Prediction of the kiwifruit decline syndrome in diseased orchards by remote sensing

Eight years after the first record in Italy, Kiwifruit Decline (KD), a destructive disease causing root rot, has already affected more than 25% of the area under kiwifruit cultivation in Italy. Diseased plants are characterised by severe decay of the fine roots and sudden wilting of the canopy, which is only visible after the season's first period of heat (July-August). The swiftness of symptom appearance prevents correct timing and positioning for sampling of the disease, and is therefore a barrier to aetiological studies. The aim of this study is to test the feasibility of thermal and multispectral imaging for the detection of KD using an unsupervised classifier. Thus, RGB, multispectral and thermal data from a kiwifruit orchard, with healthy and diseased plants, were acquired simultaneously during two consecutive growing seasons (2017-2018) using an Unmanned Aerial Vehicle (UAV) platform. Data reduction was applied to the clipped areas of the multispectral and thermal data from the 2017 survey. Reduced data were then classified with two unsupervised algorithms, a K-means and a hierarchical method. The plant vigour (canopy size and presence/absence of wilted leaves) and the health shifts exhibited by asymptomatic plants between 2017 and 2018 were evaluated from RGB data via expert assessment and used as the ground truth for cluster interpretation. Multispectral data showed a high correlation with plant vigour, while temperature data demonstrated a good potential use in predicting health shifts, especially in highly vigorous plants that were asymptomatic in 2017 and became symptomatic in 2018. The accuracy of plant vigour assessment was above 73% when using multispectral data, while clustering of the temperature data allowed the prediction of disease outbreak one year in advance, with an accuracy of 71%. Based on our results, the unsupervised clustering of remote sensing data could be a reliable tool for the identification of sampling areas, and can greatly improve aetiological studies of this new disease in kiwifruit

Studies on the aetiology of kiwifruit decline: interaction between soil-borne pathogens and waterlogging

Aims: In 2012, Italian kiwifruit orchards were hit by a serious root disease of unknown aetiology (kiwifruit decline, KD) that still causes extensive damage to the sector. While waterlogging was soon observed to be associated with its outbreak, the putative role of soil microbiota remains unknown. This work investigates the role of these two factors in the onset of the disease. Methods: Historical rainfall data were analysed to identify changes that might explain KD outbreak and mimic the flooding conditions required to reproduce the disease in a controlled environment. A greenhouse experiment was thus designed, and vines were grown in either unsterilized (U) or sterilized (S) soil collected from KD-affected orchards, and subjected (F) or not (N) to artificial flooding. Treatments were compared in terms of mortality rate, growth, and tissue modifications. Results: KD symptoms were only displayed by FU-treated vines, with an incidence of 90%. Ultrastructural observations detected tyloses and fibrils in the xylem vessels of all plants, irrespective of the treatment. Phytopythium vexans and Phytopythium chamaehyphon, isolated from roots of FU plants, emerged as the associated microorganisms. Conclusions: We succeeded in reproducing KD under controlled conditions and confirmed its association with both waterlogging and soil-borne microorganism(s)

Effect of meteorological and agronomic factors on maize grain contamination by fumonisin

Fumonisins are toxic secondary metabolites produced by fungi such as F.verticilloides. Maize is commonly colonized by several spoilage fungi both in pre- and post-harvest conditions. Field infection prevention is the best solution to contain contamination, using practices aimed at restricting plant stress and limiting the propagation of the disease. This work is focused on understanding the effect of environmental factors on the production of fumonisins in Friuli Venezia Giulia (NE Italy) on maize crops. The analysis has been performed on a dataset covering a period of 14 years (from 2000 to 2013), recording fumonisins contamination and daily meteorological data (air temperature, RH, Rain, Wind speed) for 13 different drying plants and for three different harvest times (early, medium and late). The drying plants collect grain production from an area of about 70.000-100.000 ha. Data were analyzed by full factorial ANOVA and a multiple regression approach was performed using STATA and SEMoLa software. ANOVA test pointed out a significant effect of factors \u201cyear\u201d and \u201charvest time\u201d (p<0.01) for fumonisin content. Instead, location had no significant effect. The best regression model (R2=0. 65, 2... observation) detected a significant correlation between fumonisin concentration and meteorological data in the period from 15th to 31st July. High fumonisin contents were positively correlated with daily thermal excursion, minimum temperature and wet conditions in this period. Silk drying and harvest time resulted as the key factors to contain and study fumonisins contamination in maize. Results will be used to implement a more complex dynamic model

