89 research outputs found
Assessment of the seasonal pattern of burr and nut growth in a chestnut ‘Marrone-type’ cultivar
Seasonal patterns of burr and nut growth were measured in sweet chestnut trees (C. sativa
Mill.) of the cultivar ‘Marrone di Castel del Rio’. Burr and nut growth expressed as diameter, fresh and
dry weight, and dry matter were assessed from mid of June to mid of October. Results evidenced that burr mainly grows in the initial period of the season, while the nut had a rapid growth in the last part of
the season (i.e., beginning of September). Dry matter of burrs started decreasing when its accumulation
in the nuts was increasing. Burrs with the highest number of nuts (three), experienced a limited nut
growth compared to burrs with two or one nuts per burr, but only at the beginning of nut filling phase.
Lateral nut evidenced a higher growth in weight (fresh and dry) in the first part of the season with occasionally
reduced dry matter compared to central nuts. The burr diameter had a strong positive relationship
with the internal nut diameter and with the total nut weight
Irrigation improves tree physiological performances and nut quality in sweet chestnut
Italy is one of the most important world chestnut producers. The majority of traditional sweet chestnut orchards are still non-irrigated since they are typically located in mountain-hill areas usually characterized by environmental conditions that are not limiting for the vegetative and reproductive growth of this fruit tree crop. Nowadays, the increase of summer temperatures and the decrease of rainfall are affecting negatively chestnut physiological performances and productivity. The adoption of scheduled irrigation practices, in light also of the limited water availability/possibility of storage (e.g., artificial lakes, reservoirs) of these areas, should become part of chestnut orchard management. The aim of the present study was to evaluate the effect of irrigation on sweet chestnut physiology, nut quality and yield. The study was carried out in 2020 in a traditional chestnut orchard of the “Marron Buono di Marradi” ecotype, located in the Tuscan-Emilian Apennines (Marradi, Italy). The experimental design compared trees irrigated between August and September with a non-irrigated control. Leaf gas exchange and plant water status were monitored during the growing season and, nut quality and yield were assessed at harvest. Results showed that irrigated trees exhibited, in middle September, higher photosynthesis, transpiration, stomatal conductance and stem water potentials compared to the non-irrigated control trees. Nut size was significantly smaller in non-irrigated trees than in irrigated ones while the yield was not statistically affected by the irrigation treatment. Despite the favourable mild and rainy weather conditions occurred in 2020, the application of irrigation during the nut filling phase (e.g., late summer) was beneficial for enhancing sweet chestnut physiological performances and for improving nut quality
Single-shot convolution neural networks for real-time fruit detection within the tree
Image/video processing for fruit detection in the tree using hard-coded feature extraction algorithms has shown high accuracy on fruit detection during recent years. While accurate, these approaches even with high-end hardware are still computationally intensive and too slow for real-time systems. This paper details the use of deep convolution neural networks architecture based on single-stage detectors. Using deep-learning techniques eliminates the need for hard-code specific features for specific fruit shapes, color and/or other attributes. This architecture takes the input image and divides into AxA grid, where A is a configurable hyper-parameter that defines the fineness of the grid. To each grid cell an image detection and localization algorithm is applied. Each of those cells is responsible to predict bounding boxes and confidence score for fruit (apple and pear in the case of this study) detected in that cell. We want this confidence score to be high if a fruit exists in a cell, otherwise to be zero, if no fruit is in the cell. More than 100 images of apple and pear trees were taken. Each tree image with approximately 50 fruits, that at the end resulted on more than 5000 images of apple and pear fruits each. Labeling images for training consisted on manually specifying the bounding boxes for fruits, where (x, y) are the center coordinates of the box and (w, h) are width and height. This architecture showed an accuracy of more than 90% fruit detection. Based on correlation between number of visible fruits, detected fruits on one frame and the real number of fruits on one tree, a model was created to accommodate this error rate. Processing speed is higher than 20 FPS which is fast enough for any grasping/harvesting robotic arm or other real-time applications. HIGHLIGHTS: Using new convolutional deep learning techniques based on single-shot detectors to detect and count fruits (apple and pear) within the tree canopy
The effects of chestnut orchard microclimate on burr development
