ABSTRACT. The use of multispectral images has great potential to assess seed quality and represents a significant technological advance in the search for fast and non-destructive analysis techniques. However, the devices currently available are expensive. Thus, this study aimed to propose a low-cost method for acquisition and processing of multispectral images of soybean seeds and to evaluate their potential for rapid determination of seed physiological potential. The study was conducted in three steps: implementation of the multispectral image acquisition system, development of an algorithm for automatic image processing, and evaluation of the relationship between the data obtained through image analysis and the results of standard tests used to evaluate seed physiological potential. A total of 43 variables were assessed, eight related to seed physiological potential (germination and vigor) and 35 obtained from the analysis of the multispectral images. Of the variables obtained from multispectral images, 21 were related to pixel values in the images in the different bands evaluated (green, red, and infrared) and 14 associated with seed morphometric characteristics. The proposed system is efficient in obtaining multispectral images and the algorithm developed was efficient to extract morphometric characteristics and pixel information from the images. The parameters obtained from the NIR spectrum region showed a good relationship with the physiological potential of soybean seeds.

ABSTRACT Multitemporal collections of satellite images and their products have recently been explored in digital soil mapping. This study aimed to produce a bare soil image (BSI) for the São Paulo State (Brazil) to perform a pedometric analysis for different geographical levels. First, we assessed the potential of the BSI for predicting the surface (0.00-0.20 m) and subsurface (0.80-1.00 m) clay, iron oxides (Fe 2 O 3 ), aluminum (m%) and bases saturation (V%) contents at the state level, which are important properties for soil classification. In this task, legacy soil samples, the BSI and terrain attributes were employed in machine learning. In a second moment, we evaluated the capacity of the BSI for clustering the landscape at the regional level, comparing the predicted patterns with a legacy semi-detailed soil map from a smaller reference site. In the final stage, the predicted soil maps from the state level were investigated at the farm level considering several sites distributed across the São Paulo state. Our results demonstrated that clay and Fe 2 O 3 reached the best prediction performance for both depths at the state level, reaching a RMSE of less than 10 %, RPIQ higher than 1.6 and R 2 of at least 0.41. Additionally, the predicted landscape clusters had a significant association with the main pedological classes, subsurface color, soil mineralogy and texture from the legacy semi-detailed soil map. Illustrative examples at the farm level indicated great capacity of BSI in detecting the variations of soils, which were linked to several soil properties, such as texture, iron content, drainage network, among others. Therefore, this study demonstrates that BSI is valuable information derived from optical Earth Observation data that can contribute to the future of soil survey and mapping in Brazil (PronaSolos).

ABSTRACT Nitrogen (N) plays a key role for optimal plant growth and, in particular, for profitable crop production. Optimal N management using optical sensors can provide a rapid assessment of a crop N status. Therefore, this study aimed at comparing the efficiency of two chlorophyll meters in assessing the N status in corn plants when using an economical optimum dose of nitrogen under variable rate application. To do so, a field experiment using a randomized block design with 5 treatments and 5 replicates was carried out in Januária - Brazil (15| 28' 55" S, 44° 22' 41'' W; 474 m) in 2018. Treatments consisted of comparing the pre-fixed N fertilization system with three strategies of variable rate N application using different thresholds of the nitrogen sufficiency index (NSI) in the V4, V8, V10, and V14 vegetative stages. As a result, both chlorophyll meters were capable of detecting the need for N application and differentiating between the plants that received or did not receive N application. In addition, readings from both sensors were highly correlated (> 0.92) from the V6 to the V18 stage. Lastly, both chlorophyll meters were able to identify the crop development variability and could be a suitable tool to monitor the nutritional status and for guiding N fertilization in corn crops.

