SATELLITE CROP MONITORING

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During the internship, the monitoring of soybean crops was carried out, through remote sensing of vegetation index and color compositions. The practical field activities included monitoring the choice of soybean cultivars, definition of the sowing season, and management of sowing, including maintenance, adjustment of sowing machines and centrifugal distributors. After the soybean plantation, the management of pesticides was monitored, including the preparation of syrup and aerial application. Based on the studies, satellite monitoring and observations made during the internship, the choice of sowing date, in accordance with the local agricultural zoning, and the use of good crop management enable a promising crop to be obtained, with the expression of the genetic potential of the variety grown. Keywords: Production. Soybean. Management. Agronomy. 3 SUMMARY 1 INTRODUCTION 4 2 INTERNSHIP PLACE - INTEGRATED INTERDISCIPLINARY LABORATORY (LABii) 6 3 SATELLITE CROP MONITORING 7 4 CROP STAGE 2021/2022 IN THE FIELD 12 4.1 Monitoring the 2021/2022 soybean harvest 15 4.2 Choice of cultivars and sowing times 18 4.3 Maintenance and adjustment of seed drills 19 4.4 Adjusting centrifugal distributors 21 4.5 Preparing grouts and pesticide combinations 24 5 AGRICULTURAL SATELLITE MONITORING 31 6 FINAL CONSIDERATIONS 62 4. REFERENCES 63 4 1 INTRODUCTION Brazil is one of the largest grain producers in the world, with great prominence in agribusiness. According to the National Supply Company - CONAB (2021), for the 2021/22 harvest Brazil should reach a total production of 289.8 million tons of food, which represents 37 million tons more compared to the volume obtained in the previous cycle, thus reaching a new record for national agriculture. The soybean crop continues to be highlighted, for the oleaginous crop shows a tendency to increase both in cultivated area and production, with a growth trend of 14.7% in the sown area and an estimated production of 289.8 million tons, maintaining the country as the largest producer and exporter of the grain (CONAB, 2021). It is understood, in the current moment of agriculture, that with the consecutive increase in production costs, it is increasingly necessary to achieve higher yields, in a more efficient and sustainable way (BRUM et al., 2019). Within this challenge, it is necessary to establish strategies that aim to increase the revenue of each production unit, such as, for example, perform analysis by remote sensing in order to understand the crop from a laboratory analysis, without the immediate need to go to the field, reducing logistics costs, while locating points and defining management zones with greater assertiveness. The internship was subdivided into two stages, the first of which took place in the Integrated Interdisciplinary Laboratory (LABii) of the Federal University of the Pampa and the second in the Agro Byeta farm in the municipality of Buriticupu/MA. Due to the requirement to fulfill the mandatory internship, it was chosen to perform it in the area of knowledge of major crops, with a focus on soybean culture, both with regard to remote work in the laboratory and in the field. 11 Source: EOS (2019). NDVI values are between 0.2 and 0.4 for areas with sparse vegetation, while the range 0.4 and 0.6 indicates medium-sized vegetation with good distribution. NDVI values above 0.6 indicate larger amount of vegetation with good green indices. When studying NDVI and CO flux2 in soybean Rodrigues et al. (2013) found that: From V2 to V9, there was an increase in green biomass, which was accompanied by increases in NDVI values. The maximum NDVI coincided with the V9 stage, when the crop presented the maximum vegetative vigor. After the maximum, taking into account the available images, the NDVI values started to decline, which followed the evolutionary cycle and the decrease of the crop vigor, until the end of the cycle. At the point of maturity the NDVI was approximately 50% of the maximum value obtained in this study (RODRIGUES et al., 2013, p. 98100). NDVI values reach the highest indices near flowering and that some wavelengths such as yellow reflect more, in the case of plants that have yellow flowers, such as canola, for example (FIGURE 3). In this sense, the NDVI values are increased proportionally to the photosynthetic nutritional potential of the crops (EOS, 2019). 