Herbicide application in seed maize requires special attention due to their larger sensitivity than hybrid maize. The aim of study was to examine and define the sensitivity/tolerance of the five maize inbred lines with different susceptibility to herbicides (belonging to different heterotic groups), based on alterations of secondary metabolites (phenolics, protein sulfhydryl groups, phytic and inorganic phosphorus). Two groups of herbicides: triketons (mesotrione and topramezone) and sulfonylureas (rimsulfuron and foramsulfuron) were tested. Lines from independent heterotic group, which were sensitive to herbicides expressed visible damages together with significant reduce in grain yield, mainly induced by sulfonylurea herbicides. Parallel with that, significant increase in phenolics, phytic and inorganic phosphorus, as well as drop in protein sulfhydryl groups were observed in their leaves. Tolerant lines (belonging to Lancaster group) had mainly insignificant grain yield reduce, also with lesser variations in sulfhydryl groups, content of phytic and inorganic phosphorus, as well as increase in phenolics content. Among examined secondary metabolites, phytate is the main factor, contributing to herbicide tolerance in maize lines. Owing to lesser yield decrease and variation in content of examined secondary metabolites, expressed in treatments with triketone herbicides, they usage could be safe in maize lines. [Projekat Ministarstva nauke Republike Srbije, br. TR 31068]

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SUMMARYMaize is one of the most important crops in the world. Its successful production depends mainly on meteorological factors. The aim of study was to define the most efficient tillage system (no-till, reduced or conventional tillage) and fertilizer amount (Ø, 330 or 660 kg ha -1 of N:P:K) for high maize yields (ZP 704) under rain-fed and irrigation conditions, according to the results of a longterm maize cropping experiment (1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010). The observed 20 year period was characterized by increasing trends of the average temperatures and sum of precipitation. A positive dependence between grain yield and precipitation was noticed only under rain-fed cropping. Weibull analysis emphasised that the highest yields were achieved with 330 kg ha -1 of N:P:K fertilizer and conventional tillage under unfavourable conditions. Negative meteorological factors were diminished under irrigation, where high inputs resulted in increased yields. However, rain-fed cropping is still the most abundant cropping practice in the world, and moderate inputs (330 kg ha -1 N:P:K) resulted in stability of the maize yield, regardless of the lower yields achieved. On the other hand, the high yields attained with high fertilizer and tillage inputs under irrigation could be reasonable only in seasons with low precipitation (drought).

Variations in susceptibility of maize lines to herbicides depend on different factors. Visible signs of phytotoxicity do not occur in the first few days after application when plants are tolerant to some herbicides. The aim of our experiment was to study susceptibility of 16 ZP lines to nicosulfuron and foramsulfuron 48 hours after application in the 2006-2009 period. The alterations in dry matter content, as well as thermodynamic parameters of free energy and enthalpy, were analyzed. The examined parameters show that season had a significant influence on phytotoxicity expression, with high EWRC values obtained together with high values of free energy and dry matter during the cold season with lower precipitation level (period after herbicide application). In susceptible lines, the phytotoxic effect induced an increase in dry matter and free energy. Phytotoxic effects of nicosulfuron and foramsulfuron have basically different impact on system energetic properties: the effects of nicosulfuron could be connected to greater energy consumption, and the effects of foramsulfuron to increasing potential energy, mainly from metabolism, which could be associated with a ?metabolic burst?. From that point of view, the examined parameters can be successfully used as indicators of herbicide stress immediately after application. [Projekat Ministarstva nauke Republike Srbije, br. TR-31037]

Accurate and robust state estimation is critical for autonomous navigation of robot teams. This task is especially challenging for large groups of size, weight, and power (SWAP) constrained aerial robots operating in perceptually-degraded GPS-denied environments. We can, however, actively increase the amount of perceptual information available to such robots by augmenting them with a small number of more expensive, but less resource-constrained, agents. Specifically, the latter can serve as sources of perceptual information themselves. In this paper, we study the problem of optimally positioning (and potentially navigating) a small number of more capable agents to enhance the perceptual environment for their lightweight, inexpensive, teammates that only need to rely on cameras and IMUs. We propose a numerically robust, computationally efficient approach to solve this problem via nonlinear optimization. Our method outperforms the standard approach based on the greedy algorithm, while matching the accuracy of a heuristic evolutionary scheme for global optimization at a fraction of its running time. Ultimately, we validate our solution in both photorealistic simulations and real-world experiments. In these experiments, we use lidar-based autonomous ground vehicles as the more capable agents, and vision-based aerial robots as their SWAP-constrained teammates. Our method is able to reduce drift in visual-inertial odometry by as much as 90%, and it outperforms random positioning of lidar-equipped agents by a significant margin. Furthermore, our method can be generalized to different types of robot teams with heterogeneous perception capabilities. It has a wide range of applications, such as surveying and mapping challenging dynamic environments, and enabling resilience to large-scale perturbations that can be caused by earthquakes or storms.the accuracy of a heuristic evolutionary scheme for global optimization while having a significantly lower computational demand.3) We validate our method in photorealistic simulations and real-world experiments using a robot team composed of one UAV and multiple UGVs as shown in Fig. 1. In particular, we show that our method can reduce VIO drift by as much as 90%. The rest of the paper is organized as follows. Section II summarizes the related work. Section III gives a detailed problem formulation, followed by Section IV in which we present our approach. The analysis of our algorithm is presented in Section V, and its numerical performance is showcased in Section VI. The simulation and real-world experiments in Section VII ultimately demonstrate the efficacy of our method. II. RELATED WORK A. Vision-based State EstimationVision-based state estimation has been maturing and gaining popularity during the past decade. Powerful monocular-based state estimation algorithms such as the classical structure from motion algorithm and recent state-of-the-art monocular odometry methods [3], [4] can estimate camera poses and 3D structures. However, such algorithms cannot be directly used for robo...