RESUMEN El nitrógeno (N) desempeña un papel clave para el crecimiento óptimo de las plantas y, en particular, para la producción rentable de cultivos. La gestión óptima de N mediante sensores ópticos puede proporcionar una evaluación rápida del estado de N de un cultivo. Por lo tanto, este estudio tuvo como objetivo comparar la eficiencia de dos medidores de clorofila en la evaluación del estado de N en las plantas de maíz cuando se utiliza una dosis óptima de nitrógeno económica bajo una aplicación de tasa variable. Para hacerlo, se realizó un experimento de campo utilizando un diseño de bloques al azar con 5 tratamientos y 5 réplicas en Januária - Brasil (15 °28 '55' 'S, 44 °22'41 '' O; 474 m) en 2018. Los tratamientos consistieron en comparar el sistema de fertilización de N preestablecido con tres estrategias de aplicación de N de velocidad variable utilizando diferentes umbrales del índice de suficiencia de nitrógeno (NSI) en las etapas vegetativas V4, V8, V10 y V14. Como resultado, ambos medidores de clorofila fueron capaces de detectar la necesidad de la aplicación de N y diferenciar entre las plantas que recibieron o no la aplicación de N. Además, las lecturas de ambos sensores estaban altamente correlacionadas (> 0,92) desde la etapa V6 a la etapa V18. Por último, ambos medidores de clorofila pudieron identificar la variabilidad del desarrollo del cultivo y podrían ser una herramienta adecuada para monitorear el estado nutricional y para guiar la fertilización con N en los cultivos de maíz.

RESUMEN Los nematodos se encuentran dentro de los principales problemas fitosanitarios del cultivo de tomate. El control químico es el método fitosanitario más utilizado por los productores y la búsqueda de medidas alternativas para su control se hacen indispensable. El objetivo de esta investigación fue evaluar el efecto del dióxido de silicio (SiO2) en el desarrollo inicial de plantas de tomate, así como determinar las mejores dosis en la inducción de resistencia al parásito M. incognita. Se estableció un diseño completamente al azar, con diez tratamientos y cinco repeticiones, en arreglo factorial 5x2, consistiendo en cinco concentraciones de SiO2 (0; 0,15; 0,3; 0,45 y 0,6 g dm-3 de suelo) y la presencia y ausencia de M. incognita, en invernadero. Se evaluaron las variables altura de la planta, número de hojas, masa fresca y seca de la parte aérea, porcentaje de materia seca de la parte aérea, masa fresca de la raíz, número de agallas, población final y por gramo de raíz de nematodos. La infección por M. incognita afectó las variables altura de las plantas, número de hojas y masa fresca de la parte aérea, mientras que la aplicación de SiO2 afectó de forma negativa la formación de ramas en las raíces de las plantas inoculadas y la población por gramo de raíz, reduciendo la población final de nematodos en el sistema radicular de las plantas. La aplicación de SiO2 también proporcionó mayor desarrollo a las plantas de tomate, presentando efecto significativo sobre la altura de las plantas, siendo 0,34 g dm-3 de SiO2 la dosis ideal.

ABSTRACT The tomato root-knot nematode is one of the main phytosanitary problems in crops. Chemical control is the phytosanitary method most used by farmers, and the study of alternative management of phytonematodes is crucial. The objective of this study was to evaluate the effect of silicon dioxide (SiO2) on the initial development of tomato plants, as well as to determine the best dose of SiO2 for inducing resistance to parasitism by M. incognita. This experiment was set up under a completely randomized design with ten treatments and five replicates in a 5x2 factorial arrangement consisting of five concentrations of SiO2 (0, 0.15, 0.3, 0.45 and 0.6 g dm-3 of soil) with the presence and absence of M. incognita, under greenhouse conditions. The following variables were evaluated: plant height; number of leaves; fresh and dry weight of shoot; percentage of shoot dry matter; root fresh weight; number of galls; final population of nematodes; and population per gram of root. The M. incognita infection affected plant height, number of leaves and shoot fresh weight, while the application of SiO2 negatively affected the formation of galls in the roots of the inoculated plants and the population per gram of root, reducing the final population of nematodes in the root system. SiO2 also provided greater development in the tomato plants, with a significant effect on plant height. The ideal dose was 0.34 g dm-3 of SiO2.