12 Figure 3 - Vegetation response in different bands and conditions a) No activity b) under stress c) healthy Source: EOS (2019). Among the limitations of the use of NDVI we highlight the saturation point, in which the increment of vegetation biomass, provided by photosynthesis, can no longer be accompanied by the increase of the index values, interference of the ionosphere, the presence of clouds the width of the spectral bands and the quality of the image obtained. In addition, the NDVI index has imitation in the study of heavily vegetated areas by the saturation of the infrared band (PINTO et al., 2014; PONZONI; SHIMABUKURO; KUPLICH, 2012). 13 4 HARVEST STAGE 2021/2022 IN THE FIELD The Agro Byeta Farm belongs to a local family, which started with the following of cattle breeding and soon after the beginning of soybean cultivation in the region, possessing a total of six thousand hectares. The farm is located in the municipality of Buriticupu/MA, on the highway MA 006, km 43, towards Arame. Agro Byeta Farm is a family business, which is managed by two brothers, one responsible for agriculture and the other for livestock. The name Agro Byeta comes in honor of his father, who had the drug Byeta as the main treatment of his health, then came the homage to his father. The farm was acquired in 2010, where is inserted in the municipality of Buriticupu/MA (FIGURE 4), which makes up the Microregion of Pindaré, which in turn is part of the Mesoregion West Maranhense. The locality is situated at coordinates 4°43'13.13'' S 46°13'11.46'' O (FIGURE 5), at 359 meters of altitude, with a typically Amazonian environment. 14 Figure 4 - Location of the internship municipality Source: Google Images (2021). Figure 5 - Map of the Agro Byeta Farm. Buriticupu/MA (2021) Source: Agro Byeta Farm (2021). With the intention of raising beef cattle, therefore the region suffers from lack of water in the period corresponding to May - November, due to low rainfall. Thus the brothers opted for innovation in the region with the start of cultivation of soybeans, which began with an area of 200 hectares, in soil considered Red Latosol, with 65% clay in its composition and an average rainfall of 1100 millimeters distributed in the months of November to May, called winter. 15 The activities developed during the internship on the property include the monitoring of professionals in the choice of cultivars and sowing season, the preparation of syrup and the combination of pesticides and the adjustment of sowing machines and centrifugal distributors. There was no monitoring of the corn crop. 4.1 Monitoring the soybean harvest 2021/2022 The monitoring of the 2021/2022 soybean crop at Agro Byeta Farm was based on the activities carried out, as shown in Table 1. Table 1Schedule of activities monitored in the 2021/2022 harvest. Year/month 2021 2022 Activities Au g set out No v ten ja n fe b sea A pr Soil preparation x x Ploughing planning x Choice of cultivars/implement regulation x Pre-sowin g Desiccation x Sowing x x Syrup preparation and inte g rated mana g ement x x Harvest x Source: Author (2022). The products used in the desiccation of the fields were Aurora (Carfentrazone-ethyl) at a dose of 0.100L/ha, 3L/ha of Zapp QI 16 (Glyphosate), 0.3L/ha of Nimbus (Mineral Adjuvant) and 1.0L/ha Assaris (Methomyl). Sowing began on 15/12/2021, using 7 CSS 2122 20-row 2018 model seeders, 0.50m spacing (FIGURE 6), and 7 JD J72230 tractors attached to them. Figure 6 - John Deere seeder, model CSS 2122, of 20 lines. Buriticupu/MA (2021). Source: Author (2021). The soy cultivars used were TMG 2383 (Maturity group 8.3), M8349 (Maturity group 8.3), M8644 (Maturity group 8.6) and BMX 8579 (Maturity group 7.9). The relative maturity groups that guide the choice of cultivars indicated for the region, which in the case of Maranhão, range from 7 to 9, 17 show good productive performance (AGRO-SOL, 2020), as shown in Figure 7. Figure 7 - Soybeans in vegetative stage. Buriticupu/MA (2021). Source: Author (2021). Relative maturity group determines the length of the crop cycle, from sowing to the soil until it reaches the R8 reproductive stage (physiological maturity), and is dependent on management conditions, conditions of adaptation to the region and the photoperiod. Cultivars produced with lower Relative Maturity Group GMR (4.0 to 7.0) are indicated for cultivation in the southern region of Brazil, while cultivars with GMR ranging from 8.0 to 10.0 are indicated for cultivation near the equator (ZANON et al., 2015). To determine fertilization the fertilization and liming manual for the states of Rio Grande do Sul and Santa Catarina was used, as instructed by COMMISSION (2016). The fertilization used was 180 kg/ha of KCL 00-00- 18 60 in pre-planting and at planting 250 kg/ha of Monoammonium Phosphate (MAP) 11-52-00, in line, at the base. For the first application of fungicide in soybean culture after 15 days of emergence, 0.200lt of Score (Triazole), 0.050lt of Target (Adjuvant) and 1.00lt of MaxOrgan (Foliar fertilizer) was used. And consequently for the second with 45 days after emergence 0.300ml of Priori xtra (Azoxystrobin and Cyproconazole) and 1.50kg of Unizeb Gold (Mancozeb). In the third application after 65 days, 0.200kg of Elatus (Azoxystrobin and Benzovindiflupir), 0.200L of Acetamiprid STK 200 (Acetamiprid) and 0.200L Piriproxifem 100 (Piriproxifem). And, in the fourth and last application, at 85 days after emergence, application of 2.50L of Cronnos (Picoxystrobin, Tebuconazole and Mancozeb), 0.400L of Match Ec (Lunefurom) and 0.250L of Engeo Pleno (Tiametoxam, LambdaCyhalothrin). The post-emergence application, for weed control, was used 2.50lt of Zapp Qi (Glyphosate) and 1.00lt of Glytrel (Manganese). These applications were carried out aerially using aircraft models Ipanema 203 and Air Tractor 502, and tractor application using JD 4630 sprayer. 4.2 Choice of cultivars and sowing times The choice of cultivar and soybean seed is one of the decisive moments in the success of the crop, because it defines the vigor and germination potential in the field. The physiological conditions combined with the favourable edaphoclimatic conditions influence the speed of emergence and the productive development of the crop. When the physiological and climatic conditions are adequate a rapid closure of the inter-row is observed. Situations such as "drought, superficial soil compaction, silting of the sowing line after heavy rains, or low soil 19 temperature during emergence" are factors that lead to production losses and can make the crop unviable (KRZYZANOWSKI; FRANÇA-NETO; HENNING, 2018). The first criterion that the person responsible must adopt is the region where the planting will take place, the type of soil and rainfall volume. From there, the best adapted variety can be chosen. Subsequently, a trustworthy seed producer is chosen for the recommendation and acquisition of the input. In selecting cultivars, varietal characteristics should be considered in the following sequence: (a) yield and stability; (b) disease resistance; (c) maturity group; (d) grain composition; and (e) height and lodging (TRAINING 24.COM, 2020). 