ABSTRACT Vegetation indices are a quick and practical alternative for monitoring crops due to the availability of satellite images on various platforms for free, allowing a quick analysis of the vegetative state of the crop and interventions in the field in case of signs of diseases and pests. In this context, this study aimed to evaluate the vegetative state of the coffee crop using vegetation indices (NDVI, SAVI, ARVI, EVI, and VDVI) in an agricultural year. The study was carried out on a commercial farm using satellite images from the Planet platform, during an agricultural coffee growing season (2021/2022). The indices selected for the study were the Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), Atmospherically Resistant Vegetation Index (ARVI), Enhanced Vegetation Index (EVI), and Visible Difference Vegetation Index (VDVI). The index data were analyzed using descriptive statistics, Pearson correlation, classification/interpretation proposal, and the Kappa index. NDVI and SAVI are efficient in monitoring coffee cultivation in an agricultural year, as the Kappa index was higher than 90%. ARVI and EVI had Kappa index values close to 90% and can be used to monitor the crop. VDVI was inefficient, with a low Kappa index value when compared to the others. The proposed classification for vegetation indices based on NDVI classes and values consisted of an important tool for classifying and interpreting the values of these indices, assisting monitoring and management of coffee cultivation.

ABSTRACT Sugarcane requires planning aimed at maintaining production levels, technological quality, and longevity of the sugarcane field, as it is a semi-perennial crop. To this end, the adoption of soil management systems associated with the maintenance of remaining straw are some of the strategies aimed at protecting the soil structure and its properties vital to the sustainability of agricultural systems. In this context, this study aimed to evaluate the influence of soil management systems and remaining straw with and without ratoon chiseling on the optimum water range (OWR) and load-bearing capacity (LBC) of the soil. The experimental design consisted of randomized blocks in a split-plot scheme, with four replications. The plots were composed of no-tillage and conventional tillage, the subplots consisted of three levels of remaining straw (0, 50, and 100%), and the sub-subplots consisted of the use or not of chiseling. Samples with preserved structures were collected at depths of 0.05 and 0.15 m for the analysis of the physical indicators OWR and LBC. Maintaining 100% straw associated with the use of chiseling resulted in an increase in OWR in both soil management systems and depths. Maintaining straw at 50 and 100% also led to lower LBC values in the evaluated soil management systems and depths, suggesting an improvement in soil physical quality. The use of chiseling of ratoons in conventional tillage promoted higher LBC values, indicating possible additional soil compaction in these areas.

ABSTRACT The area cultivated with sugarcane in Mato Grosso do Sul, Brazil, has increased significantly in recent years, in which to meet the demand of the mills, the use of adapted varieties has proved to be a fundamental strategy, combined with the use of irrigation, especially in periods of water deficit. The study aimed to evaluate the growth and yield of four sugarcane varieties (CTC 4, RB966928, RB975201, and RB92579) in plant cane cultivated with and without irrigation. The experiment was conducted at Embrapa Western Agriculture (Embrapa Agropecuária Oeste) in Dourados, MS, Brazil. A randomized block design arranged in a 2 x 4 factorial scheme with three replications was used. At 90, 150, 210, 270, 330, and 390 days after planting (DAP), stalk height and diameter, leaf area index (LAI), and dry biomass were evaluated. The soil cover percentage (%SC) was determined through aerial images taken with a drone, with evaluations made from planting to the maximum soil cover. Total recoverable sugar (TRS), number of stalks m-1, stalk (STY), and sugar (SGY) yield were evaluated at 390 DAP (harvest). The RB975201 variety has the highest growth in height, stem diameter, and LAI when grown under irrigation or without irrigation, and the CTC 4 variety has the smallest. The irrigated production system increases the growth of stalks, LAI, and degree of soil cover for the sugarcane varieties in plant cane and a greater amount of stems m-1, STY, and SGY, highlighting the varieties RB92579 and RB975201.

RESUMO A área cultivada com cana-de-açúcar em Mato Grosso do Sul, Brasil tem aumentado significativamente nos últimos anos, em que para atender à demanda das usinas o uso de variedades adaptadas tem se mostrado estratégia fundamental, aliado ao uso da irrigação, sobretudo em períodos de déficit hídrico. Objetivou-se avaliar o crescimento e a produção de quatro variedades de cana-deaçúcar (CTC 4, RB966928, RB975201, RB92579), em cana-planta, cultivadas sob irrigação e sequeiro. O experimento foi conduzido na Embrapa Agropecuária Oeste, em Dourados, MS, Brasil em um delineamento em blocos ao acaso, em esquema fatorial 2 x 4, com três repetições. Aos 90, 150, 210, 270, 330 e 390 dias após o plantio (DAP) avaliou-se a altura e o diâmetro de colmos, o índice de área foliar (LAI) e a biomassa seca. O percentual de cobertura do solo (% SC) foi determinado, através de imagens aéreas tomadas com drone, com avaliações feitas desde o plantio até a máxima cobertura do solo. O açúcar total recuperável (TRS), o número de colmos m-1, a produtividade de colmos (TSH) e de açúcar (TUH) foram avaliados aos 390 DAP (colheita). A variedade RB975201 apresenta maior crescimento em altura, diâmetro de colmo e LAI quando cultivada em sequeiro ou irrigação, a variedade CTC4, o menor. O sistema produtivo irrigado proporciona aumento no crescimento de colmos, LAI e grau de cobertura do solo para as variedades de cana-deaçúcar, em cana-planta, assim como maior quantidade de colmos m-1, TSH e TUH, destacando-se as variedades RB92579 e RB975201.

