An algebraic pedotransfer function to calculate standardized in situ determined field capacity.

Despite the large applicability of the field capacity (FC) concept in hydrology and engineering, it presents various ambiguities and inconsistencies due to a lack of methodological procedure standardization. Experimental field and laboratory protocols taken from the literature were used in this study to determine the value of FC for different depths in 29 soil profiles, totaling 209 soil samples. The volumetric water content (θ) values were also determined at three suction values (6 kPa, 10 kPa, 33 kPa), along with bulk density (BD), texture (T) and organic matter content (OM). The protocols were devised based on the water processes involved in the FC concept aiming at minimizing hydraulic inconsistencies and procedural difficulty while maintaining the practical meaning of the concept. A high correlation between FC and θ(6 kPa) allowed the development of a pedotransfer function (Equation 3) quadratic for θ(6 kPa), resulting in an accurate and nearly bias-free calculation of FC for the four database geographic areas, with a global root mean squared residue (RMSR) of 0.026 m3·m-3. At the individual soil profile scale, the maximum RMSR was only 0.040 m3·m-3. The BD, T and OM data were generally of a low predicting quality regarding FC when not accompanied by the moisture variables. As all the FC values were obtained by the same experimental protocol and as the predicting quality of Equation 3 was clearly better than that of the classical method, which considers FC equal to θ(6), θ(10) or θ(33), we recommend using Equation 3 rather than the classical method, as well as the protocol presented here, to determine in-situ FC.

Response of tropical maize to supplemental irrigation strategies.

Water is one of the most important factors influencing crop production in rainfed cropping systems. In tropical regions, supplemental irrigation reduces the risk of yield losses associated to water deficit due to insufficient rainfall. Water deficit in regions with irregularities in rainfall may be overcome with the use of supplemental irrigation, a technique based on the application of water at amounts below the crop?s evapotranspiration (ETc). We investigated the potential of supplemental irrigation as a strategy to increase yield of maize grown under tropical conditions. We used the CSM-CERES-Maize model of the Decision Support System for Agrotechnology Transfer (DSSAT) to simulate irrigation strategies of maize in six counties in the state of Minas Gerais, Brazil. Our results indicate significant differences on simulated crop yield in response to supplemental irrigation. As a consequence, water productivity was improved with reductions of 10% and 15% of full irrigation depths in one of the six counties while in two the water productivity was higher when full irrigation was applied.

Deciphering the role of plant microbiome on strawberry and raspberry growth, resistance, fruit quality and aroma

Besides their own adaptation strategies, plants might exploit microbial symbionts for overcoming both biotic and abiotic stresses and increase fitness. The current scenario of rapid climate change is demanding more sustainable agricultural management practices. The application of microbe-based products as a valid alternative to synthetic pesticides and fertilizers and their use to overcome stresses exacerbated by climate change, have been reviewed in the first part of this thesis. Berry fruits are widely cultivated and appreciated for their aromatic and nutraceutical properties. This thesis is focused on the role of plant and fruit microbiome on strawberry and raspberry growth, resistance, fruit quality and aroma. A taxonomical and functional description of the microbiome of different organs of three strawberry genotypes was performed both by traditional cultural dependent method and Next Generation Sequencing technique, highlighting a significant role of plant organs and genotype in determining the composition of microbial communities. Additionally, a selection of bacteria native of strawberry plants were isolated and screened for their plant growth promoting abilities and tested under the biotic stress of Xanthomonas fragariae infection and the abiotic stress of induced salinity. The monitoring of biometric parameters allowed the selection of a more restricted panel of bacterial strains, whose beneficial potential was tested in coordinated inoculations, or singularly. Raspberry plant was used for investigating the effect of cultivation method in determining fruit microbiome, and its consequent influence of berry quality and aroma. Interestingly, the cultivation method strongly influenced fruit nutraceutical traits, aroma and epiphytic bacterial biocoenosis. The involvement of the bacterial microbiota in fruit aroma determination was evaluated by performing GC–MS analysis of VOCs occurring in control, sterile and artificially reinoculated berries and by characterizing control and reinoculated berry microbiome. Differently treated berries showed significantly different aromatic profile, confirming the role of bacteria in fruit aroma development.

