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Technique based on artificial intelligence permits automation of crop seed analysis

Publicado em 19 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 half of the University of São Paulo (USP), have developed a technique based on artificial intelligence to automate and streamline seed high quality analysis, a course of required by regulation and presently executed manually by analysts accredited with the Ministry of Agriculture.

The group used light-based expertise like that deployed in plant and cosmetics analysis to amass photos of the seeds. They then turned to machine studying to automate the picture interpretation course of, minimizing some of the difficulties of typical strategies. For instance, for a lot of species, optical imaging expertise will be utilized to a complete batch of seeds somewhat than simply samples, as is the case presently. 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 nations 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 selection was based on the financial significance of these meals crops, for which world demand is excessive and rising, and on the difficulties confronted by growers in gathering their seeds. In each tomatoes and carrots, the ripening course of isn’t uniform as a result of the vegetation flower repeatedly and seed manufacturing is non-synchronous, in order that seed heaps might comprise a combination of immature and mature seeds. The presence of immature seeds isn’t simply detected by visible strategies, and strategies based on machine imaginative and prescient can decrease this downside.

The researchers in contrast the outcomes of their non-destructive analysis with these of conventional germination and vigor checks, that are damaging, 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 checks are complementary and extra subtle. The most typical are based on the seed’s response to emphasize and seedling development parameters.

Besides the difficulties talked about, conventional strategies are time-consuming. In the case of tomatoes and carrots, for instance, it might probably 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,” stated Clíssia Barboza da Silva, a researcher at CENA-USP and one of the authors of an article on the research revealed in Frontiers in Plant Science.

Silva is the principal investigator for the challenge supported by São Paulo Research Foundation – FAPESP. The lead creator of the article is Patrícia Galletti, who carried out the research as half of her grasp’s analysis and received the Best Poster Award in 2019 on the seventh Seed Congress of the Americas, the place she offered partial outcomes of the challenge.

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 stated.

If mild at a selected wavelength is shone on the chlorophyll in a seed, it doesn’t switch this power to a different molecule however as a substitute re-emits the sunshine at one other wavelength, which means that it fluoresces. This fluorescence will be measured, she defined. Red mild 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 mild within the seen portion of the spectrum in addition to non-visible mild (UV and near-infrared). To analyze seed high quality based on reflectance, the researchers used 19 wavelengths and in contrast the outcomes with high quality evaluation knowledge obtained by conventional strategies. The finest outcomes have 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 soak up half of the sunshine emitted by the LEDs and mirror the remaining. The mirrored mild is captured by a multispectral digital camera, and the picture captured is processed to separate the seeds from the help within the system, 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 stated. “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 most effective end result. 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 remark. “We then deployed chemometrics, a set of statistical and mathematical methods used to classify materials chemically,” Silva stated. “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 research are extensively utilized in medication and the meals business.

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 stated. 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 foremost strategies have been each correct and time-saving, given the velocity of picture seize. The chlorophyll fluorescence instrument captured one picture per second, whereas the multispectral imaging analyzer processed 19 photos in 5 seconds.

Unexpected outcomes

An surprising end result produced within the course of the challenge proved extremely necessary. Chlorophyll fluorescence and multispectral imaging are additionally environment friendly strategies for plant selection screening, a necessary half 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 stated.

Screening is presently executed by analysts educated within the abilities wanted to grade seeds by coloration, form, and dimension, in addition to molecular markers the place attainable. In the research, 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 stated. “We found no prior research in which fluorescence was used for this purpose. Some studies show multispectral imaging to be efficient for this purpose, but not with the instrument we used.”

Instrument sharing

A great way to switch the data produced by the analysis to the productive sector, Silva stated, could be to have corporations 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.


Technique based on artificial intelligence permits automation of crop seed analysis (2021, March 19)

retrieved 19 March 2021


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