EN 
PT_BR 
Scientists from Embrapa Maize and Sorghum (MG) and the company Spectral Solutions have developed a portable method for evaluating the chemical composition of ground maize and sorghum grains. The technology uses NIR spectroscopy, based on infrared light, which, in addition to not destroying the samples, reduces process costs while ensuring safety, hygiene, and efficiency. The portable analysis model uses MicroNIR, a device similar in size to a pen, and can be installed for reading directly on cell phones, tablets, or other devices via Bluetooth.
The system utilizes miniaturized sensors that maintain precision in a compact format, enabling rapid, real-time analysis without the need for chemical reagents. This facilitates decision-making in the field, warehouse, or industry. The Portable NIR Analysis System is the result of combining Embrapa's chemical and agronomic knowledge, along with its database of corn and sorghum cultivars, with the hardware and software technology of the partner company.
“The goal was to create robust calibration models that considered the diversity of climate, soil, and different corn and sorghum cultivars planted in Brazil, ensuring that the equipment functions accurately in any region of the country,” reports Embrapa Corn and Sorghum researcher Maria Lúcia Simeone.
The development of this technique was motivated by the need to overcome the limitations of traditional laboratory methods, which are slower, more expensive, and often destructive. "The agricultural sector needed a solution capable of guaranteeing the nutritional quality of the grain, based on protein, oil, and starch content, instantly, to improve storage and processing," says Simeone.
Analytical precision and validation
The Portable NIR System is available for analyzing milled grains. “The analytical models were built this way to ensure greater analytical precision. They have been validated to measure elements such as protein, oil, crude fiber, mineral matter, starch, and moisture,” highlights Luiz Felipe Aquino, CEO of Spectral Solution.
Basically, the tool creates a digital fingerprint, where infrared light shines on the ground grain and the molecular bonds absorb energy in specific ways, generating a unique spectrum for each sample. “Then what we call multivariate calibration occurs, which translates these light signals into percentage values of protein, moisture, and other grain quality data. Because this spectrum is complex, mathematical and statistical models are used, composed of multivariate calibration algorithms or deep learning,” adds Simeone.
“The methodology used demonstrated equivalence with official methods, which allowed us to validate the asset as a real alternative to wet chemistry. There was no statistically significant difference between the results using the models obtained with the Portable NIR System and the reference methods of the Association of Official Analytical Chemists (AOAC),” adds Aquino.
The technology employs the concepts of "Green Chemistry" and sustainable agriculture for several reasons that positively impact the sustainability of the production chain and the environment. "Unlike conventional chemical analyses, NIR works with zero residue, meaning it does not use chemical reagents or toxic solvents," describes the executive director.
He further emphasizes that the model promotes energy efficiency by reducing the transportation of samples to distant laboratories and streamlining industrial processes, saving energy. "In addition, it reduces waste because it allows for the early identification of substandard batches, preventing low-quality products from spoiling or contaminating larger processes," he notes.
Benefits in the field
The prospects for using the equipment are clear. Researcher Simeone states that the system promotes crop optimization and contributes to deciding the best time to harvest, based on actual maturity in terms of moisture and starch values, or the possibility of segregating grains with higher protein value for niche markets.
“Furthermore, sample preparation is minimal. It only requires grinding the grains, making the operation simple for farm employees after a short training session. In economic terms, the return on investment will come from savings on external laboratory fees, reduced reagent use, monitoring of grain quality, and, most importantly, the gain in negotiating batches with proven quality on the spot,” he adds.
The expectation is that adopting the system will promote agility in classifying batches, as trucks will spend less time waiting for the results of physicochemical analyses, improve adjustments in formulating animal diets when sorghum and corn are destined for silage and feed, and increase trust between buyer and seller.