Preharvest factors affecting quality and antioxidant levels on Abate Fétel pears: study of superficial scald with a multivariate statistical approach and neural networks

There are only a few insights concerning the influence that agronomic and management variability may have on superficial scald (SS) in pears. Abate Fétel pears were picked during three seasons (2018, 2019 and 2020) from thirty commercial orchards in the Emilia Romagna region, Italy. Using a multivariate statistical approach, high heterogeneity between farms for SS development after cold storage with regular atmosphere was demonstrated. Indeed, some factors seem to affect SS in all growing seasons: high yields, soil texture, improper irrigation and Nitrogen management, use of plant growth regulators, late harvest, precipitations, Calcium and cow manure, presence of nets, orchard age, training system and rootstock. Afterwards, we explored the spatio/temporal variability of fruit attributes in two pear orchards. Environmental and physiological spatial variables were recorded by a portable RTK GPS. High spatial variability of the SS index was observed. Through a geostatistical approach, some characteristics, including soil electrical conductivity and fruit size, have been shown to be negatively correlated with SS. Moreover, regression tree analyses were applied suggesting the presence of threshold values of antioxidant capacity, total phenolic content, and acidity against SS. High pulp firmness and IAD values before storage, denoting a more immature fruit, appeared to be correlated with low SS. Finally, a convolution neural networks (CNN) was tested to detect SS and the starch pattern index (SPI) in pears for portable device applications. Preliminary statistics showed that the model for SS had low accuracy but good precision, and the CNN for SPI denoted good performances compared to the Ctifl and Laimburg scales. The major conclusion is that Abate Fétel pears can potentially be stored in different cold rooms, according to their origin and quality features, ensuring the best fruit quality for the final consumers. These results might lead to a substantial improvement in the Italian pear industry.

Design and characterization of automated agricultural vehicle systems

Nowadays, technological advancements have brought industry and research towards the automation of various processes. Automation brings a reduction in costs and an improvement in product quality. For this reason, companies are pushing research to investigate new technologies. The agriculture industry has always looked towards automating various processes, from product processing to storage. In the last years, the automation of harvest and cultivation phases also has become attractive, pushed by the advancement of autonomous driving. Nevertheless, ADAS systems are not enough. Merging different technologies will be the solution to obtain total automation of agriculture processes. For example, sensors that estimate products' physical and chemical properties can be used to evaluate the maturation level of fruit. Therefore, the fusion of these technologies has a key role in industrial process automation. In this dissertation, ADAS systems and sensors for precision agriculture will be both treated. Several measurement procedures for characterizing commercial 3D LiDARs will be proposed and tested to cope with the growing need for comparison tools. Axial errors and transversal errors have been investigated. Moreover, a measurement method and setup for evaluating the fog effect on 3D LiDARs will be proposed. Each presented measurement procedure has been tested. The obtained results highlight the versatility and the goodness of the proposed approaches. Regarding the precision agriculture sensors, a measurement approach for the Moisture Content and density estimation of crop directly on the field is presented. The approach regards the employment of a Near Infrared spectrometer jointly with Partial Least Square statistical analysis. The approach and the model will be described together with a first laboratory prototype used to evaluate the NIRS approach. Finally, a prototype for on the field analysis is realized and tested. The test results are promising, evidencing that the proposed approach is suitable for Moisture Content and density estimation.

