75 research outputs found
Application of multivariate analysis techniques for selecting soil physical quality indicators: A case study in long-term field experiments in Apulia (Southern Italy)
No full textLong-term field experiments and multivariate analysis techniques represent research tools that may improve our knowledge on soil physical quality (SPQ) assessment. These techniques allow us to measure relatively stable soil conditions and to improve soil quality judgment, thereby reducing uncertainties. A monitoring of SPQ under long-term experiments, aimed at comparing crop residue management strategies (burning vs. incorporation of straw, FE1) and soil management (minimum tillage vs. no tillage, FE2), was established during the crop growing season of durum wheat. The relationships between five SPQ indicators (bulk density [BD], macroporosity [PMAC], air capacity [AC], plant available water capacity [PAWC], and relative field capacity [RFC]) were evaluated, and two techniques of multivariate analysis (principal component analysis and stepwise discriminant analysis) were applied to select key indicators for SPQ assessment. According to the used indicators, an SPQ from optimal to intermediate (i.e., not definitely poor) was detected in 65% of the observations in FE1 and in 54% in FE2. The main results showed a significant negative relationship between RFC and AC, and multivariate analysis identified RFC as a key SPQ indicator, mainly in FE2. Plant available water capacity and BD showed the highest discriminating capability in the FE1 dataset. The highest scores of RFC assessment were highlighted for burning and minimum tillage treatments (+1 and +2). An optimal AC range, derived from optimal RFC limits, was obtained and was suggested to better assess the AC of agricultural soils (0.10 ≤ AC ≤ 0.26 cm3 cm-3)
The mechanical impact of water affected the soil physical quality of a loam soil under minimum tillage and no-tillage: An assessment using beerkan multi-height runs and BEST-procedure
No full textThe multi-height (low, L = 3 cm; intermediate, M = 100 cm; high, H = 200 cm) Beerkan run methodology was applied on both a minimum tilled (MT) (i.e., up to a depth of 30 cm) and a no-tilled (NT) bare loam soil, and the soil water retention curve was estimated by the BEST-steady algorithm. Three indicators of soil physical quality (SPQ), i.e., macroporosity (Pmac), air capacity (AC) and relative field capacity (RFC) were calculated to assess the impact of water pouring height under alternative soil management practices. Results showed that, compared to the reference low run,Mand H runs affected both the estimated soil water retention curves and derived SPQ indicators. Generally, M-H runs significantly reduced the mean values of Pmac and AC and increased RFC for both MT and NT soil management practices. According to the guidelines for assessment of SPQ, the M and H runs: (i) worsened Pmac classification of both MT and NT soils; (ii) did not worsen AC classification, regardless of soil management parameters; (iii) worsened RFC classification of only NT soil, as a consequence of insufficient soil aeration. For both soil management techniques, a strong negative correlation was found between the Pmac and AC values and the gravitational potential energy, Ep, of the water used for the infiltration runs. A positive correlation was detected between RFC and Ep. The relationships were plausible from a soil physics point of view. NT soil has proven to be more resilient than MT. This study contributes toward testing simple and robust methods capable of quantifying soil degradation effects, due to intense rainfall events, under different soil management practices in the Mediterranean environment
Lo sviluppo professionale del docente: dal Piano di Miglioramento alla valorizzazione del merito
No full textIl saggio affronta un tema fra i più dibattuti, attualmente, nel campo dell'analisi delle pratiche educative: la documentazione delle pratiche di miglioramento della qualità scolastica e di valorizzazione della professionalità dell'insegnante.La "logica" del miglioramento chiede a insegnanti e dirigenti di passare da una prospettiva individuale di azione ad una organizzativa più ampia, di sistema, in cui lo sviluppo professionale individuale venga valorizzato quando contribuisce anche al miglioramento del sistema scolastico.Di qui la centralità dei dispositivi di documentazione che devono essere agili, chiari, efficaci nel supportare gli obiettivi del miglioramento. Saper ben documentare è acquisire la padronanza d'uso di una delle leve più efficaci di promozione della professionalità docente. Documentare con competenza permette all'insegnante di raccogliere evidenze a supporto del proprio operato, di saper interpretare i dati per individuare priorità di azioni migliorative; di riuscire a monitorare l'andamento dei processi mobilitati rendendone conto alla comunità degli stakholders con la trasparenza necessaria a esternalizzare il valore di una Scuola e delle azioni dei suoi operatori: dirigenti, personale docente e amministrativo. Solo una valutazione nella sua funzione valorizzante - questa in estrema sintesi la tesi del saggio - può assolvere alla delicata funzione di visibilizzare il livello di professionalità espresso in una Scuola: professionalità che, in assenza di strumenti valutativi/valorizzanti, continuerà a restere oscura e mai veramente riconosciuta
