1,720,966 research outputs found
Low- and high-frequency irrigation of ‘Rosso di Treviso’ Radicchio
No full textRadicchio (Cichorium intybus L., group rubifolium) is a plant widely cultivated in Italy to sell the leafy heads. Veneto is one of the Italian regions with the largest share of Radicchio cultivation. Radicchio ‘Rosso di Treviso’ is one of the more cultivated varieties, but scientific knowledge about the most appropriate irrigation management is still limited. The study focuses on the effect of two irrigation scheduling criteria on Radicchio yield and on the number of marketable plants, in a field experiment carried out from 2013 to 2017 in a commercial farm in Veneto (northeast Italy). Mini-sprinkler system was set to provide water from the transplanting for most of the cropping period, with a low-frequency schedule, and a high-frequency schedule that doubled the number of interventions but halved the water volumes applied each time. The total volumes of water applied each year were the same in both treatments. At harvest, 7 sample areas were randomly harvested and (i) marketable yield, (ii) average head weight, and (iii) number of marketable plants were measured. Overall, the high-frequency schedule produced 26.5 t ha‐1 of marketable Radicchio heads, while the low-frequency schedule 23.6 t ha‐1, significant variability was found between years. The greater productivity was mainly the result of a greater number of marketable plants, while the average head weight was not significantly different between the treatments. This suggests that a greater irrigation interval can create less favorable conditions for radicchio yield, increasing the number of underweight, rotten and missing plants. Farmers should take into account the possibility to increase irrigation frequency if the eventual higher management cost does not offset the gain in radicchio productivity
Controlled drainage and crop production in a long-term experiment in North-Eastern Italy
No full textCrop productivity under controlled drainage was studied in long-term field experiment with shallow fluctuating water table in North-Eastern Italy. Fourteen years of hydrological and yield data, including winter wheat, su- garbeet, soybean and maize, were collected over two monitoring periods (1995–2002 and 2006–2013). Controlled drainage (CD) and free drainage (FD) were tested in combination with open ditches (O) and sub- surface pipes (P) systems. CD reduced outflow waters by 69%, respect to FD. Wheat produced on average 4.9 t ha−1. P system was more productive (up to 14.2%) in drier years characterized by sparse and more intense spring rainfalls, due to reduced runoff and increased infiltration. O system was more productive (up to 27.9%) in wet years with frequent rainfalls after sowing, as water was removed faster from soil surface avoiding water- logging. Soybean produced on average 3.2 t ha−1, with higher yield (5.7% more) in P, probably due to better and more uniform topsoil moisture conditions. Sugarbeet sucrose production showed no univocal response to CD, as a great variety of factors were involved in determining root growth and sucrose concentration. Maize yield had great variability among the years, depending on weather. However, the best results were always obtained with CD (up to 14.5 t ha−1 of grain), showing a definite increase in productivity (on average, with CD grain maize produced 27.3% more, and silage maize 4.0% more). The benefits of CD on maize yield were more pronounced in years with wet springs followed by summer droughts. Subirrigation in CD helped to achieve higher yields when soil moisture content was declining due to prolonged dry periods.
