within and between laboratories:

1. Standard Operating Procedures: Documented step-by-step instructions ensure uniform protocols.

2. Harmonized Standards: Universal rules prescribed by ISTA are globally adopted.

3. Regular Personnel Training: Ensures competence in sample preparation, testing, evaluation and statistics.

4. Automated Equipment: Enhances speed, precision and minimizes analyst-based errors.

5. Calibration and Checks: Equipment calibration, periodic checks with reference standards and control samples.

6. Labeling Systems: Details like analyst, date, replicate number, equipment identification.

7. Statistical Design and Tolerances: Appropriate replication, randomization, sample size and permitted variances prescribed.

8. Quality Assurance: Accreditation, external audits, blind check samples, performance statistics analysis.

9. Digital Data Management: Integrated Laboratory Information Management System for efficient data storage, analysis and reporting.

Mandatory quality control protocols coupled with analyst training and technological tools ensure standardization, reliability and data integrity critical for seed testing.

Scope for Improvement in Seed Testing

While current practices and technology enable satisfactory performance of quality assurance functions, opportunities exist for enhancing seed testing speed, precision, sensitivity, informational value, integration and throughput. Potential advancements include:

1. Automated Smart Sampling: Real-time sensors for bulk seed lots to guide AI-driven targeted sampling and representativeness checks.

2. Hyperspectral Imaging: Detection of contaminants, defects and physiological state based on spectral signature analysis.

3. Computer Vision: Automated seedling image analysis for faster, more consistent vigor and germination evaluation.

4. Molecular Tools: DNA fingerprinting, qPCR, lateral flow strips and high-throughput sequencing for varietal ID, purity checks and disease diagnostics.

5. Spectral Phenomics: Chlorophyll fluorescence, NMR, FTIR and Raman spectroscopy for non-destructive seed quality profiling.

6. Wireless Sensors: Embedded sensor networks to monitor seed microclimate and metabolism aiding prediction of longevity and vigour.

7. Knowledge Systems: Comprehensive databases and expert systems to aid quality assessment and support decision making.

8. Blockchain Integration: Cryptographic traceability mechanisms to track seed movement, analyze trends and ensure transparency.

Advances in robotics, automation, remote sensing, information technology and genomics coupled with interdisciplinary collaboration can transform seed testing to become faster, more detailed and integrated with on-farm and on-line systems for smart seed quality management.

Conclusion

Seed testing provides the foundation for quality assurance, regulation and performance prediction in the seed supply chain. As the first link in the cycle of productivity, quality seed establishes the yield potential. Reliable seed testing safeguards farmers against risks from poor quality seed. Globally harmonized procedures, continued research on seed physiology and viability markers, automation, molecular diagnostics and IT integration can enhance the capability, information value and user access to seed testing systems. However, ensuring representative samples remains the most critical factor for seed quality testing accuracy. Integrating seed testing with certification, conditioning, storage and field monitoring can enable proactive management of seed quality factors from breeding through delivery to sustain crop productivity and food security.

References

AOSA (2022). Rules for testing seeds. Association of Official Seed Analysts. https://www.analyzeseeds.com/rules-for-testing-seeds

Elias, S.G., & Copeland, L.O. (1997). The US national seed quality system for soybean. Seed Science Research, 7(3), 255-264.

ISTA (2022). International rules for seed testing. International Seed Testing Association. https://www.seedtest.org/upload/cms/user/ISTA_Rules_2022_chapter4_sampling_MV.pdf

Lakon, G. (1949). The topographical tetrazolium method for determining the germinating capacity of seeds. Plant physiology, 24(3), 389.

More information

Additional Tests

Besides routine quality tests like purity, moisture, germination and vigor, several other laboratory and field-based tests provide valuable supplemental data:

1. Field Emergence and Survival: Planted samples monitored for emergence percentage, speed and seedling survival to predict performance.

2. Seed Aging Tests: Controlled deterioration to assess relative longevity and shelf-life potential.

3. Insect Damage Tests: X-ray imaging or embryo excision to enumerate internal feeding injuries.

4. Seed Weight: Hundred-seed weight indicates seed development and potential reserves.

5. Biochemical Tests: Enzyme activity, conductivity, respiration rate and metabolites as viability markers.

6. Pathology Tests: Grow-out, ELISA, DNA/RNA assays for specific pathogens.

7. Cytology and Imaging: Microscopy, radiography and tomography to visualize internal morphology and defects.

8. Ploidy Testing: Flow cytometry and chromosome counts to verify hybridity and purity.

9. DNA Fingerprinting: Molecular markers for varietal identity confirmation and parental verification.

10. Trait Verification: Grow-outs, chemical assays and instrumental analysis to validate special traits like oil, protein, pigments, and bioactives.

While not routine, targeted deployment of special tests provides additional useful information on seed characteristics to guide quality enhancement, conditioning, processing, storage, marketing and regulatory actions.

Automation in Seed Testing

Manual seed testing procedures are labor-intensive, slow and prone to subjective errors. Automation aims to accelerate sample throughput, improve precision and minimize drudgery. Current applications include:

1. Automatic Seed Counters: Precision dispensing of seed numbers for replicates using vibratory trays, vacuum pickups or robotics.

2. Programmable Incubators: Automated temperature, humidity, lighting and imaging systems for germination testing with data logging capabilities.

3. Seedling Evaluation Systems: Machine vision and image analysis tools for vigor and morphology assessments.

4. Near Infrared Reflectance (NIR) Sorting: Spectral detection of contaminants and foreign material for automatic separation.

5. Robotics: Robotic arms for sample transfer and handling to minimize human errors.

6. Laboratory Information Systems (LIS): Databases for test scheduling, processing, analysis and certificate generation.

7. Moisture Meters: Portable instant digital readout meters for rapid estimation.

8. Hyperspectral Imaging: Non-destructive seed quality evaluation based on spectral signature analysis.

Automation enhances the speed, precision and objectivity of seed testing besides improving working conditions for analysts. However, initial investments, technical skills and standardization efforts are needed for widespread adoption. Collaboration between engineers, data scientists and seed analysts will be key to develop practical integrated automation solutions.

In summary, standardized scientifically robust seed testing protocols, automation and quality assurance practices enable stakeholders to objectively evaluate seed lot value, make informed decisions and prevent introduction of poor quality planting material into the supply chain. Reliable seed testing thereby provides the foundation for realizing the benefits of quality seed - the vehicle to improve agricultural productivity, sustainability and food security across regions and farming systems.