ABSTRACT Leaf chemical analysis is one of the ways to assess plant development. However, this type of assessment is expensive and time-consuming. The variation of nutrient content in the leaves modifies the proportion of light reflected and absorbed by plants at different wavelengths. Being able to relate the color reflected by the leaves with their phosphorus (P) content and using this data as input into an artificial neural network (ANN) can be an alternative for its determination. For this, it is necessary to establish which colors are most correlated with the different nutrients. Therefore, the phosphorus content in tomato leaves was evaluated in this study, according to four treatments (0.25, 50, 75, and 100% of the P doses). Different vegetation indices were also evaluated using images of mini-tomato leaves through a principal component analysis to determine which ones would be suitable to serve as an input to an ANN (multilayer perceptron). DGCI (Dark Green Color Index) and Bn (Normalized Blue) were the indices most related to P content. The neural network obtained 90% accuracy in the classification after training using both sides of the leaves.

ABSTRACT Lowland rice is traditionally irrigated by flood systems, demanding high water consumption. Localized irrigation by subsurface dripping is proposed as an alternative, in addition to the replacement of the source of water intended for human consumption with another of lower quality, such as saline water. However, plants can be affected by saline and/or water stress in both conditions, and the use of thermal imaging emerges as a tool to assess the plant status. In this context, this study aimed to identify the stress of subsurface drip-irrigated arborio rice under different salt concentrations and soil moisture by thermographic images. The design consisted of randomized blocks in a (2×4)+2 factorial with three replications, totaling 30 experimental plots. Soil solution salinity was assessed by electrical conductivity. The thermal images were processed by an algorithm to determine the normalized relative canopy temperature (NRCT) index at different crop development stages. Saline stress was identified by the NRCT index, with higher sensitivity of plants at the flowering stage with a rebalance over time, confirmed at grain filling and harvest stages.

ABSTRACT: This study was conducted to evaluate the nutritional status of table beet plants cultivated in a greenhouse irrigated with treated dairy effluent at different irrigation depths. The experimental design used was a randomized block in a 3 x 3 + 1 factorial arrangement with four replications and conducted in a greenhouse. The treatments consisted of three types of water sources and three irrigation depths applied by drip irrigation: anaerobic effluent; anaerobic/aerobic effluent; tap water, and irrigation for replenishment 50; 100 and 150% of the crop evapotranspiration (ETc). All these treatments were applied in combination with 50% of the recommended nitrogen fertilization for the table beet cultivation. A control treatment was irrigated with tap water with irrigation depth equal to 100% ETc and received the complete dose (100%) of mineral nitrogen fertilizer. Table beet seedlings were arranged in 40 fiberglass boxes with a base area of 1 m2. Table beets were harvested 72 days after transplanting (DAT) when the leaves and roots were analyzed. Irrigation with wastewater promoted appropriate levels of macronutrients, distributed between the leaves and roots. The sodium was increased significantly in the leaves and roots of table beets in effluent treatments at increasing irrigation depths, which was antagonistic to the absorption of potassium.

ABSTRACT: Phytoremediation is a technique that uses plants to decontaminate soils containing harmful organic and inorganic elements. The aim of this study was to evaluate the potential of three species of forage green manure in phytoremediation of saline soil irrigated with treated effluent from dairy processing plant. The design used was randomized blocks (3×3) with four replicates. The treatments were three different water sources (anaerobic treated effluent, aerobic treated effluent, and tap water) applied to growing table beets combined with the post-cultivation of three forage green manure: Calopogonium mucunoides Desv (Calopo), Cajanus cajan (L.) Millsp (Pigeon pea), and Pennisetum glaucum (L.) R. Brown (Millet). The treatment with Millet had higher dry mass production with all water sources, although showing growth reduction after irrigation with anaerobic treated effluent. Millet presented higher sodium extraction efficiency (22.4 kg ha−1); however, it was not effective in soil phytoremediation because the exchangeable sodium percentage was not reduced to levels that allowed for new effluent input.