Soil quality in an experimental vineyard treated with biochar and compost

In order to increase fertility of agricultural soils, in the framework of circular economy, the use of soil amendments such as biochar, compost, and mixtures of the two, has been implemented in recent years. Although it has been demonstrated that their use can improve the physico-chemical characteristics of soil and plant yield, few studies investigated the effect of these amendments on the soil fauna, and consequently the biological quality of soils. This study aimed to provide information on soil fauna, in particular microarthropods , in plots of an experimental vineyard treated with different soil amendments (biochar, compost, and CB mix, i.e. a mixture of biochar and compost) compared to untreated plots. What emerged from this study is that taxa abundances are significantly increased in compost-treated soil samples compared to untreated and CB mix ones. The value of the QBS-ar index obtained in soil samples treated with CB mix is lower than in samples treated with compost, biochar, and untreated, although the difference was not statistically significant. The physico-chemical soil characteristics are, in general, significantly more favorable in samples treated with CB mix than in the control, although the soil fauna seems to be partially negatively influenced by the treatment with CB mix. In fact, the number of taxa, in particular the number of taxa most adapted to edaphic life, are significantly negatively affected by the application of the CB mix. Concluding, improved physico-chemical characteristics induced by soil amendments do not always correspond to a positive response of the soil fauna, at least with respect to the QBS-ar approach.

Motion Control of an Advanced Electric Implement for Agricultural Autonomous Vehicles

Nowadays, the development of intelligent and autonomous vehicles used to perform agricultural activities is essential to improve quantity and quality of agricultural productions. Moreover, with automation techniques it is possible to reduce the usage of agrochemicals and minimize the pollution. The University of Bologna is developing an innovative system for orchard management called ORTO (Orchard Rapid Transportation System). This system involves an autonomous electric vehicle capable to perform agricultural activities inside an orchard structure. The vehicle is equipped with an implement capable to perform different tasks. The purpose of this thesis project is to control the vehicle and the implement to perform an inter-row grass mowing. This kind of task requires a synchronized motion between the traction motors and the implement motors. A motion control system has been developed to generate trajectories and manage their synchronization. Two main trajectories type have been used: a five order polynomial trajectory and a trapezoidal trajectory. These two kinds of trajectories have been chosen in order to perform a uniform grass mowing, paying a particular attention to the constrains of the system. To synchronize the motions, the electronic cams approach has been adopted. A master profile has been generated and all the trajectories have been linked to the master motion. Moreover, a safety system has been developed. The aim of this system is firstly to improve the safety during the motion, furthermore it allows to manage obstacle detection and avoidance. Using some particular techniques obstacles can be detected and recovery action can be performed to overcome the problem. Once the measured force reaches the predefined force threshold, then the vehicle stops immediately its motion. The whole project has been developed by employing Matlab and Simulink. Eventually, the software has been translated into C code and executed on the TI Lauchpad XL board.

Heavy Metals distribution in drainage canals sediments of the Ravenna province

This work, in collaboration with the Romagna Reclamation Consortium, has the aim of studying the heavy metals concentration distribution in the drainage canals of the Ravenna coastal basins, Italy. Particular attention was given to the area of the V Fosso Ghiaia and VI Bevanella basins, where water and sediment samples were collected in the field and integrated with existing databases. The hydrological regime is controlled and managed by the Consortium, which has divided the territory into several mechanical drainage basins. XRF was performed on 21 sediment samples and pH, EC, T°, Fe2+ and Fetot were measured on 15 water samples by probes and spectrophotometer, respectively. Heavy metals concentrations exceeding legal limits of the D.LGS n ° 152/2006 were found for As, Co, Cr, Pb and Zn. These results were then integrated with canal sediment analyses provided by the Consortium to perform a Principal Component Analysis. PCA results show that the main variable affecting heavy metals distribution is the use of fertilizers, followed by distance from sea, and altimetry, which are directly linked to salinity. Heavy metals concentrations increase with increasing use of fertilizers, which are mainly due to the widespread agricultural practices and industrial land use in the area. High heavy metals concentrations are also found in the canals interested by higher salinity (especially Pinetale Ramazzotti). In fact, the area is affected by salinization caused by a water table below sea level and upward seepage of salty oxygen-poor saline water from the bottom of the aquifer. According to the literature, iron and manganese oxides were found to be an important factor in controlling the heavy metals distribution.

