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Technique based on artificial intelligence permits automation of crop seed analysis

Publicado em 20 março 2021

In Brazil, researchers affiliated with the Center for Nuclear Energy in Agriculture (CENA) and the Luiz de Queiroz College of Agriculture (ESALQ), each a part of the University of São Paulo (USP), have developed a technique primarily based on synthetic intelligence to automate and streamline seed high quality evaluation, a course of required by legislation and at the moment achieved manually by analysts accredited with the Ministry of Agriculture.

The group used light-based expertise like that deployed in plant and cosmetics evaluation to amass photographs of the seeds. They then turned to machine studying to automate the picture interpretation course of, minimizing among the difficulties of typical strategies. For instance, for a lot of species, optical imaging expertise will be utilized to a whole batch of seeds reasonably than simply samples, as is the case at the moment. Furthermore, the method is non-invasive and doesn’t destroy the merchandise analyzed or generate residues.

The light-based strategies consisted of chlorophyll fluorescence and multispectral imaging. Among vegetation which are related as each crops and experimental fashions, the researchers selected tomatoes and carrots produced in several international locations and seasons and submitted to totally different storage situations. They used seeds of the Gaucho and Tyna business tomato varieties produced in Brazil and the US, and seeds of the Brasilia and Francine carrot varieties produced in Brazil, Italy, and Chile.

The alternative was primarily based on the financial significance of those meals crops, for which world demand is excessive and rising, and on the difficulties confronted by growers in amassing their seeds. In each tomatoes and carrots, the ripening course of is just not uniform as a result of the vegetation flower repeatedly and seed production is non-synchronous, in order that seed tons could comprise a mix of immature and mature seeds. The presence of immature seeds is just not simply detected by visible strategies, and strategies primarily based on machine imaginative and prescient can reduce this downside.

The researchers in contrast the outcomes of their non-destructive evaluation with these of conventional germination and vigor assessments, that are harmful, time-consuming, and labor-intensive. In the germination take a look at, seed analysts separate samples, sow them to germinate in favorable temperature, water, and oxygen situations, and confirm the ultimate amount of regular seedlings produced in accordance with the foundations established by the Ministry of Agriculture. Vigor assessments are complementary and extra subtle. The most typical are primarily based on the seed’s response to emphasize and seedling progress parameters.

Besides the difficulties talked about, conventional strategies are time-consuming. In the case of tomatoes and carrots, for instance, it will possibly take as much as two weeks to acquire outcomes, that are additionally largely subjective, relying on the analyst’s interpretation. “Our proposal is to automate the process as much as possible using chlorophyll fluorescence and multispectral imaging to analyze seed quality. This will avoid all the usual bottlenecks,” mentioned Clíssia Barboza da Silva, a researcher at CENA-USP and one of many authors of an article on the examine printed in Frontiers in Plant Science.

Silva is the principal investigator for the venture supported by São Paulo Research Foundation – FAPESP. The lead writer of the article is Patrícia Galletti, who performed the examine as a part of her grasp’s analysis and received the Best Poster Award in 2019 on the seventh Seed Congress of the Americas, the place she introduced partial outcomes of the venture.

Chlorophyll as a marker of high quality

Chlorophyll is current in seeds, the place it provides power for the storage of vitamins wanted for improvement (lipids, proteins, and carbohydrates). Once it has fulfilled this operate, the chlorophyll breaks down. “However, if the seed doesn’t complete the maturation process, this chlorophyll remains inside it. The less residual chlorophyll, the more advanced the maturation process and the more and higher-quality the nutrients in the seed. If there’s a lot of chlorophyll, the seed is immature and its quality is poor,” Silva mentioned.

If gentle at a particular wavelength is shone on the chlorophyll in a seed, it doesn’t switch this power to a different molecule however as an alternative re-emits the sunshine at one other wavelength, that means that it fluoresces. This fluorescence will be measured, she defined. Red gentle can be utilized to excite chlorophyll and seize the fluorescence utilizing a tool that converts it into {an electrical} sign, producing a picture comprising grey, black, and white pixels. The lighter areas correspond to larger ranges of chlorophyll, indicating that the seed is immature and unlikely to germinate.