Application of Multivariate Analysis Techniques for Selecting Soil Physical Quality Indicators: A Case Study in Long-Term Field Experiments in Apulia (Southern Italy)
No full textLong-term field experiments and multivariate analysis techniques represent research tools that may improve our knowledge on soil physical quality (SPQ) assessment. These techniques allow us to measure relatively stable soil conditions and to improve soil quality judgment, thereby reducing uncertainties. A monitoring of SPQ under long-term experiments, aimed at comparing crop residue management strategies (burning vs. incorporation of straw, FE1) and soil management (minimum tillage vs. no tillage, FE2), was established during the crop growing season of durum wheat. The relationships between five SPQ indicators (bulk density [BD], macroporosity [PMAC], air capacity [AC], plant available water capacity [PAWC], and relative field capacity [RFC]) were evaluated, and two techniques of multivariate analysis (principal component analysis and stepwise discriminant analysis) were applied to select key indicators for SPQ assessment. According to the used indicators, an SPQ from optimal to intermediate (i.e., not definitely poor) was detected in 65% of the observations in FE1 and in 54% in FE2. The main results showed a significant negative relationship between RFC and AC, and multivariate analysis identified RFC as a key SPQ indicator, mainly in FE2. Plant available water capacity and BD showed the highest discriminating capability in the FE1 dataset. The highest scores of RFC assessment were highlighted for burning and minimum tillage treatments (+1 and +2). An optimal AC range, derived from optimal RFC limits, was obtained and was suggested to better assess the AC of agricultural soils (0.10 ≤ AC ≤ 0.26 cm3 cm-3). © 2019 The Author(s)
Improved Beerkan run methodology to assess water impact effects on infiltration and hydraulic properties of a loam soil under conventional- and no-tillage
No full textBeerkan infiltration experiments with three water pouring heights (low, L = 3 cm; intermediate, M = 100 cm; high, H = 200 cm) were performed on both a no-tilled (NT) and a conventionally tilled (CT) bare loam soil to determine the surface soil hydraulic properties by the BEST-steady algorithm. Saturated soil hydraulic conductivity, Ks, significantly and monotonically decreased from the L to the H runs (from 236 to 37 mm h‒1) and lower Ks values were detected under CT (163–23 mm h‒1) than NT (346–51 mm h‒1) for each water pouring height. For both soil management practices, the gravitational potential energy, Ep, of the water used for the infiltration runs, explained most of the variance in the mean Ks values. According to the fitted relationships, an increase of Ep from 50 to 3,327 J m‒2 determined a Ks decrease by a factor of 9.5 in the CT soil and 6.3 in the NT soil. The CT soil was 2.1 and 3.3 times less conductive than the NT soil with the lowest and the highest energy, respectively. The water retention scale parameter, hg, only varied between non-perturbing (L) and perturbing (M, H) runs because |hg| increased from 55 to 93–100 mm. Therefore, water impact can greatly influence hydrodynamic properties of the upper soil layer regardless of the management practice. The tested infiltration methodology looks promising to mimic effects of relatively high energy rainfall events and to determine the hydraulic properties of the exposed soil layer under different management practices
The Development of Soil Science in Apulia
No full textThe history of soil science in Apulia region begins at the Agricultural Station (today CREA—Council for Agricultural Research and Economics) and it continues with the Universities of Bari (mainly) and Foggia. The characteristics of the rural environment and the Mediterranean climate have influenced research in universities and public research institutes. The relationship between soil and agricultural productivity has always been the common subject of studies. In addition, over the years, there has been a growing interest in the preservation of soil fertility and its improvement in agro-environmental conditions hostile to the conservation of organic matter, fertility, and soil biodiversity. At the operational level, the research carried out proposes sustainable soil management solutions for the farms of the region and the updating of the soil map
Field partitioning by proximal hyperspectral and fluorescence sensor data and multivariate geostatistics
No full textHyperspectral and fluorescence devices can provide relevant information on physiological plant status related to canopy cover, plant nutrition, water status, pigments concentration and functionality. The aim of this study was to combine data from hyperspectral and fluorescence sensors with plant variables, to delineate homogeneous sub-field areas, using multivariate geostatistics. Proximal sensor and biometric data were collected in a 5-ha durum wheat field at anthesis stage, at 104 georeferenced positions. Fluorescence and hyperspectral data were analysed by principal component analysis to reduce the dimensions of the datasets; the retained components together with plant variables were analysed by means of a multivariate geostatistics approach, factorial co-kriging analysis. A linear model of coregionalization, fitted to the direct and cross experimental variograms of the Gaussian transformed variables, included a nugget effect and a spherical model with a range of 125 m. The first regionalised factor at 125m-scale, explaining 66.9% of the corresponding variance, was able to discriminate areas characterised by better overall plant status and photosynthetic performance from more stressed areas. The approach was sensitive to split the field into two main areas. However, repeated measurements over the crop season are needed to confirm the previous results