Private sensors and crowdsourced rainfall data: accuracy and effectiveness for monitoring severe events and mapping pluvial flooding in urban areas

The increasing number of extreme rainfall events, combined with the high population density and the imperviousness of the land surface, makes urban areas particularly vulnerable to pluvial flooding. In order to design and manage cities to be able to deal with this issue, the reconstruction of weather phenomena is essential. Among the most interesting data sources which show great potential are the observational networks of private sensors managed by citizens (crowdsourcing). The number of these personal weather stations is consistently increasing, and the spatial distribution roughly follows population density. Precisely for this reason, they perfectly suit this detailed study on the modelling of pluvial flood in urban environments. The uncertainty associated with these measurements of precipitation is still a matter of research. In order to characterise the accuracy and precision of the crowdsourced data, we carried out exploratory data analyses. A comparison between Netatmo hourly precipitation amounts and observations of the same quantity from weather stations managed by national weather services is presented. The crowdsourced stations have very good skills in rain detection but tend to underestimate the reference value. In detail, the accuracy and precision of crowd- sourced data change as precipitation increases, improving the spread going to the extreme values. Then, the ability of this kind of observation to improve the prediction of pluvial flooding is tested. To this aim, the simplified raster-based inundation model incorporated in the Saferplaces web platform is used for simulating pluvial flooding. Different precipitation fields have been produced and tested as input in the model. Two different case studies are analysed over the most densely populated Norwegian city: Oslo. The crowdsourced weather station observations, bias-corrected (i.e. increased by 25%), showed very good skills in detecting flooded areas.

Changes In The Bacterial Community Of Soil From A Neutral Mine Drainage Channel.

Mine drainage is an important environmental disturbance that affects the chemical and biological components in natural resources. However, little is known about the effects of neutral mine drainage on the soil bacteria community. Here, a high-throughput 16S rDNA pyrosequencing approach was used to evaluate differences in composition, structure, and diversity of bacteria communities in samples from a neutral drainage channel, and soil next to the channel, at the Sossego copper mine in Brazil. Advanced statistical analyses were used to explore the relationships between the biological and chemical data. The results showed that the neutral mine drainage caused changes in the composition and structure of the microbial community, but not in its diversity. The Deinococcus/Thermus phylum, especially the Meiothermus genus, was in large part responsible for the differences between the communities, and was positively associated with the presence of copper and other heavy metals in the environmental samples. Other important parameters that influenced the bacterial diversity and composition were the elements potassium, sodium, nickel, and zinc, as well as pH. The findings contribute to the understanding of bacterial diversity in soils impacted by neutral mine drainage, and demonstrate that heavy metals play an important role in shaping the microbial population in mine environments.

Antioxidant And Antiproliferative Activities Of Methanolic Extract From A Neglected Agricultural Product: Corn Cobs.

Neglected agricultural products (NAPs) are defined as discarded material in agricultural production. Corn cobs are a major waste of agriculture maize. Here, a methanolic extract from corn cobs (MEC) was obtained. MEC contains phenolic compounds, protein, carbohydrates (1.4:0.001:0.001). We evaluated the in vitro and in vivo antioxidant potential of MEC. Furthermore, its antiproliferative property against tumor cells was assessed through MTT assays and proteins related to apoptosis in tumor cells were examined by western blot. MEC showed no hydroxyl radical scavenger capacity, but it showed antioxidant activity in Total Antioxidant Capacity and DPPH scavenger ability assays. MEC showed higher Reducing Power than ascorbic acid and exhibited high Superoxide Scavenging activity. In tumor cell culture, MEC increased catalase, metallothionein and superoxide dismutase expression in accordance with the antioxidant tests. In vivo antioxidant test, MEC restored SOD and CAT, decreased malondialdehyde activities and showed high Trolox Equivalent Antioxidant Capacity in animals treated with CCl4. Furthermore, MEC decreased HeLa cells viability by apoptosis due an increase of Bax/Bcl-2 ratio, caspase 3 active. Protein kinase C expression increased was also detected in treated tumor cells. Thus, our findings pointed out the biotechnological potential of corn cobs as a source of molecules with pharmacological activity.