Chestnut crop is regaining its fame worldwide with powerful investment perspectives. Unluckily the climate change effects are posing high threat to its cultivation with less available resources and increased production cost both in traditional and specialized orchards. Additionally, the chestnut physiological knowledge is still limited, especially as concern the burr development (i.e., the economical production target) and its relationship with the environmental parameters. The aim of the present study was to evaluate the seasonal, daily, and hourly burr growth pattern associated to environmental parameters for improving physiological knowledge on this species. The study was carried out in a traditional rainfed sweet chestnut orchard located in the Tuscan-Emilian Apennines (Monterenzio, Italy). The chestnut burr growth was measured, along the entire season, both with a digital calliper and through the use of plant-based sensors (fruit-gauges) that permitted to measure, in real-time, the burr growth pattern. Environmental data were recorded by a weather station placed in the middle of the orchard. Results evidenced a higher burr growth rate, in the last part of the season (from middle-end of August to full fall) while the daily growing pattern was characterized by increased oscillation, along the season, of night-swelling and daily-shrinkage. The night-swelling was found to be influenced by high nocturnal air relative humidity while the daily-shrinkage was influenced by the higher wind speed, solar radiation and vapour pressure deficit. Thus, the burr daily net growth can be associated, depending on the phenological stages, to environmental parameters. Precipitation but especially the atmosphere humidity, in September and October, were the main external drivers of burr daily net growth. These results could be promising for the adoption of sustainable (e.g., late season grass mowing, sprinkler irrigation) and smart practices for improving chestnut management in both traditional and specialized orchards
The fate of bacteria in urban wastewater-irrigated peach tree: a seasonal evaluation from soil to canopy
Irrigation with wastewater can be a solution to preserve and mitigate freshwater demand, in particular during drought periods. Unfortunately, wastewater, although being treated at different levels, could be a carrier of human pathogens (e.g., E. coli) and potentially contaminate crops for human consumptions.This study investigated the seasonal microbiological concentrations, on soil, shoot and fruit tissues of potted peach trees, following two irrigation treatments: freshwater (FW) and secondary urban wastewater without the final disinfection treatment (SW). E. coli was only detected in SW irrigated soil, whereas total coliforms (TC) and total bacteria counts (TBC) were similar in both treatments throughout the season. EndophyticE. coli, Salmonella spp. and TC were not detected in shoot and fruit, but a higher presence of total bacteria (TBC) was observed in SW-irrigated tree compared to FWirrigated tree. In particular, SW shoots had a higher load compared to fruits, thus showing a potential effect of leaf transpiration, that promoted the transfer of water-borne bacteria from soil to the epigeal part (shoot). The adoption of low-quality SW (even above the microbiological limits of the European Regulation 2020/741 for wastewater re-use in agriculture), when a drip irrigation method is applied, could be a valid alternative to save fresh water without compromising fruit safety
Different capabilities of five ELISAs for detection of antibodies against PEDV in pigs exposed to geographically different strains
Fighting autoinflammation in FIRES: The role of interleukins and early immunomodulation
Febrile infection-related epilepsy syndrome (FIRES) is a challenging condition with unfavorable outcome in most cases. Preliminary evidence suggests that some interleukins, in particular IL-1 Receptor Antagonist (IL-1RA), could be elevated due to a functional deficiency of anti-inflammatory pathways. Therefore, treatment strategies acting on innate immunity could represent a targeted treatment. We describe the case of an 11-year-old child with super-refractory status epilepticus (SE), lasting more than two months. After being treated aggressively with antiseizure medications, anesthetics and empiric treatment for autoimmune encephalitis without success, she responded to anakinra and ketogenic diet. Escalation of the therapy was supported by the finding of a very high serum level of IL-1RA. This immunomodulatory approach allowed to discharge the child from intensive care 48 days after the SE onset. After more than one year follow-up the patient has moderate intellectual disability but with good language skills; she is seizure free and without motor deficits. This case suggests that serum IL-1RA serum levels may help to support treatment escalation. Moreover, anakinra and ketogenic diet represent encouraging immunomodulatory strategies which deserve further studies and could potentially have a synergistic effect. Finally, structured neuropsychological testing is an important outcome measure that will help to define the effectiveness of different treatment strategies
Contratto a tutele crescenti e naspi
Il volume suddiviso in tre sezioni affronta, nelle prime due, gli aspetti salienti del d.lgs. n. 23/2015 con riferimento al significato da attribuire al contratto a tutele crescenti e al nuovo regime di tutela dei licenziamenti individuali e collettivi. La terza sezione è dedicata all'analisi della nuova assicurazione sociale per l'impiego ed ai sistemi di politica attiva per la ricerca di nuova occupazion
Abuso e maltrattamento all\u2019infanzia: il ruolo dei Servizi territoriali di Neuropsichiatria dell\u2019infanzia e dell\u2019 adolescenza nel territorio Veneziano , Uoc Famiglia ed Et\ue0 evolutiva, Azienda Ulss 12 Veneziana
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