Evaluation of soil management effect on crop productivity and vegetation indices accuracy in mediterranean cereal-based cropping systems

none3noMostly, precision agriculture applications include the acquisition and elaboration of images, and it is fundamental to understand how farmers’ practices, such as soil management, affect those images and relate to the vegetation index. We investigated how long-term conservation agriculture practices, in comparison with conventional practices, can affect the yield components and the accuracy of five vegetation indexes. The experimental site is a part of a long-term experiment established in 1994 and is still ongoing that consists of a rainfed 2-year rotation with durum wheat and maize, where two unfertilized soil managements were repeated in the same plots every year. This study shows the superiority of no tillage over conventional tillage for both nutritional and productive aspects on durum wheat. The soil management affects the vegetation indexes’ accuracy, which is related to the nitrogen nutrition status. No-tillage management, which is characterized by a higher content of soil organic matter and nitrogen availability into the soil, allows obtaining a higher accuracy than the conventional tillage. So, the users of multispectral cameras for precision agriculture applications must take into account the soil management, organic matter, and nitrogen content.openOrsini R.; Fiorentini M.; Zenobi S.Orsini, R.; Fiorentini, M.; Zenobi, S

ELENA instrument science and testing: validation with particle beam

Understanding of particle emission processes from the Mercury surface is one of the major objectives of ELENAinstrument in the SERENA experiment on board of the BepiColombo mission. In particular the Ion-Sputteringprocess resulting from charged and energetic particles impacting on the surface can be investigated detectingthe low energetic neutral particles escaping from the planet. The possibility to identify the Ion-Sputtering signaltogether with back-scattered particles and neutrals generated by charge exchange is strictly linked with the newtechnology capability to measure low energetic neutral atoms. This goal can be addressed thanks to a new&oldapproach for the neutral atoms measurement: a well known Time of Flight system enhanced with a new kind ofStart section able to define the start time of the entrance in the ToF path without interacting with the particles anddirectly follow to the Stop detector. The Start section is a shutter composed by two membranes with nanometricslits realized in a large area (1cm2) and oscillating at several frequencies to open and close the entrance of ToFsection. This system is never used before in space mission.The IFSI-INAF Ion beam facility in Rome is devoted to the ELENA testing. The crucial point of the shutteringsystem interaction with particle beam is investigated. The first results demonstrate the good functionality of thiskind of system: capability of the shutter to Open and Close the entrance respect to an ion beam is tested with aMCP stop detector. In this poster we present the IFSI activity in the frame of ELENA science requirement togetherwith the experimental activity devoted to instrument verification

Las micro-regiones entrerrianas en la agenda del desarrollo: fundamentos políticos, económicos y perspectivas

El proyecto concentró sus esfuerzos en poder determinar las transformaciones que sufrió la province de Entre Ríos a nivel de sus escalas de gobernanza, focalizando centralmente en las capacidades de los actores micro-regionales formalmente constituidos. Con la sistematización de contenidos se pudo diseñar el mapa de organizaciones, caracterizarlas y medir el nivel de desarrollo organizacional alcanzado por cada una de ellas. Surge del estudio la evidencia suficiente como para establecer el nivel de complejidad que ha adquirido la gobernanza en el nivel provincial, sobre todo en lo que hace a la gestión estratégica de políticas de desarrollo territorial

Standalone vertex finding in the ATLAS muon spectrometer

A dedicated reconstruction algorithm to find decay vertices in the ATLAS muon spectrometer is presented. The algorithm searches the region just upstream of or inside the muon spectrometer volume for multi-particle vertices that originate from the decay of particles with long decay paths. The performance of the algorithm is evaluated using both a sample of simulated Higgs boson events, in which the Higgs boson decays to long-lived neutral particles that in turn decay to bbar b final states, and pp collision data at √s = 7 TeV collected with the ATLAS detector at the LHC during 2011

Las micro-regiones entrerrianas en la agenda del desarrollo: fundamentos políticos, económicos y perspectivas