Artificial intelligence

In multispectral imaging, LEDs (light-emitting diodes) emit gentle within the seen portion of the spectrum in addition to non-visible gentle (UV and near-infrared). To analyze seed high quality primarily based on reflectance, the researchers used 19 wavelengths and in contrast the outcomes with high quality evaluation information obtained by conventional strategies. The finest outcomes had been obtained utilizing near-infrared within the case of carrot seeds and UV within the case of tomato seeds.

Seeds comprise proteins, lipids and sugars that take up a part of the sunshine emitted by the LEDs and mirror the remaining. The mirrored gentle is captured by a multispectral digicam, and the picture captured is processed to separate the seeds from the assist within the machine, which corresponds to black pixels with zero worth, whereas the seeds are gray-scale. The values of the pixels within the picture of a seed correspond to its chemical composition.

“We don’t work with an average result for a sample. We perform individualized extraction for each seed,” Silva mentioned. “The larger the amount of a given nutrient the seed contains, the more light of a specific wavelength it absorbs so that less is reflected. A seed with a smaller nutrient content contains fewer light-absorbing molecules. This means its reflectance is higher, although this varies according to its components, which behave differently depending on the light wavelength used.”

An algorithm identifies the wavelength that obtains the perfect outcome. The course of supplies details about the seed’s chemical composition, from which its high quality will be inferred.

For the researchers, it was not sufficient to achieve the imaging stage, as that is nonetheless an operation that requires human commentary. “We then deployed chemometrics, a set of statistical and mathematical methods used to classify materials chemically,” Silva mentioned. “The idea was that the equipment should classify quality on the basis of the image it captured.” The strategies utilized by the scientists on this examine are extensively utilized in medication and the meals trade.

Next, they leveraged machine studying to check the fashions created utilizing chemometrics. “We taught the model to identify high-quality and low-quality seeds. We used 70% of our data to train the model, and used the remaining 30% for validation,” Silva mentioned. Quality classification accuracy ranged from 86% to 95% within the case of tomato seeds, and from 88% to 97% within the case of carrot seeds.

The two most important strategies had been each correct and time-saving, given the pace of picture seize. The chlorophyll fluorescence instrument captured one picture per second, whereas the multispectral imaging analyzer processed 19 photographs in 5 seconds.

Unexpected outcomes

An sudden outcome produced in the middle of the venture proved extremely essential. Chlorophyll fluorescence and multispectral imaging are additionally environment friendly strategies for plant selection screening, an important a part of seed lot analysis to keep away from financial losses. “Growers buy seeds with the expectation of a certain crop yield, but production will be affected if seeds with different genetic characteristics aren’t properly separated,” Silva mentioned.

Screening is at the moment achieved by analysts educated within the abilities wanted to grade seeds by shade, form, and dimension, in addition to molecular markers the place potential. In the examine, each strategies proved environment friendly to separate carrot varieties however multispectral imaging was unsatisfactory within the case of tomato varieties.

“The study produced novel results with regard to the use of fluorescence to screen varieties,” Silva mentioned. “We discovered no prior analysis through which fluorescence was used for this goal. Some research present multispectral imaging to be environment friendly for this goal, however not with the instrument we used.”

Instrument sharing

A great way to switch the data produced by the analysis to the productive sector, Silva mentioned, can be to have companies develop the gear on the market to seed producers. “It would be possible to use the results of our research to develop an instrument that used only UV light to characterize tomato seed quality and bring it to market, for example,” she surmised.

Study points to the challenges of harvest-time weed seed controls in Pacific Northwest

More data:
Patrícia A. Galletti et al, Integrating Optical Imaging Tools for Rapid and Non-invasive Characterization of Seed Quality: Tomato (Solanum lycopersicum L.) and Carrot (Daucus carota L.) as Study Cases, Frontiers in Plant Science (2020). DOI: 10.3389/fpls.2020.577851

Citation:
Technique primarily based on synthetic intelligence permits automation of crop seed evaluation (2021, March 19)
retrieved 19 March 2021
from https://phys.org/news/2021-03-technique-based-artificial-intelligence-automation.html

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