In our environment, CD proved to be extremely helpful in reducing water outflows and increasing maize yield, mitigating drought stress
Multi-year N and P removal of a 10-year-old surface flow constructed wetland treating agricultural drainage waters
Full text linkSurface flow constructed wetlands (SFCWs) can be e↵ectively used to treat agricultural drainage waters, reducing N and P surface water pollution. In the Venice Lagoon drainage basin (northeastern Italy), an SFCW was monitored during 2007–2013 to assess its performance in reducing water, N, and P loads more than 10 years after its creation. Nitrogen concentrations showed peaks during winter due to intense leaching from surrounding fields. Phosphorus concentrations were higher after prolonged periods with no discharge, likely due to mobilization of P of the decomposing litter inside the basin. Over the entire period, N removal eciency was 83% for NO3–N and 79% for total N; P removal eciency was 48% for PO4–P and 67% for total P. Values were higher than in several other studies, likely due to the fluctuating hydroperiod that produced discontinuous and reduced outflows. Nitrogen outlet concentrations were reduced by the SFCW, and N removal ratios decreased with increasing hydraulic loading, while no strong correlations were found in the case of P. The SFCW was shown to be an e↵ective long-term strategy to increase water storage and reduce N and P loads in the Venice Lagoon drainage basin
ESTIMATION OF FIELD SCALE TOPSOIL PROPERTIES OF AGRONOMIC INTEREST FROM PRISMA IMAGING SPECTROMETER DATA
Full text linkOn the 22 March 2019, the Italian Space Agency (ASI) launched the PRISMA satellite, having onboard a hyperspectral imager covering the 400-2500 nm range with 234 spectral bands and about 10 nm of bandwidth. The ground spatial resolution is 30 m, plus a panchromatic camera with 5 m spatial resolution. One of the potential application areas of this scientific mission is for precision agriculture applications, among which the mapping of field-scale variability of topsoil properties is of particular interest. PRISMA clear-sky hyperspectral images were acquired in autumn and spring 2019 over two agricultural areas, Maccarese (Central Italy), and Pignola (Southern Italy). An intensive soil sampling campaign was performed, using a ground sampling scheme adapted to PRISMA spatial 30 and 5 m (PAN) resolutions, in the fields where bare soil was exposed at the satellite acquisition dates. Soil texture (clay, silt, sand) and soil organic carbon (SOC) for the collected soil samples were then determined in the laboratory. The dataset was then used to test calibration and validation of PLS (Partial Least Squares) and Random Forest (RF) regressions, developed using PRISMA surface reflectance data. To this aim, several pre-treatment tests were performed. The results show that good results could be obtained especially for clay estimation
Soil properties zoning of agricultural fields based on a climate-driven spatial clustering of remote sensing time series data
Full text linkThe identification of zones within an agricultural field that respond differently to environmental factors and agronomic management is a key requirement for the adoption of more precise and sustainable agricultural practices. Several approaches based on spatial clustering methods applied to different data sources, e.g. yield maps, proximal sensors and soil surveys, have been proposed in the last decades. The current availability of a huge amount of free remote sensing data allows to apply these approaches to agricultural areas where ground or proximal data are not available. However, in order to provide useful agronomic management information, it is essential that the zoning obtained by clustering is linked to the underlying spatial variability of soil properties. In this work we explore the hypothesis that the response of crop vigor to temporal climate variability, assessed by remote sensing data time series, selected to correspond to specific growth phases and seasonal climate patterns, provides indications on the variability of soil properties within agricultural fields, for both herbaceous and tree crops. NDVI time-series for 38 years (1984–2021) were obtained for fourteen non-irrigated herbaceous and tree crop fields in Central Italy, from multispectral satellites data (Landsat 5/7/8, Sentinel 2). The Standardized Precipitation-Evapotranspiration Index (SPEI) was used to classify time series into three climatic classes (dry/normal/wet) for five different periods of the growth season, covering the main phenological phases. K-means clustering was used to identify patterns of crop growth from climatically classified image sets, as well as for all the bulked images for comparison (bulk clustering). Clustering results were compared with soil maps obtained from spatialized ground data, for soil texture (clay, silt and sand), soil organic matter and available soil water (ASW). The agreement between the different clustering results and soil maps was assessed by the Adjusted Rand Index. Agreement with soil maps varied depending on the field, the phenological phase considered and the soil property considered. Climate driven clustering from long, late growth season periods best matched soil properties, both for herbaceous and tree crops, despite being based on a limited number of images. The clustering from images spanning a longer growth period for dry years systematically outpaced the bulk clustering for silt, sand and ASW, while the clustering for normal climatic conditions was the best for organic matter. The performance of the matching between clustering and soil maps increased with soil variability significantly more (P < 0.05) than in the bulk clustering (mean slopes respectively 0.468 ± 0.167; 0.113 ± 0.270). The integration of the SPEI climatic index into the clustering procedure systematically improved the identification of zones with homogeneous soil properties, highlighting that a greater attention should be posed to the climate-crop-field
interactions when using remotely sensed images
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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