4.3 Maintenance and adjustment of seed drills For an efficient regulation of the seed drills it is necessary that they are clean, so as not to compromise the inspection. Wear and broken parts need to be replaced (SILVA, 2013). When planting soybeans, the appropriate spacing and alignment is defined. Details such as fertilizer distribution also need to be checked, especially the transmission system (shaft rotation) to ensure uniformity in the distribution of inputs. Procedures such as washing, lubrication, replacement of hoses, polishing of metal parts tests with springs and gears need to become a routine practice soon after using the machines, because it facilitates the replacement of parts without delaying the harvest, therefore, professionals should know the content brought in the machines' manual (ROSA, 2017; COPETI, 2005). Obtaining an adequate plant population is one of the main factors in defining productivity, because of its importance in the efficiency of intercepting incident solar radiation, closely related to the sizing and calibration of the seeding machine. The plant population obtained depends 20 on the adoption of these practices applied in the establishment and management of the crop (ROSA, 2017). The Agro Byeta Farm has John Deere CS 2122 model hydraulic, articulated, vacuum seeder, indicated for work in no-till farming system. It is powered by a JD J7230, 230CV, 6-cylinder diesel (FIGURE 8). Figure 8 - John Deere CS 2122 seeder. Buriticupu/MA (2021). Source: Author (2021). The seeder has 10 lines and the spacing used for soybean is 0.50 m. Regarding its regulation for fertilization, the plain cutting disk and double disk for fertilizer are employed. Based on this regulation (FIGURE 9), it should drop 0.500 kg, using 200 kg per hectare. Figure 9 - Calibration of the seeding machine. Buriticupu/MA (2021). 27 (SEIXAS et al., 2020). As a consequence of efficient management, plants with well-developed yield components are obtained (FIGURE 14). Figure 14 - Soybean plant in R8 stage. Buriticupu/MA (2021). Source: Author (2021). The fall of the soybean leaves and the complete filling of the grains indicate the maturation point for harvesting (FIGURE 15), at which time the harvesting of the grains is carried out, maintaining the straw on the soil as a guarantee of vegetation cover, minimising the emergence of weeds and the effect of erosion (BALDOTTO; BALDOTTO, 2017). Figure 15 - Soybean crop at harvesting point. Buriticupu/MA (2021). 28 Source: Author (2021). With regard to Table 2, it can be seen that in the 20/21 harvest more than 4,000 hectares of soybeans were sown. The farm harvests an average of 65 sacks of soybeans. The plots with the highest productivity were plots 02, 04 and 10. Consequently, all are sown within the interval of dates stipulated by the ideal calendar for soybean cultivation in the Maranhão region. The variety TMG 2383, of great productive potential, has as a result of average productivity of the plots of 76.78 bags per hectare. It is also observed that in plot 14, already sown outside the ideal calendar for culture, with a larger population of plants per linear meter, productivity was already lower than the others, which shows the importance of following the technical recommendations for the culture. 29 Table 2 - Soybean crop data, Byeta farm 2020-2021 PLOTS AND TREATMENT AREA (ha) VARIETY SC/HA GM N° PLANT SEEDING HARVEST T. 01 SOYA WITHOUT STRAW 405,52 M8644 62,89 8.6 8,2 25/01/2021 15/May T. 01 SOYA TRAT. MOSAIC 120,15 M8644 68,53 8.6 8,1 25/01/2021 15/May T. 01 A - - - - - - - T. 02 SOYBEANS WITHOUT STRAW 178,13 TMG2383 76,58 8.3 11,52 13/01/2021 08/May T. 02 SOYBEANS WITHOUT STRAW 184,1 BONUS 70,96 7.9 9,65 13/01/2021 04/May T. 03 SOYBEAN TRAT. MOSAIC 77,87 M8644 61,91 8.6 8,33 26/01/2021 16/May T. 03 SOYBEANS WITHOUT STRAW 31,14 M8349 66,76 8.3 7,98 27/01/2021 12/May T. 03 SOYBEANS WITHOUT STRAW 377,08 M8644 61,3 8.6 8,5 27/01/2021 17/May T. 04 SOYA WITHOUT STRAW 544,98 TMG2383 76,31 8.3 11,59 09/01/2021 05/May T. 05 SOYBEAN WITH HAYSTACK 102,62 M8349 65,69 8.3 8,72 20/12/2020 17/Apr T. 05 SOYBEANS WITHOUT STRAW 49,85 M8349 60,21 8.3 8,13 20/12/2020 14/Apr T. 06 SOYBEAN WITH HAYSTACK 213,24 M8349 70,89 8.3 8,56 23/12/2020 18/Apr T. 06 SOYBEAN WITHOUT STRAW 111,67 M8349 62,79 8.3 8,51 20/12/2020 15/Apr T. 07 SOYBEAN WITH HAYSTACK 203,14 M8349 69,44 8.3 8,78 23/12/2020 