The present invention relates to a method for selecting a seed intended for sowing. The method comprises subjecting a seed to germination conditions and selecting a seed that has germinated as a seed intended for sowing. As a result, only seeds which are likely to develop into a commercially interesting plant need to be sown and grown into plants.

A seed imaging system for imaging seeds includes a seed transfer station configured to move seeds through the system. An imaging assembly includes a first camera mounted relative to the seed transfer station and configured to acquire images of the seeds as the seeds move through the system. A second camera is mounted relative to the seed transfer station and is configured to acquire images of the seeds as the seeds move through the system. The second camera has an imaging modality different from an imaging modality of the first camera. First and second cameras may be disposed above and below the seed transfer stations, such as a transparent belt.

The present invention discloses a CIELAB color space-based quantitative testing and analysis method for rice seed viability, and the method comprises removing husks on surfaces of rice seeds, soaking and imbibing the rice seeds without the husks removed, staining the rice seeds by using a TTC staining solution, and longitudinally cutting the rice seeds along embryos; converting the longitudinal section image of the rice seed from an RGB color space to a CIELAB color space, and calculating L value, a value and b value per unit area of the rice embryo as a staining intensity per unit area, and converting the staining intensity into a rice seed viability score according to a pre-established conversion model of the staining intensity and the rice seed viability score. According to the present invention, a reference result can be provided for the rapid, accurate and objective evaluation of the seed viability.

Methods for preserving viability of plant tissues such as plant embryos are provided herein. Also included are methods for storing genomic DNA and/or molecular marker assay materials in an oil bilayer as part of a high-throughput molecular characterization system. Moreover, plant embryos may be treated while in an oil matrix. The treatment may include chromosome doubling, Agrobacterium-mediated transformation, or herbicide selection as part of an embryo rescue process.

An automated system for sampling seeds generally includes an automated sampling station having a sampler configured to remove material from a seed while protecting germination viability of the seed, a seed conveyor configured to receive the seed from out of the sampling station after the material is removed from the seed, and a sample conveyor configured to receive the material removed from the seed. The sample conveyor is configured to locate the material removed from the seed in a sample container, and the seed conveyor is configured to locate the seed from which the material is removed in a seed container so as to facilitate a one-to-one correspondence between the seed and the material removed from the seed.

An automated system for sampling seeds generally includes an automated sampling station having a sampler configured to remove material from a seed while protecting germination viability of the seed, a seed conveyor configured to receive the seed from out of the sampling station after the material is removed from the seed, and a sample conveyor configured to receive the material removed from the seed. The sample conveyor is configured to locate the material removed from the seed in a sample container, and the seed conveyor is configured to locate the seed from which the material is removed in a seed container so as to facilitate a one-to-one correspondence between the seed and the material removed from the seed.

A method for breaking dormancy of Thesium chinense Turcz. seeds, which includes: immersing collected seeds of Thesium chinense Turcz. in water, selecting seeds that sink in the water followed by air-drying, and storing at 2-4? C. to obtain to-be-used seeds; immersing the to-be-used seeds in a gibberellin solution, taking out the seeds and mixing with river sand under ?4-2? C. for a first stratification treatment; rinsing off the river sand, removing green skins and stalks of the seeds after the first stratification treatment, keeping the seeds moist and placing the seeds under 2-4? C. for a second stratification treatment to obtain ruptured seeds; and using the ruptured seeds in a three-slit stage as a germination material, and culturing the ruptured seeds in a three-slit stage in a dark environment at 17-22? C. for seed germination. The method can significantly improve the germination rate of Thesium chinense Turcz. seeds.

Provided herein are systems and methods for the automation of seed planting and analysis comprising automated planting of the seeds, germination, and analysis. The methods generally comprise conveying containers containing seeds to an automated seed planting station, wherein each container includes a machine-readable tag, planting at least some of the seeds in the container onto respective planting trays, wherein each planting tray includes a machine-readable tag, allowing the seeds to germinate, and analyzing the germinated seeds. The systems generally comprise a seed planting system and a planting verification and correction system. Also provided herein are backlit templates comprising a light source and a power interface configured to connect to a power source to power the light source.

The present invention provides methods for testing seed germination and predicting seed emergence in stressful field conditions, such as cold and flooding stress. Cold Soak Test and ultra-drying methods are provided herein. The methods find use in the development of corn breeding technologies and germplasm selection to evaluate and develop new hybrids that can produce stable stands under stressful field conditions.

An information processing device that can easily predict the seed quality is provided. An information processing device includes an information acquiring unit configured to acquire, as seed management information about a seed to be predicted, a state of a plant for seed collection from which the seed is collected, and a state of the seed; and a generation processing unit configured to generate seed quality information for the seed to be predicted, by inputting the seed management information acquired by the information acquiring unit into a learning model that has been taught, through machine learning, a correlation between the seed management information about a seed being a training object and the seed quality information indicating quality related to germination or maturity of the seed.