El proyecto concentró sus esfuerzos en poder determinar las transformaciones que sufrió la province de Entre Ríos a nivel de sus escalas de gobernanza, focalizando centralmente en las capacidades de los actores micro-regionales formalmente constituidos. Con la sistematización de contenidos se pudo diseñar el mapa de organizaciones, caracterizarlas y medir el nivel de desarrollo organizacional alcanzado por cada una de ellas. Surge del estudio la evidencia suficiente como para establecer el nivel de complejidad que ha adquirido la gobernanza en el nivel provincial, sobre todo en lo que hace a la gestión estratégica de políticas de desarrollo territorial

Validation of Rapid and Low-Cost Approach for the Delineation of Zone Management Based on Machine Learning Algorithms

Proximal soil sensors are receiving strong attention from several disciplinary fields, and this has led to a rise in their availability in the market in the last two decades. The aim of this work was to validate agronomically a zone management delineation procedure from electromagnetic induction (EMI) maps applied to two different rainfed durum wheat fields. The k-means algorithm was applied based on the gap statistic index for the identification of the optimal number of management zones and their positions. Traditional statistical analysis was performed to detect significant differences in soil characteristics and crop response of each management zones. The procedure showed the presence of two management zones at both two sites under analysis, and it was agronomically validated by the significant difference in soil texture (+24.17%), bulk density (+6.46%), organic matter (+39.29%), organic carbon (+39.4%), total carbonates (+25.34%), total nitrogen (+30.14%), protein (+1.50%) and yield data (+1.07 t ha−1). Moreover, six unmanned aerial vehicle (UAV) flight missions were performed to investigate the relationship between five vegetation indexes and the EMI maps. The results suggest performing the multispectral images acquisition during the flowering phenological stages to attribute the crop spatial variability to different soil proprieties

Nitrogen and chlorophyll status determination in durum wheat as influenced by fertilization and soil management: Preliminary results.

Handheld chlorophyll meters as Soil Plant Analysis Development (SPAD) have proven to be useful tools for rapid, no-destructive assessment of chlorophyll and nitrogen status in various crops. This method is used to diagnose the need of nitrogen fertilization to improve the efficiency of the agricultural system and to minimize nitrogen losses and deficiency. The objective of this study is to evaluate the effect of repeated conservative agriculture practices on the SPAD readings, leaves chlorophyll concentration and Nitrogen Nutrition Index (NNI) relationships in durum wheat under Mediterranean conditions. The experimental site is a part of a long-term-experiment established in 1994 and is still on-going where three tillage managements and three nitrogen fertilizer treatments were repeated in the same plots every year. We observed a linear relationship between the SPAD readings performed in the central and distal portion of the leaf (R2 = 0.96). In fertilized durum wheat, we found all positive exponential relationships between SPAD readings, chlorophyll leaves concentration (R2 = 0.85) and NNI (R2 = 0.89). In the unfertilized treatment, the SPAD has a good attitude to estimate leaves chlorophyll concentration (R2 = 0.74) and NNI (R2 = 0.77) only in crop grow a soil with relative high content of soil organic matter and nitrogen availability, as observed in the no tilled plots. The results show that the SPAD can be used for a correct assessment of chlorophyll and nitrogen status in durum wheat but also to evaluate indirectly the content of soil organic matter and nitrogen availability during different growth stages of the crop cycle

Fertilization and soil management machine learning based sustainable agronomic prescriptions for durum wheat in Italy