23/Apr T. 07 SOYA WITHOUT STRAW 101,69 M8349 65,46 8.3 8,3 20/12/2020 16/Apr T. 07A SOJA 24,18 M8349 59,97 8.3 7,9 23/12/2021 23/Apr T. 08 SOYBEAN WITHOUT STRAW 541,96 BONUS 65,35 7.9 9,43 20/01/2021 29/Apr 30 T. 09 SOYBEANS WITHOUT STRAW 250,98 M8349 57,63 8.3 8,13 04/01/2021 23/Apr T. 10 SOY 247,73 TMG2383 77,46 8.3 11,36 07/01/2021 06/May T. 11 SOY 120,89 M8349 64,87 8.3 7,88 03/01/2021 27/Apr T. 12 SOY 138,75 M8349 60,07 8.3 8 04/01/2021 27/Apr T. 13 SOY 116,68 M8349 59,51 8.3 8,36 07/01/2021 28/Apr T. 14 SOY 143,52 M8349 56,02 8.3 10,73 04/02/2021 25/May TOTAL 4.285,87 Source: Byeta Farm (2021) 31 5 AGRICULTURAL SATELLITE MONITORING Agricultural satellite monitoring occurred in parallel and RGB images were analysed and NDVI values were extracted for each plot, associating the percentages of different NDVI intervals with the productivity achieved in each plot. To be clearer, Figure 16 shows the Sentinel2 satellite image in a true colour RGB composition, where the fields are numbered and with their respective areas planted with soybean cultivation on the Agro Byeta Farm. Buriticupu/MA. Figure 16 - Location of the plots and their respective areas in an RGB image of April 07, 2021 with the soybean crop implemented in the Agro Byeta Farm. Buriticupu/MA. 32 In Figure 17, one can observe an image in RGB of plot 01 of the farm with approximately 643 hectares sown on January 25, 2021. The image in NDVI, one can note NDVI values between 0.9 and 1 with 92.02% of the area; values between 0.8 and 0.9 with 5.71% of the area; and values below 0.7 represent approximately 7% of the area, which reflected in a productivity of approximately 65 bags per hectare, staying within the regional average that is precisely 65 bags per hectare. It is also noted the planting direction, which started from the left side to the right, leaving the right side with an NDVI index below the rest of the plot, characterizing a lower leaf area index. In this plot the variety M8644 was used with an initial population of 180,000 plants and a final stand of 8.1 plants per linear meter, reaching a total of 162,000 plants per hectare. 33 Figure 17 - Sentinel2 satellite image in RGB and NDVI of the soybean plot 01 in the Agro Byeta Farm. Buriticupu/MA (2021). RGB NDVI 34 Figure 18 shows an RGB image of plot 02 of the farm with approximately 364 hectares, sown on January 13, 2021. The image in NDVI (FIGURE 18), it can be noted NDVI values between 0.9 and 1 with 75.02% of the area; values between 0.8 and 0.9 with 21.44% of the area; and values below 0.7 represent approximately 3.36% of the area, which reflected in a productivity of approximately 73.77 bags per hectare, being above the regional average that is precisely 65 bags per hectare. In this plot was used the variety TMG2383, which had as initial planning a population of 240,000 plants per hectare, reaching a final stand of 11.5 plants per linear meter, reaching a total of 230,000 plants per hectare. It can also be highlighted the direction of sowing, which started from the right to the left side. 35 Figure 18 - Sentinel2 satellite image in RGB and NDVI of soybean plot 02 in the Agro Byeta Farm. Buriticupu/MA (2021) RGB NDVI 36 In Figure 19, one can observe an image in RGB of the plot 03 of the farm with approximately 597 hectares sown on January 27, 2021. The image in NDVI (FIGURE 19), it can be noted NDVI values between 0.9 and 1 with 88.6% of the area; values between 0.8 and 0.9 with 6.26% of the area; and values below 0.7 represent approximately 5.14% of the area, which reflected in a productivity of approximately 63.32 bags per hectare, being below the regional average that is precisely 65 bags per hectare. It is also noted the planting direction, which started from the left side to the right, leaving the right side with an NDVI index below the rest of the plot, characterizing a lower leaf area index. In this plot the variety M8644 was used with an initial population of 180,000 plants and a final stand of 8.1 plants per linear meter, reaching a total of 162,000 plants per hectare. Plot was sown together with TL 01, following the same direction. It can also be noted a transverse strip in the plot without vegetation cover, being the aeroplane runway. 