Droplets size in the phytosanitary control of potato / Tamanho da gota no controle fitossanitário de batata

The use of different spray nozzles with droplet size ranging from fine to coarse may compromise the application efficiency in potato crops. This study aimed to evaluate the production of potato in the northeast region of Mato Grosso do Sul by using different cultivars and droplet sizes in phytosanitary treatments. Potato is one of the crops that mostly depends on the application of phytosanitary products.  Potato cultivars were planted in the experimental area of the Universidade Federal de Mato Grosso do Sul, in the municipality of Chapadão do Sul. Plots consisted of three seedbeds (0.8 m x 1.4 m), and the plants were spaced at 0.35 m. The area of each experimental unit was 3.36 m2, to9taling 12 plants per unit. The experiment was carried out in subplots, in a randomized block design (2x3); the spray system had two droplets sizes (tips TT 110015 and TXA 8001VK, fine and coarse, respectively) in the plots and three potato cultivars (Yacon, Sminia, and Marcy) in the subplots, with four replications. The different droplets sizes interfere with the yield and morphology of potato tubers. The highest yield values are associated with fine droplets. Cultivar Sminia had longer tubers; however, Marcy showed thicker and wider tubers

In situ remote sensing as a strategy to predict cotton seed yield

Crop harvest scheduling and profits and losses predications require strategies that estimate crop yield. This work aimed to investigate the contribution of phenological variables using path analysis and remote sensing techniques on cotton boll yield and to generate a model using decision trees that help predict cotton boll yield. The sampling field was installed in Chapadão do Céu, in an area of 90 ha. The following phenological variables were evaluated at 30 sample points: plant height at 26, 39, 51, 68, 82, 107, 128, and 185 days after emergence (DAE); number of floral buds at 68, 81, 107, 128, and 185 DAE; number of bolls at 185 DAE; Rededge vegetation index at 23, 35, 53, 91, and 168 DAE; and cotton boll yield. The main variables that can be used to predict cotton boll yield are the number of floral buds (at 107 days after emergence) and the Rededge vegetation index (at 53 and 91 days after emergence). To obtain higher cotton boll yields, the Rededge vegetation index must be greater than 39 at 53 days after emergence, and the plant must present at least 14 floral buds at 107 days after emergence

Application technology of boron via foliar and its effects on cotton crop phenology / Tecnologia de aplicação de boron através de foliar e seus efeitos na fenologia da cultura de algodão

Boron can be applied to cotton crops together with pesticides. Producers have allied medium and fine droplets to low application rates, which can lead to low boron deposition on the leaves. This work aimed to evaluate the spray deposition and absorption of boron leaf application on a cotton crop, by varying the surfactant and the application rate, comparing the effects on the crops’ phenology and yield. Boron was applied using a backpack sprayer pressurized with CO2. Spray deposition was estimated based on the mass balance methodology. Plant leaves were collected for analysis at 17 days after application. The use and variation of the application technology affect micronutrient B absorption by leaf spray application. The application rate of 120 L ha-1 with siliconized surfactant adjuvant provides higher spray deposition on cotton plants and consequently higher boron absorption. The application rate of 70 L ha-1 without siliconized surfactant adjuvant provides lower boron absorption

Nitrogen doses in topdressing affect vegetation indices and corn yield

Nitrogen is the main nutrient required by corn crop, especially in Cerrado soils. Remote sensing techniques can be used to generate additional information now of nitrogen fertilization recommendation. This work investigated the association of plant height and dry matter phenological variables together with NDVI, REDEDGE, SAVI, and IV 760/550 vegetation indices (VIs) with corn grain yield, under different N doses. Sowing occurred in November 2016, at a spacing of 0.45 m between rows and a 60,000 ha-1 plant population. Four N doses (0, 80, 160, and 240 kg of N ha-1) were applied at phenological stage V4. The experimental design consisted of randomized blocks, containing four N doses in topdressing and 16 replications. The active optical sensor Crop Circle ACS-470 was used to obtain the VIs. The NDVI, SAVI, and RE indices have a high positive association with each other and with the variables plant height and dry matter. Polynomial regression equations were adjusted between the variables in response as doses of N. Afterwards, they were estimated as correlations between variables and results expressed through the network of correlations. Finally, a multivariate analysis of canonical variables was performed to understand the interrelationship between the variables and each dose of N applied. NDVI and RE have a positive relationship of moderate magnitude with grain yield in corn crops

Artificial neural networks for corn yield prediction and definition of site-specific crop management through soil properties