ABSTRACT Bean is among the most consumed and produced crops in Brazil. Given the high demand for food, the search for technologies and controllers to increase the efficiency of agricultural systems has grown. This study aimed to model artificial neural network (ANN) architectures to predict mechanical efficiencies in the semi-mechanized bean harvest. We used a multilayer perceptron network with three inputs (harvest moisture, threshing rotor rotation, and feed rate), two hidden layers of neurons, and one output (efficiency). We evaluated the efficiency in the header, separation on the threshing rotor, cleaning of sieves, and the total efficiency of the machine. ANN was processed by a scripted algorithm to model the network, alternate the number of neurons in hidden layers, as well as to select, test, and validate ANN with less error. ANN was validated by comparing its results with the experimental data. The architectures selected to predict efficiencies were 3-8-15-1 for the header, 3-9-7-1 for the thresher and separation, 3-5-11-1 for cleaning, and 3-15-10-1 for the total operation. ANN predicted satisfactory results with errors below 1% and a high hit rate, thus being valid to predict the efficiencies in the semi-mechanized bean harvest.

ABSTRACT Machinery traffic intensification has been recurrent in intensive agriculture in annual crops, which may lead to structural soil degradation and, consequently, a reduction of its productive capacity. Therefore, this study aimed to assess the influence of tractor traffic intensification on soil physical attributes and soybean yield components. The study was performed in an Oxisol under no-tillage for 10 years, using a randomized block design with five tractor traffic intensities (0, 2, 4, 6, 8, and 12 passes) and five replications. Density, porosity, macroporosity, microporosity, and penetration resistance were assessed in the soil and stem diameter, number of pods per plant, number of grains per pod, grain weight per plant, thousand-grain weight, and grain yield were assessed in the soybean crop. Tractor traffic intensification changed soil physical attributes, which were not limiting factors to soybean yield under the no-tillage system, providing higher stem diameter, number of pods per plant, grain weight per plant, and grain yield after 12 passes.

ABSTRACT Seed metering system and tractor-seeder forward speed are factors that affect sowing. Therefore, this study aimed to evaluate sowing and agronomic components of corn as a function of seed metering mechanism and tractor-seeder forward speed, in addition to evaluating the yield data obtained from a harvester with a yield monitor. The soil of the area is classified as Distroferric Red Latosol. The experiment was set up in the second crop season of 2018 and treatments consisted of two seed metering mechanisms (M) (pneumatic and mechanical), and tractor-seeder forward speeds (S) (3, 5, 7, and 9 km h−1). The pneumatic system promoted the best longitudinal distribution, with values above 90%, and the increased sowing forward speed reduced normal spacings and increased failure. The interaction M × S indicated that pneumatic seeder promotes the best stand at the highest forward speed, normal spacing, and less failure. The yield data showed less variation with increasing forward speed, and the best result was observed for the mechanical seeder at 5 km h−1 when these data are grouped into yield classes.

ABSTRACT The inadequate agricultural management in the semiarid region of northeastern Brazil, associated with the fragility of most soils, has caused degradation of the quality of this resource. This study aimed to evaluate the quality of Quartzipsamments under different uses through the multivariate analysis of chemical and physical attributes. Five areas were selected: four of them with agricultural use (onion, banana, cassava, and corn) and the other with Caatinga. Soil samples were collected at depths of 0.00–0.10, 0.10–0.20, and 0.20–0.40 m for chemical and physical analyses. The data were submitted to descriptive analysis and then to the multivariate analysis using the principal component analysis (PCA) technique and Ward’s clustering method. PCA and clustering techniques allowed the identification of different production systems in subsurface layers, suggesting the effect of fertility on the differentiation of areas with onion and banana, as well as the clustering of cassava and corn cultivations. Physical attributes and sodium content of the surface layer of the area with onion showed a tendency of compaction and salinization process of this environment. In general, fertility was the main responsible for the improvement of soil quality with agricultural use when compared to the Caatinga.