43 Figure 22 - Sentinel2 satellite image in RGB and NDVI of the soybean plot 06 in the Agro Byeta Farm. Buriticupu/MA (2021). RGB NDVI 1. 44 In Figure 23, it can be observed an image in RGB of the plot 07 of the farm with approximately 490.17 hectares sown on 23 December 2020. The image in NDVI (FIGURE 23), it can be noted NDVI values between 0.9 and 1 with 0.02% of the area; values between 0.8 and 0.9 with 93.74% of the area; and values below 0.7 represent approximately 6.24% of the area; which reflected in a productivity of approximately 67.44 bags per hectare, being above the regional average that is precisely 65 bags per hectare. In this plot the variety M8349 was used, which had as initial planning a population of 180,000 plants per hectare, reaching a final stand of 8.7 plants per linear meter, reaching a total of 174,000 plants per hectare. This plot was the first to be sown, together with plots 05 and 06, ended up suffering water stress at the beginning of development, in which approximately 15 days occurred without rainfall in the area. It can be noted in the RGB image, some bands over the crop, which may be a possible problem of transposition at the time of application of fungicide, which ended up marking the flight direction of the plane. But did not cause any disuniformity in photosynthetic active biomass of the crop. 45 Figure 23 - Sentinel2 satellite image in RGB and NDVI of the soybean plot 07 in the Agro Byeta Farm. Buriticupu/MA (2021). RGB NDVI 2. 46 In Figure 24, one can observe an image in RGB of the plot 08 of the farm with approximately 541.96 hectares sown on January 20, 2021. The image in NDVI (FIGURE 24), it can be noted NDVI values between 0.9 and 1 with 89.25% of the area; values between 0.8 and 0.9 with 6.89% of the area; and values below 0.7 represent approximately 3.26% of the area, which reflected in a productivity of approximately 65.35 bags per hectare, staying within the regional average that is precisely 65 bags per hectare. In this plot the BMX 8579 variety was used, which had as its initial planning a population of 200,000 plants per hectare, reaching a final stand of 9.4 plants per linear meter, reaching a total of 188,000 plants per hectare. It was noted that there are some sowing faults in this plot, and also some problems such as erosion and leaching, leaving the soil bare. 47 Figure 24 - Sentinel2 satellite image in RGB and NDVI of soybean plot 08 in the Agro Byeta Farm. Buriticupu/MA (2021). RGB NDVI 48 In Figure 25, one can observe an image in RGB of the plot 09 of the farm with approximately 250.98 hectares sown on 04 January 2021. The image in NDVI (FIGURE 25), it can be noted NDVI values between 0.9 and 1 with 0.88% of the area; values between 0.8 and 0.9 with 52.79% of the area; and values below 0.7 represent approximately 46.34% of the area; which reflected in a productivity of approximately 57.63 bags per hectare, being below the regional average that is precisely 65 bags per hectare. In this plot the variety M8349 was used, which had as initial planning a population of 180,000 plants per hectare, reaching a final stand of 8.3 plants per linear meter, reaching a total of 166,000 plants per hectare. It was noted that there are some sowing failures in this plot, and also some problems such as erosion and leaching, leaving the soil bare. Through history and routine monitoring, we highlight the problem of compaction in this plot, causing low plant development. 