O entendimento dos fatores que influenciam a produtividade é essencial para o sucesso produtivo e para adoção de manejo diferenciado em sítios específicos. Na busca de alternativas para predizer a produtividade de grãos de milho a partir de atributos do solo, uma alternativa consiste no uso de redes neurais artificiais (RNAs). Diante disso, o presente estudo teve por objetivo avaliar a eficácia de adoção de atributos do solo por interface da análise de regressão, e das RNAs no estabelecimento de sítios de manejo diferenciado e predição da produtividade de grãos de milho, “segunda safra”, em solos de cerrado. Os dados foram obtidos em uma área de 41,76 ha, cultivada em 2010 e 2011. Apesar de demandar maior tempo de construção e processamento em relação à regressão linear, a adoção de RNAs permite melhor predição da produtividade de grãos. Em consonância ao estabelecimento de sítios específicos de manejo diferenciado do solo, a partir dos atributos teor de argila, capacidade de troca de cátions, matéria orgânica do solo e saturação de bases.The understanding of the factors influencing yield is essential for the crop success and adoption of site-specific management. The use of artificial neural networks (ANN) is an alternative of corn yield prediction from soil properties attributes. Thus, this study aimed to evaluate the effectiveness of adoption of soil properties by interface of the regression analysis, and ANNs in the establishment of site-specific management zones and prediction of corn yield, second crop in Cerrado’s soil. Data were collected in an area of 41.76 ha cropped in 2010 and 2011. The adoption of ANNs allows better corn yield prediction despite of higher demand of construction time and processing when compared to linear regression. In consonance to the soil site-specific establishment from clay content, exchange cation capacity, organic matter and base soil saturation

Liquid nitrogen fertilization on the yield and phenologic variables of narrow-row cotton

Slow-release liquid nitrogen fertilizer sources have been around since 1970. However, this technique is not widely used in the field, probably due to the low cost per ton of nitrogen in the solid form. This study aimed to evaluate the combination of the conventional and slow-release nitrogen fertilization on the yield and phenological variables in a narrow-row cotton crop. Treatments consisted of the combination of the nitrogen fertilizer applied as topdressing in solid form (via soil) and pulverized in the liquid form (via urea formaldehyde - UF): 0% of solid N + 0% of liquid N (0S0L); 100% of solid N + 0% of liquid N (100S0L); 75% of solid N + 25% of liquid N (75S25L); 50% of solid N + 50% of liquid N (50S50L); 25% of solid N + 75% of liquid N (25S75L); e 0% of solid N + 100% of liquid N (0S100L). The cotton crop was phenotypically evaluated at 35, 70, and 130 DAE (Days after emergence) and at the harvest time. The variation between the source of the solid nitrogen fertilizer applied to the soil (ammonium nitrate) and the liquid Nitrogen fertilizer applied by spraying (UF) affects the phenology, physiology, and yield components of the narrow-row cotton crop. The highest yield of the narrow-row cotton crop under the experimental conditions was achieved when 25% of the dose of the solid nitrogen fertilizer was applied as topdressing via soil, and 75% of the dose of the slow-release nitrogen fertilizer was sprayed. This technique provides higher profitability of the produced cotton in relation to the conventional application of the N solid fertilizer via soil

Relationship between vegetation indices and agronomic performance of maize varieties under different nitrogen rates

Precision agriculture is a set of techniques that assist the monitoring of the agronomic performance of the maize crop by using vegetation indices. This study aimed to verify the relationship between vegetation indices, plant height, leaf N content, and grain yield of three maize varieties, grown under high and low N as topdressing. The experiment was carried out at the Fundação de Apoio à Pesquisa Agropecuária de Chapadão (Fundação Chapadão), located in the municipality of Chapadão do Sul, during the 2017/2018 season. The experiment consisted of a randomized block design with four replications, arranged in a 3x2 split-plot scheme. The first factor (plots) corresponded to three open-pollinated maize varieties (BRS 4103, BRS Gorotuba, and SCS 154), and the second factor (subplots) consisted of two N rates applied as topdressing (80 and 160 kg- 1). All the evaluated variables showed varieties x N interaction. Vegetation indices in maize varieties were influenced by the N rate applied as topdressing. Normalized Difference Vegetation Index (NDVI) and Soil-adjusted Vegetation Index (SAVI) showed a higher correlation with plant height. At the same time, Normalized Difference Red Edge (NDRE) had a stronger association with leaf N content

Factors affecting aerial spray drift in the Brazilian Cerrado.

Pesticides aerial application may results in the drift to neighboring areas if some application technology is not well executed. This phenomenon should be minimized to reduce environmental risks and agricultural production costs. This work aimed to investigate the interaction of environmental conditions, surrounding distance, and application conditions influencing spray drift in aerial applications. Sampling data from aerial sprays were collected during three agricultural years (from 2012 to 2014) in fields cultivated with sorghum, millet, soybean, corn, and cotton. The following variables were evaluated: application swath width, application rate, distance from the applied field, wind speed, relative humidity, and temperature. The estimated Pearson's correlations and path analysis identified that application rate and distance from the applied field and application were the variables that most influenced drift. Equations relating spray drift in function of distance from the applied field and application rate were adjusted in function of the variable, and a response surface model was constructed to estimate drift. The major pesticide class sprayed with aircraft in the Brazilian Cerrado was insecticide, followed by fungicide. This scenario shows the potential hazard risk of spray drift over the environment. The concentration of the drift deposits decreased as surrounding distance and application rate were increased. A mathematical equation of drift prediction was established, where the variables that contributed most to drift deposits were surrounding distance and wind speed. Thus, it is very important to monitor and respect the wind speed limits during the aerial spraying, mainly when there is any risk potential associated with pesticide exposure over the downwind direction