Gábor Milics

Use of mesotrione and tembotrione herbicides for post-emergence weed control in alkaloid poppy (Papaver somniferum)

Two field experiments were carried out a year apart on the alkaloid poppy (Papaver somniferum) in 2012 and 2013 in north-west Hungary, to assess the efficacy of mesotrione and tembotrione herbicides for post-emergence weed control. Our experiments tested (1) a single application of mesotrione at 144 g active ingredient (a.i.) ha–1, (2) two separate applications of mesotrione at 144 g a.i. ha–1, (3) a single application of tembotrione at 88 g a.i. ha–1, (4) two separate applications of mesotrione at 88 g a.i. ha–1, and (5) the combination of a single application of mesotrione at 144 g a.i. ha–1 followed by a single application of tembotrione at 88 g a.i. ha–1. Both non-treated and hand-weeded plots were used as controls. Among the most important weeds, Chenopodium album was most successfully controlled in the majority of the test treatments, but Fallopia convolvulus and Polygonum aviculare tolerated each herbicide application in 2012, likely due to the dry weather conditions. Because of the botanical similarity to the crop, none of the treatments proved to be significant against Papaver rhoeas. One dosage of tembotrione alone never reduced the dry weights of the target weed species or weed numbers significantly. The cuticular wax layer of the opium poppy can provide a natural defence against these herbicides, but some temporary phytotoxic yellowish discoloration occurred after tembotrione treatments. Our results show that mesotrione in combination with tembotrione is the most effective treatment and should be employed in poppy cultivation.

Continuous field soil moisture content mapping by means of apparent electrical conductivity (ECa) measurement

Abstract A soil moisture content map is important for providing information about the distribution of moisture in a given area. Moisture content directly influences agricultural yield thus it is crucial to have accurate and reliable information about moisture distribution and content in the field. Since soil is a porous medium modified generalized Archie’s equation provides the basic formula to calculate moisture content data based on measured ECa. In this study we aimed to find a more accurate and cost effective method for measuring moisture content than manual field sampling. Locations of 25 sampling points were chosen from our research field as a reference. We assumed that soil moisture content could be calculated by measuring apparent electrical conductivity (ECa) using the Veris-3100 on-the-go soil mapping tool. Statistical analysis was carried out on the 10.791 ECa raw data in order to filter the outliers. The applied statistical method was ±1.5 interquartile (IRQ) distance approach. The visualization of soil moisture distribution within the experimental field was carried out by means of ArcGIS/ArcMAP using the inverse distance weighting interpolation method. In the investigated 25 sampling points, coefficient of determination between calculated volumetric moisture content data and measured ECa was R2 = 0.87. According to our results, volumetric moisture content can be mapped by applying ECa measurements in these particular soil types.

Effects of soil compaction on cereal yield

This paper reviews the works related to the effect of soil compaction on cereal yield and focuses on research of field experiments. The reasons for compaction formation are usually a combination of several types of interactions. Therefore one of the most researched topics all over the world is the changes in the soil’s physical and chemical properties to achieve sustainable cereal production conditions. Whether we are talking about soil bulk density, physical soil properties, water conductivity or electrical conductivity, or based on the results of measurements of on-line or point of soil sampling resistance testing, the fact is more and more information is at our disposal to find answers to the challenges. Thanks to precision plant production technologies (PA) these challenges can be overcome in a much more efficient way than earlier as instruments are available (geospatial technologies such as GIS, remote sensing, GPS with integrated sensors and steering systems; plant physiological models, such Decisio...

Improving yield advisory models for precision agriculture with special regards to soil compaction in maize production

Evaluating the accuracy of Decision Support System for Agrotechnology Transfer (DSSAT) and ProPlanta fertilizer advisory system for maize crop (Zea mays L.) using the 2010 and 2011 database, it was concluded that simulations led to large inaccuracies in small plot sizes (0.25 ha). However the differences between simulated and measured yields related to a research field (15.3 ha) were relatively good. The 10-year databases have also been taken into consideration. The aim of the research was to adapt the different crop system models to site-specific precision technologies by taking the soil physical parameters electrical conductivity, cone index and tillage draught force into account.

Soil moisture distribution mapping in topsoil and its effect on maize yield

Abstract Soil moisture content directly influences yield. Mapping within field soil moisture content differences provides information for agricultural management practices. In this study we aimed to find a cost-effective method for mapping within field soil moisture content differences. Spatial coverage of the field sampling or TDR method is still not dense enough for site-specific soil management. Soil moisture content can be calculated by measuring the apparent soil electrical conductivity (ECa) using the Veris Soil EC-3100 on-the-go soil mapping tool. ECa is temperature dependent; therefore values collected in different circumstances were standardized to 25°C temperature (EC25). Constants for Archie’s adjusted law were calculated separately, using soil temperature data. According to our results, volumetric moisture content can be mapped by applying ECa measurements in our particular field with high spatial accuracy. Even though within-field differences occure in the raw ECa map standardization to EC25 is recommended. Soil moisture map was also compared to yield map showing correlation (R2 = 0.5947) between the two datasets.

MACHINE VISION FOR ON-LINE WEED IDENTIFICATION

Abstract To compensate the existing difficulties in case of machine vision based weed recognition more and more complicated systems are applied. It means a demand of significantly increasing investment and extra cost for the farmers. However, the complexity of the field conditions and the morphological variability of the plants still make weed identification complicated. The typical barrier of the practical application is the insufficient efficiency caused by the limited viewing angle of the optical devices and the long computation time. The authors review their optical sensor based weed monitoring system operating with CCD and infrared camera, and a special solution –a special optical device with an optical angle of 360° – trying to eliminate the limitation of the optical instruments concerning to their view angle.

Image Acquisition for Site-specific Weed Monitoring Using Panoramic Annular Lens

The practical application of ground-based site-specific applications using optical devices is set back by some typical limiting factors. In case of optical sensing of weeds, pests and other causative agents or even soil properties, there are some different theories to follow (separate weed species or not, take into account shape parameters or only the spectroscopic differences etc.). The more complex image processing is applied, the more elaborated system build-up and more computing demand are required. Besides, the problem of limited visual field still exists, what can be consequently blamed also for the inadequate operation efficiency. The authors applied a Panoramic Annular Lens (PAL) with a horizontal view angel of 360. allowing the coverage of a field part of 1 ha with a single image. The evaluation of the images is carried out in two parallel ways. After pulling the image on the surface of an inverse sphere identical with the PAL, the 1 ha area can be “walked through” and the weeds are present can be identified by means of visual evaluation on a given level of probability. Simultaneously, the pixels containing green plant parts are filtered and a so-called plant density value is calculated. Positioning the pixels containing plant parts and taking into account the information of the visual analysis proper site-specific weed control can be planned. The authors review their experiences in connection with the mentioned research tasks and the already reached results.