Anna Maria Stellacci

An approach for assessing the effects of site-specific fertilization on crop growth and yield of durum wheat in organic agriculture

Precision agriculture (PA) technologies allow us to assess field variability and support site-specific (SSP) application of inputs. The joint application of PA and organic farming practices might be synergetic. The objective of this 3-year study was to propose a multivariate statistical and geostatistical approach, to evaluate the effects of SSP nitrogen (N) fertilization on durum wheat in transition to organic farming. Soil parameters were measured to assess soil fertility level before the SSP fertilization on wheat, which was carried out by management zones in the third year. Radiometric measurements were performed with a hyperspectral spectroradiometer and N-uptake at anthesis and grain yield were determined. The expected values and 95xa0% confidence intervals of the soil parameters, N-uptake and yield data were estimated with polygon kriging for each management zone. Reflectance data were reduced through principal component analysis and the retained principal components were submitted to factorial co-kriging analysis to estimate orthogonal scale-dependent factors. Comparisons between N-uptake and yield and between the retained regionalized factors (F1) and yield were performed. The spatial pattern of F1 at shorter scales was mostly reproduced in the N-uptake map, suggesting the predictive capacity of hyperspectral data for crop N-status. Within-cluster variance for yield was reduced, quite probably as a combined effect of meteorological pattern and management. The preliminary results seem to be promising in the perspective of PA. Moreover, an inverse relationship between grain yield and crop N-status was observed.

Short-term effects of conversion to no-tillage on respiration and chemical - physical properties of the soil: a case study in a wheat cropping system in semi-dry environment

47 Abstract: No-tillage (NT) is considered an agricultural practice to preserve soil organic carbon (C), however large uncertainties still affect land-use management measures for reducing carbon dioxide (CO2) emissions from agricultural soil. Short-term changes during the transition between conventional tillage (CT) and NT systems have to be further investigated. In this study, measurements of both actual CO2 fluxes in field and microbial mineralization activity were connected to chemical and physical properties of the soil in a winter wheat cropping system subject to semi-arid climate where NT, performed from only 4 years, has been compared to CT. Results showed no significant differences between CT and NT, confirming a similar turnover time of the organic C between the two treatments, probably due to the young changing in the management (4 years) and the period of measurements (far from ploughing).

Effects of Conservative Tillage and Nitrogen Management on Weed Seed Bank after a Seven-Year Durum Wheat—Faba Bean Rotation

Conservative agriculture includes a range of management strategies with low energy inputs such as no-tillage, minimum tillage, and low application of fertilizers. Weed flora in arable fields is strictly affected by agronomic practices such as tillage and fertilization management. This study was conducted seven years after the beginning of a long-term—durum wheat–faba bean—rotation. It analyzes the combined effects on the soil seed bank of three different tillage systems (conservative, reduced, and conventional tillage) and two levels of nitrogen fertilization. The effects were investigated both using stepwise discriminant analysis and analysis of variance in order to find statistical differences among main factors and their interactions. The seed bank of Conyza canadensis, Papaver rhoeas, Solanum nigrum, Fallopia convolvulus, and Fumaria officinalis was higher in conservative or reduced tillage plots. The magnitude of the response to nitrogen supply varied among weed species. Conyza canadensis seemed to be favored by low nitrogen supply, whereas Sinapis arvensis by higher doses of nitrogen. Anagallis arvensis showed the lowest seed bank in conventionally tilled plots, without distinction of nitrogen supply. The results suggest that different tillage systems and, to a lesser extent, different nitrogen supply, produce changes in the seed bank size and composition, along the soil profile.

On-the-go Acquisition of Hyperspectral Data on a Durum Wheat Field - A Methodological Approach

Hyperspectral 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.

Field Partitioning by Proximal Hyperspectral and Fluorescence Sensor Data and Multivariate Geostatistics

Hyperspectral 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.