49 Figure 25 - Sentinel2 satellite image in RGB and NDVI of the soybean plot 09 in the Agro Byeta Farm. Buriticupu/MA (2021). RGB NDVI 50 51 In Figure 26, one can observe an image in RGB of plot 10 of the farm with approximately hectares sown on 04 January 2021. The image in NDVI (FIGURE 26), it can be noted NDVI values between 0.9 and 1 with % of the area; values between 0.8 and 0.9 with 52.79% of the area; and values below 0.7 represent approximately 46.34% of the area; which reflected in a productivity of approximately 57.63 bags per hectare, being below the regional average that is precisely 65 bags per hectare. In this plot the variety TMG2383 was used, which had as initial planning a population of 240,000 plants per hectare, reaching a final stand of 11.3 plants per linear meter, reaching a total of 226,000 plants per hectare. This is the plot that generated the highest average per hectare of the farm, being a plot already with a good soil structure, high accumulation of organic matter, and allied to the health of plants. 52 Figure 26 - Sentinel2 satellite image in RGB and NDVI of soybean plot 10 in the Agro Byeta Farm. Buriticupu/MA (2021). RGB NDVI 59 Figure 29 - Sentinel2 satellite image in RGB and NDVI of soybean plot 13 in the Agro Byeta Farm. Buriticupu/MA (2021). RGB NDVI 60 In Figure 30, one can observe an RGB image of plot 14 of the farm with approximately 143.52 hectares sown on February 04, 2021. The image in NDVI (FIGURE 25), it can be noted NDVI values between 0.9 and 1 with 83.57% of the area; values between 0.8 and 0.9 with 7.57% of the area; and values below 0.7 represent approximately 8.84% of the area; which reflected in a productivity of approximately 56.02 bags per hectare, being below the regional average that is precisely 65 bags per hectare. In this plot was used the variety M8349, which had as initial planning a population of 220,000 plants per hectare, reaching a final stand of 10.7 plants per linear meter, reaching a total of 214,000 plants per hectare. This increase in the number of plants per hectare is justified by being sown outside the ideal planting window of the region, but the increase in the number of plants did not increase productivity. 61 Figure 30 - Sentinel2 satellite image in RGB and NDVI of soybean plot 14 in the Agro Byeta Farm. Buriticupu/MA (2021). RGB NDVI 62 6 CONCLUDING REMARKS The internship in the company Agro Byeta was extremely important for academic training, as it was possible to experience various situations that professionals in the field of Agronomy are subjected to, especially in the area of growing soybeans, one of the most important Brazilian commodities, which was observed the manifestation of the genetic potential of the crop, responding well to phytosanitary treatments and the choice of sowing date. During this three-month internship period, it was possible to witness the importance of the participation and presence of an Agronomist Engineer during the production cycle of a crop. With the high technification of the production system and the better use of resources, transforming them into increased productivity, the Agronomy professional shows the value of technical-scientific knowledge in management, production and agricultural development. The importance of carrying out an internship in the field is the best option to put into practice everything that was learned during academic life and to apply in the most diverse areas, including those that were not emphasized in the classroom. Therefore the main difficulties during the internship was the little theoretical and practical foundation in the culture of greater expression of the Brazilian agribusiness soybean. The internship also showed the importance of seeking updated knowledge about application technology and chemicals; as well as the regulation and choice of spray nozzles, an essential part for the realization of a good application in the field. All this knowledge was essential for the formation of a good Agronomist Engineer. Accompanying the most important crops in the national and international market, such as soybean cultivation, through the 63 internship, enriches the knowledge that will be carried throughout the professional career. 3. REFERENCES AGRO-SOL. 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