ABSTRACT Machine traffic and conventional tillage can cause structural degradation of the soil, affecting the physical attributes and, consequently, the production and longevity of the sugarcane field. The objective of this study was to evaluate the production components of sugarcane cultivars (RB965902, RB985476, RB966928, RB855156, RB975201, RB975242, RB036066 and RB855536) and physical attributes of a Dystroferric Red Latosol (Oxisol) under no-tillage and reduced-tillage systems. The experiment was conducted using a completely randomized experimental design in an 8 × 2 factorial arrangement, with four replicates. The soil attributes evaluated were density, total porosity, macroporosity, microporosity and penetration resistance. The production components evaluated were stalk length and diameter, number of tillers (NT), tons of cane per hectare (TCH), sucrose content (Pol), tons of sucrose per hectare (TPH), soluble solids content (Brix), total recoverable sugars (TRS) and plant fiber. Cultivars RB965902, RB966928, RB855156 and RB985476 have productivity and technological attributes that are superior to the other cultivars, whereas these are lower for RB036066 in both soil tillage systems. Cultivars RB966928, RB855156, RB975242 and RB855536 exhibited higher TCH and TPH in the no-tillage system, and all cultivars displayed equal or higher performances than those observed in the reduced-tillage system. In the no-tillage system, which exhibits lower penetration resistance values between wheel tracks and in the subsurface layer of the planting row (0.20–0.40 m), cultivars RB985476 and RB975242 had a higher NT, and RB855156 had higher stalk lengths and NT.

ABSTRACT In areas of no tillage system where there is intense traffic of machines and minimal soil mobilization, the periodic monitoring allied on localized soil compaction represent important strategies aiming agricultural sustainability. Thus, the objective of this study was to evaluate the spatial variability of soil resistance to penetration (RP) in no tillage system. Data collection took place in an experimental area of 7.65 ha using a sample grid composed of 40 points. At each point the RP was determined by three replications from which was obtained the mean RP, the maximum RP, and the depth of the maximum RP in the 0-0.40m layer. Deformed samples were randomly collected in the area to determine the water content in the soil (θ). Then the RP data were analyzed using descriptive and geostatistical statistics techniques for spatial variability maps. The RP presents spatial variability detected by means of spherical semivariogram in all soil layers. There was spatial variability in the area with the appearance of intermediate values for RP (2.00-3.00 MPa) due to no ploughing and continuous traffic of agricultural machines. There were greater reaches and critical levels of compaction on the layers 0.10-0.20 and 0.20-0.30 m where there is predominance of the maximum RP.

ABSTRACT The performance of the tractor-seeder can be influenced by factors related to the seeder, as loads and crop. The aim of the present study was to evaluate the performance of tractor-seeder at sowing in the corn crop in function of the fertilizer systems (at presowing and at sowing) and those intercropping of crops (corn + bean-Stizolobium deeringianum, corn + bean-Cajanus cajan and corn + bean-Dolichos lab lab). The experiment was carried out at FCAV-UNESP with totally randomized delineation, on factorial scheme (2x3) with four repetitions. The use of fertilization during the pre-sowing resulted in greater displacement speed and effective field capacity in the corn sowing operation, without changing the distribution of corn seeds; however, it demanded more power and volumetric and weight hourly consumption of the tractor fuel.

Com o advento da mecanização agrícola e o uso intensivo de máquinas e implementos agrícolas nas propriedades, o solo passou a receber maior carga do tráfego de máquinas, o que pode causar aumento da compactação do solo. O objetivo do trabalho foi avaliar a variabilidade espacial da resistência mecânica do solo à penetração (RP), nas camadas de 0,00-0,10; 0,10-0,20; 0,20-0,30 e 0,30-0,40 m, por meio da geoestatística, em área cultivada com manga, em Vertissolo Háplico do semiárido nordestino, com unidade móvel equipada com penetrômetro eletrônico. A coleta de dados de RP foi realizada em 56 pontos de uma área de 3 ha, sendo tomadas também amostras aleatórias para a determinação da umidade e da textura do solo. Para a análise dos dados de RP, utilizou-se da estatística descritiva e da geoestatística. A resistência mecânica do solo à penetração apresentou variabilidade elevada, sendo ajustado o semivariograma esférico e exponencial nas camadas. Verificou-se que 42% da área na camada de 0,10-0,20 m apresentou valores de RP acima de 2,70 MPa. Foram encontrados valores máximos de RP, na camada de 0,19-0,27 m, predominante em 56% da área.

Since the advent of mechanized farming and intensive use of agricultural machinery and implements on the properties, the soil began to receive greater load of machinery traffic, which can cause increased soil compaction. The aim of this study was to evaluate the spatial variability of soil mechanical resistance to penetration (RP) in the layers of 0.00-0.10, 0.10-0.20, 0.20-0.30 and 0.30-0.40m, using geostatistics in an area cultivated with mango in Haplic Vertisol of the northeastern semi-arid, with mobile unit equipped with electronic penetrometer. The RP data was collected in 56 points from an area of 3 ha, and random soil samples were collected to determine the soil moisture and texture. For RP data analysis we used descriptive statistics and geostatistics. The soil mechanical resistance to penetration presented increased variability, with adjustment of the spherical and exponential semivariograms in the layers. We found that 42% of the area in the layer of 0.10-0.20m showed RP values above 2.70 MPa. Maximum values of RP were found in the layer of 0.19-0.27m, predominantly in 56% of the area.