On-the-go acquisition of hyperspectral data on a durum wheat field - A methodological approach
No full textHyperspectral proximal sensors, operating in the Vis-NIR-SWIR ranges, are usually employed for static recording. The availability of data at a fine spatial resolution through on-the-go spectra collection would open new frontiers to this field of study, allowing in real time the acquisition of a huge amount of information related to plant response. In this paper we describe a methodological approach for analysing on-the-go hyperspectral data in order to delineate homogeneous zones in an agricultural field cropped with durum wheat. HS data were acquired in southern Italy at shooting stage of durum wheat. Spectral readings were recorded using a high resolution spectroradiometer, FieldSpec 4 (350-2500 nm). The sensor was mounted on a plot seeder. Collected data were subjected to pre-processing and then analysed through principal component analysis. Afterwards, retained factors were analyzed through block co-kriging to produce continuous maps. The method was very effective to disclose differences in the spectral response of the plants; however, the interpretation of the results in terms of agronomical behaviour of the wheat needs more survey and investigation
A multivariate approach for assessing leaf photo-assimilation performance using the IPL index
No full textThe detection of leaf functionality is of pivotal importance for plant scientists from both theoretical and practical point of view. Leaves are the sources of dry matter and food, and they sequester CO2 as well. Under the perspective of climate change and primary resource scarcity (i.e. water, fertilizers and soil), assessing leaf photo-assimilation in a rapid but comprehensive way can be helpful for understanding plant behavior under different environmental conditions and for managing the agricultural practices properly. Several approaches have been proposed for this goal, however, some of them resulted very efficient but little reliable. On the other hand, the high reliability and exhaustive information of some models used for estimating net photosynthesis are at the expense of time and ease of measurement. The present study employs a multivariate statistical approach to assess a model aiming at estimating leaf photo-assimilation performance, using few and easy-to-measure variables. The model, parameterized for apple and pear and subjected to internal and external cross validation, involves chlorophyll fluorescence, carboxylative activity of ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCo), air and leaf temperature. Results prove that this is a fair-predictive model allowing reliable variable assessment. The dependent variable, called IPL index, was found strongly and linearly correlated to net photosynthesis. IPL and the model behind it seem to be (1) reliable, (2) easy and fast to measure and (3) usable in vivo and in the field for such cases where high amount of data is required (e.g. precision agriculture and phenotyping studies)
NDVI as a potential tool for predicting biomass, plant nitrogen content and growth in wheat genotypes subjected to different water and nitrogen conditions
No full textThe application of spectroradiometric index such as the normalized difference vegetation index (NDVI) to assess green biomass or nitrogen (N) content has focused on the plant canopy in precision agriculture or breeding programs. However, little is known about the usefulness of these techniques in isolated plants. The few reports available propose the use of a spectroradiometer in combination with special adaptors that improve signal acquisition from plants, but this makes measurements relatively slow and unsuitable. Here we studied the direct use (i.e. without adaptors) of a commercial cost-effective spectroradiometer, GreenSeekerTM (NTech Industries Ins., Ukiah, California, USA) provided with an active sensor (i.e. equipped with its own source of radiation) for measuring NDVI in four genotypes of durum wheat (Triticum turgidum L. var. durum) grown in pots under a range of water and N regimes. Strong correlations were observed between NDVI measurements and dry aboveground biomass (AB), total green area (TGA), green area without spikes (GA) and aboveground N content (AN). To prove the predictive ability of NDVI measured under potted conditions, linear regression models for each growth trait and for plant N content were built with the data of two genotypes. The models accurately predicted growth traits and N content, confirming the direct relationship between total plant biomass and spectroradiometric readings
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