Rock magnetic signature of the Middle Eocene Climatic Optimum (MECO) event in different oceanic basins

The Middle Eocene Climatic Optimum (MECO) event at ~40 Ma was a greenhouse warming which indicates an abrupt reversal in long-term cooling through the middle Eocene. Here, we present environmental and rock magnetic data from sedimentary successions from the Indian Ocean (ODP Hole 711A) and eastern NeoTethys (Monte Cagnero section - MCA). The high-resolution environmental magnetism record obtained for MCA section shows an interval of increase of magnetic parameters comprising the MECO peak. A relative increase in eutrophic nannofossil taxa spans the culmination of the MECO warming and its aftermath and coincides with a positive carbon isotope excursion, and a peak in magnetite and hematite/goethite concentrations. The magnetite peak reflects the appearance of magnetofossils, while the hematite/goethite apex are attributed to an enhanced detrital mineral contribution, likely related to aeolian dust transported from the continent adjacent to the Neo-Tethys Ocean during a drier, more seasonal MECO climate. Seasurface iron fertilization is inferred to have stimulated high phytoplankton productivity, increasing organic carbon export to the seafloor and promoting enhanced biomineralization of magnetotactic bacteria, which are preserved as magnetofossils during the warmest periods of the MECO event. Environmental magnetic parameters show the same behavior for ODP Hole 711A. We speculate that iron fertilization promoted by aeolian hematite during the MECO event has contributed significantly to increase the primary productivity in the oceans. The widespread occurrence of magnetofossils in other warming periods suggests a common mechanism linking climate warming and enhancement of magnetosome production and preservation

Italian Ryegrass Establishment by Self-Seeding in Integrated Crop-Livestock Systems: Effects of Grazing Management

Recent reports have indicated that integrated crop-livestock systems (ICLS) can enhance sustained crop and livestock production by efficiently using agricultural system resources (Liu et al. 2012). In the subtropical South American regions, soybean (Glycine max L. Merril) and maize (Zea Mays L.) crops are widely grown after Italian ryegrass (Lolium multiflorum Lam) pastures. In this system, the pasture may be established by self-seeding. Self-seedling reduces pasture production costs and extends the grazing period. The stoking method, and especially the grazing intensity, can greatly affect the quantity of seeds added to the soil by affecting the demography of the reproductive tillers. In subtropical areas where Italian ryegrass is used for winter pastures in ICLSs, the effects of crop rotation, stocking methods or grazing intensities on the subsequent ability of Italian ryegrass to self-seed are unknown. The objectives of this study are to evaluate the effects of management practices (crop rotation, stocking method and herbage allowance) on the establishment of Italian ryegrass pastures by self-seedling in an ICLS

Dry matter intake from beef cattle grazing natural grassland with different intensification levels.

Estimating dry matter intake from grazing animals remains a challenge. Among the indicators currently used, n-alkanes have been shown to be a good alternative, especially in heterogeneous environments such as natural grasslands

Methane Emissions by Lactating Ewes Grazing Italian Ryegrass

Agriculture contributes 13.5% of global emissions of greenhouse gases (GHG) (IPCC 2007), and about 50% of CH4 and 60% N2O from anthropogenic sources, while livestock contributes an additional 18% of global GHG emissions (FAO, 2006). Among the various sources with a potential negative impact on the environment, methane emissions for which livestock are mainly responsible have been highlighted for the agricultural sector. Studies on means to mitigate these emissions, and understand how integrated crop and livestock production systems may contribute to the reduction of greenhouse gases, are essential for the creation of public policies for environmental preservation. The objective in this study was to evaluate how strategies for grazing management can influence animal production and emission of methane in areas of crop-livestock integration