An on-farm rotational grazing trial: restricting access time to pasture did not affect the productivity of a dairy sheep flock in spring

In the Mediterranean area, semi-extensive mixed farming systems characterise the inland landscape and guarantee the maintenance of several agroecosystem services. Rationed and rotational grazing have been proposed as efficient agroecological practices for sustainable intensification. Previous studies have highlighted that, during spring, restricted access time to pasture of below four hours per day decreases herbage intake and milk production of rotationally stoked ewes. The aim of this study was to assess the effect of restricted access time on daily herbage intake and milk productivity of Sarda ewes under rotational grazing management in a real farm located in southern Tuscany. The entire flock of 145 lactating ewes was allotted two homogenous groups and rotationally stoked on a grass-legume mixed pasture and fed about 1.7 kg of DM ewe(-1) d(-1) of supplementation. Each group was then assigned to the following treatments: two hours per day of access time to pasture, from 10:00 to 12:00 CET, and four hours per day of access time to pasture, from 10:00 to 14:00 CET. Data on herbage yield and quality, dry matter intake and milk yield were collected from April 5 to May 10, 2018. The rotational grazing schedule was conducted allowing for abundant herbage and exploiting high-nutritive biomass of the upper horizon sward. The results of our on-farm experiment showed that restricting daily access time to pasture down two hours did not reduce the potential daily herbage intake and the milk performance of dairy ewes rotationally stocked on a mixed pasture in spring. Our study also highlighted the capacity of ewes to self-regulate the herbage intake in order to meet their energy requirements, when neutral detergent fibre is not a limiting factor. Our outcomes should encourage researchers and farmers to co-design further on-farm experiments

Two years monitoring of soil N2O emissions on durum wheat in a Mediterranean area: the effect of tillage intensity and N-fertilizer rate

Two years monitoring of soil N2O emissions on durum wheat in a Mediterranean area: the effect of tillage intensity and N-fertilizer rate. EGU General Assembly 2016 Conference Abstracts, European Geophysical Unio

Carbon Budget of an Agroforestry System after Being Converted from a Poplar Short Rotation Coppice

Poplar (Populus L. spp.) Short Rotation Coppice systems (SRCs) for bioenergy production are being converted back to arable land. Transitioning to Alley Cropping Systems (ACSs) could be a suitable strategy for integrating former tree rows and arable crops. A field trial (Pisa, Central Italy) was set up with the aim of assessing the C storage of an ACS system based on hybrid poplar and sorghum (Sorghum bicolor L. Moench) and comparing it with that of an SRC cultivation system. The carbon budget at the agroecosystem scale was assessed in the first year of the transition using the net biome production (NBP) approach with a simplified method. The overall NBP for the SRC was positive (96 ± 40 g C m−2 year−1), highlighting that the system was a net carbon sink (i.e., NBP > 0). However, the ACS registered a net C loss (i.e., NBP < 0), since the NBP was −93 ± 56 g C m−2 year−1. In the first year of the transition, converting the SRC into an ACS counteracted the potential beneficial effect of C storage in tree belowground biomass due to the high heterotrophic respiration rate recorded in the ACS, which was fostered by the incorporation of residues and tillage disturbance in the alley. Additional years of heterotrophic respiration measurements could allow for an estimate of the speed and extent of C losses

Carbon Budget of an Agroforestry System after Being Converted from a Poplar Short Rotation Coppice

Poplar (Populus L. spp.) Short Rotation Coppice systems (SRCs) for bioenergy production are being converted back to arable land. Transitioning to Alley Cropping Systems (ACSs) could be a suitable strategy for integrating former tree rows and arable crops. A field trial (Pisa, Central Italy) was set up with the aim of assessing the C storage of an ACS system based on hybrid poplar and sorghum (Sorghum bicolor L. Moench) and comparing it with that of an SRC cultivation system. The carbon budget at the agroecosystem scale was assessed in the first year of the transition using the net biome production (NBP) approach with a simplified method. The overall NBP for the SRC was positive (96 40 g C m2 year1), highlighting that the system was a net carbon sink (i.e., NBP &gt; 0). However, the ACS registered a net C loss (i.e., NBP &lt; 0), since the NBP was 93 56 g C m2 year1. In the first year of the transition, converting the SRC into an ACS counteracted the potential beneficial eect of C storage in tree belowground biomass due to the high heterotrophic respiration rate recorded in the ACS, which was fostered by the incorporation of residues and tillage disturbance in the alley. Additional years of heterotrophic respiration measurements could allow for an estimate of the speed and extent of C losses

Non-Parametric Statistical Approaches for Leaf Area Index Estimation from Sentinel-2 Data: A Multi-Crop Assessment

The leaf area index (LAI) is a key biophysical variable for agroecosystem monitoring, as well as a relevant state variable in crop modelling. For this reason, temporal and spatial determination of LAI are required to improve the understanding of several land surface processes related to vegetation dynamics and crop growth. Despite the large number of retrieved LAI products and the efforts to develop new and updated algorithms for LAI estimation, the available products are not yet capable of capturing site-specific variability, as requested in many agricultural applications. The objective of this study was to evaluate the potential of non-parametric approaches for multi-temporal LAI retrieval by Sentinel-2 multispectral data, in comparison with a VI-based parametric approach. For this purpose, we built a large database combining a multispectral satellite data set and ground LAI measurements collected over two growing seasons (2018 and 2019), including three crops (i.e., winter wheat, maize, and alfalfa) characterized by different growing cycles and canopy structures, and considering different agronomic conditions (i.e., at three farms in three different sites). The accuracy of parametric and non-parametric methods for LAI estimation was assessed by cross-validation (CV) at both the pixel and field levels over mixed-crop (MC) and crop-specific (CS) data sets. Overall, the non-parametric approach showed a higher accuracy of prediction at pixel level than parametric methods, and it was also observed that Gaussian Process Regression (GPR) did not provide any significant difference (p-value > 0.05) between the predicted values of LAI in the MC and CS data sets, regardless of the crop. Indeed, GPR at the field level showed a cross-validated coefficient of determination (R2CV) higher than 0.80 for all three crops