Application of a low-cost camera on a UAV to estimate maize nitrogen-related variables

The development of small unmanned aerial vehicles and advances in sensor technology have made consumer digital cameras suitable for the remote sensing of vegetation. In this context, monitoring the in-field variability of maize (Zea mays L.), characterized by high nitrogen fertilization rates, with a low-cost color-infrared airborne system could be the basis for a site-specific nitrogen (N) fertilization support system. An experimental field with different N treatments applied to silage maize was monitored during the years 2014 and 2015. Images of the field and reference destructive measurements of above ground biomass, its N concentration and N uptake were taken at V6 and V9 development stages. Classical normalized difference vegetation indices (NDVI) and the indices adjusted by crop ground cover were calculated and regressed against the measured variables. Finally, image colorgrams were used to explore the potential of band-related information in variable estimation. A colorgram is a linear signal that summarizes the color content of each digital image. It is composed of a sequence of the frequency distribution curves of the camera bands, of their related parameters and of results of the principal components analysis applied to each image. The best predictors were found to be the ground cover and the adjusted green-based NDVI: regression equation at V9 resulted in R2 of 0.7 and RRMSE < 25% in external validation. Colorgrams did not improve prediction performance due to the spectral limitations of the camera. Therefore, the feasibility of the method should be tested in future research. In spite of limitations of sensor setup, the modified camera was able to estimate maize biomass due to the very high spatial resolution. Since the above ground biomass is a robust proxy of N status, the modified camera could be a promising tool for a low-cost N fertilization support system

Agronomic and Environmental Benefits of Cover Crops in Northern Italy

Cover crops have a number of benefits (reduction of nitrate leaching and of soil erosion, control of weed seed bank, increase of soil organic matter and increase of cash crop yield), but these were seldom quantified in cropping systems of Northern Italy. This experiment aimed to quantify some of these effects, by comparing cover crop species and their management techniques

Assessing the Reliability of Thermal and Optical Imaging Techniques for Detecting Crop Water Status under Different Nitrogen Levels

Efficient management of irrigation water is fundamental in agriculture to reduce the environmental impacts and to increase the sustainability of crop production. The availability of adequate tools and methodologies to easily identify the crop water status in operating conditions is therefore crucial. This work aimed to assess the reliability of indices derived from imaging techniques\u2014thermal indices (Ig (stomatal conductance index) and CWSI (CropWater Stress Index)) and optical indices (NDVI (Normalized Difference Vegetation Index) and PRI (Photochemical Reflectance Index))\u2014as operational tools to detect the crop water status, regardless the eventual presence of nitrogen stress. In particular, two separate experiments were carried out in a greenhouse, on two spinach varieties (Verdi F1 and SV2157VB), with different microclimatic conditions and under different levels of water and nitrogen application. Statistical analysis based on ANOVA test was carried out to assess the independence of thermal and optical indices from the crop nitrogen status. These imaging indices were successively compared through correlation analysis with reference destructive and non-destructive measurements of crop water status (stomatal conductance, chlorophyll a fluorescence, and leaf and soil water content), and linear regression models of thermal and optical indices versus reference measurements were calibrated. All models were significant (Fisher p-value lower than 0.05), and the highest R2 values (greater than 0.6) were found for the regression models between CWSI and the soil water content, NDVI and the leaf water content, and PRI and the stomatal conductance. Further analysis showed that imaging indices acquired by thermal cameras (especially CWSI) can be used as operational tools to detect the crop water status, since no dependence on plant nitrogen conditions was observed, even when the soil water depletion was very limited. Our results confirmed that imaging indices such as CWSI, NDVI and PRI can be used as operational tools to predict soil water status and to detect drought stress under different soil nitrogen conditions

Gene Expression Biomarkers for Evaluating Nitrogen Nutritional Status in Rice

Over the last five decades the increase in rice yield has been associated with a dramatic increment in the use of nitrogen (N) fertilizers. Understanding of plant molecular responses to N is critical for our ability to improve the agricultural sustainability of rice cropping systems by developing a comprehensive approach that allows the selection of varieties with enhanced efficiency in their ability to use N and the development of new strategies to better manage N fertilization practices. In order to develop novel tools for real-time assessing of rice N nutritional status, we analyzed the expression profiles of seven putative gene expression markers in the shoots of rice plants grown under different N availability and environmental conditions. Our results suggest that five out of the seven genes analyzed have the potential to be used as agronomic tools to monitor and optimize the N nutritional status of rice

A multi-element psychosocial intervention for early psychosis (GET UP PIANO TRIAL) conducted in a catchment area of 10 million inhabitants: study protocol for a pragmatic cluster randomized controlled trial

Multi-element interventions for first-episode psychosis (FEP) are promising, but have mostly been conducted in non-epidemiologically representative samples, thereby raising the risk of underestimating the complexities involved in treating FEP in 'real-world' services

Inerbimento del vigneto con specie autoriseminanti

Annual species sown in a north Italian vineyard in 1998 were monitored during 1999-2001. Species sown included 3 Trifolium subterraneum cultivars (Nuba, Denmark and Gosse), as well as T. resupinatum (cv. Kyambro), T. michelianum (cv. Giorgia) and Lolium rigidum (cv. Nurra). Species were compared with spontaneous cover. All adapted well to low temperatures and maintained good ground cover, in particular the T. subterraneum varieties. Cv. Gosse led to improved white wine quality, despite the known sensitivity of white wine to water or nutrient stress in the vines