The agricultural sector is challenged to produce more food with less available land. This challenge is compounded by increasing production input costs, which are further impacted by geopolitical changes and the adverse effects of climate change. Finding sustainable solutions to address these challenges is crucial. Machine learning can be a valuable tool in agriculture to optimize soil, nutrient, and crop management, helping to maximize food production on limited land and mitigate the effects of climate change. Machine learning models hold great promise in agriculture; however, their success is contingent on ease of use, accessibility for farmers, and the perceived utility of such models by the agricultural community. This work aimed to develop a meta-machine learning that allows the simulation of different combinations of soil and nitrogen management of durum wheat in Italy. This model aimed to assist decision makers and stakeholders in determining the most effective agronomic management based on attainable crop yield and potential income margins derived from the use of agronomic inputs. The meta-machine learning model was developed and tested across four sites located in the Italian regions of Marche and Basilicata. These sites featured different experimental designs, and durum wheat was grown for several years. The study involved the comparison of a total of eleven different nitrogen levels. The meta-machine learning was composed by linked classification and regression machine learning models. These components were trained using a multi-data source approach, which included data from remote sensing, crop phenology, soil chemical properties, weather data, soil management, and nitrogen levels, to predict durum wheat yield. The classification task employed a Random Forest model with an accuracy of 0.98, kappa of 0.96 and recall of 0.98 for predicting the crop phenology while the yield prediction task was performed by a Neural Network model with an R squared of 0.90, Root Mean Square Error of 0.59, Mean Absolute Error of 0.45 and Mean Absolute Percentage Error of 0.17. The variable importance analysis was conducted to identify the most important covariates that allow to improve the model’s accuracy. This analysis revealed that temperature, precipitation, NDVI (Normalized Difference Vegetation Index), and nitrogen input are the most important factors. The meta-model was used to run simulations of 30 different combinations of soil management and fertilization levels. These simulations aimed to identify the most effective agronomic strategy for each of the farm sites. The no tillage management have been found to result in increased grain yield. The Marginal Fertilizer Yield Index was used to determine the optimal nitrogen application for the crop. The potential transferability to field conditions of the model is facilitated by its utilization of publicly available spatial datasets, which can enable the broader application of the meta-model

Long term effects of nitrogen fertilization on soil organic matter: applications of the DSSAT model

The conversion from natural to agricultural ecosystems and unsustainable land management and agricultural practices have often lowered the soil organic matter (SOM) content (Doran, 2002). An increase of SOM is required almost everywhere (Triberti et al. 2008), since it plays a key role to maintain sustainable cropping systems. It prevents soil degradation by limiting soil cracking and erosion, reduces pollution risks by adsorbing toxic substances, improves soil structure, plant nutrients availability and soil microbial biodiversity. Part of SOM which has been lost can be re-sequestered through adoption of recommended soil and crop management practices. DSSAT 4.02 (Jones et al., 2003) has been recently integrated with the CENTURY SOM module (Gijsman et aI., 2002) and the module for tillage effects on soil processes, to simulate the long term dynamics of SOM.The objective of this study was to analyze the long term impact of tillage and fertility management on soil organic matter fractions in a durum wheat-corn rotation in a hilly rainfed area using field experiments and model simulations. In this paper we report the results of the effect of the nitrogen fertilization on SOM

Immunohistochemical analysis for CD21, CD35, Caldesmon and S100 protein on dendritic cells types in oral lymphomas

OBJECTIVE: Follicular dendritic cells (FDCs) and interdigitating dendritic cells (IDCs) are dendritic cells found in lymphoid follicles, reactive follicles and in lymphomas. The goal of this study was to evaluate the presence and distribution of FDCs and IDCs in oral lymphomas. MATERIAL AND METHODS: Immunohistochemistry reactions were applied to 50 oral lymphomas using the antibodies anti-CD21, anti-CD35 and anti-caldesmon to FDCs, and anti-S100 protein to IDCs. Caldesmon+/FDCs and S100+/IDCs were quantified in Imagelab® software. RESULTS: FDCs revealed by CD21 and CD35 were positively stained in two cases of diffuse large B-cell lymphoma, one MALT lymphoma, and in one case of mantle cell lymphoma. FDCs were immunopositive to caldesmon in all cases, as well as IDCs to S100 protein. Burkitt lymphoma presented a lower amount of caldesmon+/FDCs and S100+/IDCs than diffuse large B-cell lymphoma and plasmablastic lymphoma of the oral mucosa type. CONCLUSIONS: The microenvironment determined by neoplastic lymphoid cells in oral lymphomas is responsible by the development and expression of dendritic cells types