Biomass and nitrogen accumulation in white oat (Avena sativa L.) under water deficit 1 Knowledge on nitrogen absorption rate by crops can indicate important managements, especially the definition of rates of this nutrient and the best time for topdressing application. This study aimed to evaluate and compare the accumulation of biomass and nitrogen in white oat cultivated under severe, moderate and no water deficit. Treatments consisted of levels of irrigation, with four repetitions. The treatments under severe water deficit (L1), moderate deficit (L3) and no deficit (L5) received 11%, 60% and 100% of the water volume evapotranspired by the crop (ETc). For each treatment, six plants were collected in each replicate. After collection, plants were separated into leaves, culm and reproductive structures (panicle + grains). Second and third order regressions were tested to model the behavior of biomass and nitrogen accumulation in white oat leaves, culms, reproductive structures and total over time. The maximum total nitrogen accumulation in white oat plants in the treatments L1, L3 and L5 was 50 kg ha-1 , 163 kg ha-1 and 246 kg ha-1 , respectively. Severe water deficit drastically reduced biomass and nitrogen accumulation in white oat. Severe water deficit causes earlier peak of biomass and nitrogen accumulation, reduces nitrogen accumulation rate and shortens cycle of white oats.

The increase of N fertilization in sugarcane can negatively influence the technological quality of the crop for sugar and alcohol production. The use of Mo in fertilization combined with N can reduce this effect and increase agricultural and sugar yield. The objective of this study was to evaluate the levels of Mo in soil, roots and leaves of sugarcane fertilized with N and Mo, to measure agricultural and sugar productivity and to evaluate quality of the technological attributes for production of sugar and alcohol. Two varieties were cultivated (RB867515 and RB92579) under field conditions, submitted to two doses of N (0 and 60 kg ha-1) and two doses of Mo (0 and 200 g ha-1) both applied to the soil. The source of N used was urea and the source of Mo was sodium molybdate. RB867515 was influenced by Mo and agricultural and sugar productivity increased by 21%. N fertilization did not increase agricultural productivity but reduced the technological quality of sugarcane, and Mo did not change this reduction. It is suggested that N fertilization should be reduced in first crop cycle and Mo fertilization should be stimulated.

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The use of remote sensing in agriculture presents some practical applications in crop production forecast. In this context, studies with remote sensing are scarce for crops such as white oats, which may indicate the capacity of using this technique in the crop. The aim of this study was to evaluate the accuracy in validation of white oat biomass and grain yield estimates by spectral models previously calibrated using two vegetation indices (NDVI and IRVI) at three phenological stages. The mean values of NDVI and IRVI were correlated with the grain and biomass yield of white oats to obtain regression equations. The accuracy was verified by the determination coefficient (R 2 ), root mean square error (RMSE) and mean bias error (MBE). The models were calibrated using data from a field experiment carried out in 2017 and validated with data from the same experiment, but conducted in 2018. The models had good generalization capacity for estimating yield of white oats, especially for biomass yield. Parametrized models in more advanced phenological stages, showed lower error of estimation. Models calibrated with the vegetation index IRVI had lower error of estimation than when calibrated with NDVI.

Additions of poultry manure can promote improvements in the conditioning of the biological, physical and chemical properties of the soil. Thus, the present study aimed to evaluate soil chemical attributes through the superficial application of linear doses of chicken litter. The experimental design was a randomized block design, with 4 replicates and 7 treatments: T1: Witness (without application of avian bed), T2: 1 Mg ha potassium content in the analyzed soil. The doses of aviary bed alter the total organic carbon content. It can be said that higher doses of avian bed result in higher values of phosphorus and calcium. The calcium contents were higher than the magnesium content, potential acidity (H + + Al 3+ ) and Sulfur had a similar behavior to that of Calcium and Magnesium, a negative quadratic behavior. The values for pH measured did not vary greatly in relation to the doses of poultry bed applied and from the statistical data it was possible to determine that only pH CaCl2 had a significant difference. All other chemical attributes analyzed were not significantly influenced by the addition of the organic fertilizer when compared to the control, regardless of the application form in the soil.

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Remote sensing techniques have been considered a new technology in worldwide agriculture for diagnosing the plant nutritional demand. Fertilizer management efficiency is a goal to be achieved, and modern tools based on remote sensing are promising for monitoring the crop needs. This study aimed to evaluate the agronomic performance and relative economic return of white oat under nitrogen rates, as well as to verify whether the normalized difference vegetation index (NDVI) and leaf chlorophyll index (LCI) could be used for topdressing nitrogen fertilization management, in white oat. Treatments consisted of five topdressing nitrogen fertilization strategies: T1 - 160 kg ha-1 (reference rate); T2 - 90 kg ha-1 (recommended rate); T3 - 60 kg ha-1 (economic rate); T4 - 30 kg ha-1 (when NDVI < 90 % of T1); and T5 - 30 kg ha-1 (when LCI < 90 % of T1). The white oat did not respond to the topdressing nitrogen fertilization. Its temporal monitoring using spectral indices allowed dispensing the topdressing nitrogen fertilization without reducing the grain and biomass yields and the leaf nitrogen content, when compared to the recommended management (90 kg ha-1 of N as topdressing), with no differences between the evaluated spectral indices. Thus, both the NDVI and LCI spectral indices are promising tools for the topdressing nitrogen fertilization management in the white oat crop.