Fusarium spp. is one of the most prominent genera of plant pathogens due to its wide range of hosts and mycotoxin production. The Fusarium fujikuroi species complex (FFSC) encompasses several known plant pathogens, such as Fusarium circinatum, F. fujikuroi, F. sacchari, and F. verticillioides. Cymbopogon citratus is a widely distributed aromatic and medicinal plant rich in secondary metabolites. Most of C. citratus cultivation is related to essential oil (EO) extraction since their volatiles have applications in the food, fragrance, and pharmaceutical industries. In the present study, the first report of C. citratus wilt caused by a FFSC species in Portugal is described. Symptomatologic, cultural, morphologic, genetic, and cytogenomic characteristics associated with this pathogen and disease are displayed. The cultural features included flat, white-colored colonies with filiform margins and abundant cottony aerial mycelia at the upper surface and orange-violet colored at the lower surface. On Carnation Leaf-Piece Agar, septate fusoid macroconidia were present, displaying a flattened tapering toward the basal part and a number of septa ranging from one to four. The comparison of amplified and aligned ITS sequences revealed a 100% similarity between the isolated fungus and the FFSC. Finally, a flow cytometry assay revealed an estimated genome size of 29.9 Mbp, contrasting with other FFSC-known pathogens. Ultimately, by examining these various aspects, this work aims to comprehensively understand the wilt and its causal agent.

Soil organic carbon loss occurs at a rate equivalent to 10 % of the total fossil fuel emissions for Europe as a whole. Intensive use of synthetic fertilizers results in soil degradation and nutrient loss. Microbially mediated soil organic matter is an extremely sensitive pool that indicates subtle changes in the quality parameters responsible for the soil’s ecological and productive functions. The goal of the research was calculation of carbon budget and changes in carbon accumulation/sequestration as a result of more than 50 years of mineral fertilization. Stocks of C in organic carbon, labile carbon, light carbon and microbial carbon fractions were analyzed, as well as carbon sequestration rate in 50-yrs were calculated. The highest input of organic C, PMC LFC and MBC was found for the treatments with the highest N-fertilization. However, C sequestration rates of the fertilized plots were from 10.68 – to 12.12 % from the 100% adjacent natural meadow. C sequestration rate between the fertilized plots were not significantly different except for the control plot for each studied fraction of carbon (OC, PMC, LFC and MBC). The sensitivity index correlated with the amount of light-fraction OM. The results give a deeper insight into the behavior of different pools of labile SOM in the agro-landscapes and can serve as a reliable basis for further researches focused on neutral carbon emissions and effective C sequestration

Remote sensing technology (namely, through UAVs) has been used to monitor potato crops. As such, this study aims to analysis the relationship between the NDVI index model and yield productivity in Solanum tuberosum L. plants from Agria variety submitted to Ca biofortification process with two different concentrations (12 and 24 kg/ha) of CaCl₂ or Ca-EDTA. The NDVI values were collected six days after the six foliar application and compared to Ca increase in potato tubers (at harvest) and total yield. The results highlight the fact that 24 kg/ha CaCl₂ presented the lowest NDVI index, however, did not show the lowest yield. Moreover, that same treatment presented the highest Ca biofortification index in tubers. Also, seems that NDVI index can be used in decision-making and improve crop management strategies considering being an indicator to detect plant growth or vigor, however in this research, it’s not sufficient for yield prediction.

Human malnourishment is a current problem of society and agronomic biofortification is a procedure that wishes to tackle these mineral deficits in human diets by increasing a specific nutrient on the edible part of food crops. Calcium is an important mineral element that performs structural functions, and thus can help prevent the development of pathologies such as osteoporosis. Thereby, this work aims to study the impact of calcium enrichment on fatty acid content in Rocha pears. Thus, an agronomic enrichment workflow with seven foliar sprays of CaCl₂ (with concentrations between 4 - 8 kg/ha), was performed in an orchard located in the West region of Portugal. Besides Ca enrichment assessment in fruits (with a portable x-ray fluorescence analyzer) at harvest, fatty acids (FA) quantification and FA profile (acquired with a gas–liquid chromatograph, coupled to a flame ionization detector (GC-FID)), DBI and lipoperoxidation values (with a spectrophotometer) were also attained. Increases of Ca in sprayed fruits reached 7.6 % to 44.3 %. For FA related parameters, no significant differences were observed, suggesting that Ca sprays did not impact these parameters. Total fatty acids (TFA), double bond index (DBI) and lipoperoxidation values varied between 0.72 - 0.74 g/100 g FW, 8.13 - 9.83 and 2.23 - 3.18 µM /g FW respectively. The following FA profile was attained: C18:2 > C16:0 > C18:3 > C18:0 > C18:1 > <C16:0. No significant differences were observed. In summary, CaCl₂ can be used to increase Ca levels in fruits allowing the production of fruits with prophylactic characteristics, while the concentrations from this study did not impact their FA content. Overall, this suggests that cell compartmentation and membranes regular functioning were maintained, suggesting the absence of lipid decay, and avoiding a potential increase in storage losses.

The global demand for bottled king coconut water has led to a significant accumulation of empty king coconut husks in nut water export industries, posing challenges in managing and disposing of this agricultural waste. To address this issue, the production of king coconut husk ash (KCHA) has emerged as an eco-friendly solution. This product can be applied as a fertiliser, soil amendment, or after mixing with compost to enhance its nutrient value. This study aimed to determine the optimal cut size and moisture level for obtaining a high yield of KCHA with the maximum potassium content. The experiment involved drying full, half, quarter, and chip-sized husks in a dehydrator at 60°C for 0h, 2h, 4h, 8h, 12h, 24h, and 48h. The findings revealed that reducing the particle size of the husks accelerated the drying process. Ash produced with chips exhibited the most favourable characteristics, reaching the desired dryness in a relatively shorter time while yielding the highest KCHA content. Moreover, the results indicated that the optimal duration for dehydrating the husks to produce ash was 24h at 60 °C, resulting in 24 % of moisture content. This processing condition facilitated the efficient conversion of king coconut husks into potassium-rich ash. Implementing these findings into the production of KCHA as a nutrient-rich fertiliser or soil amendment offers a sustainable approach to improve agricultural practices while reducing the dependence on synthetic fertilisers and mitigating the environmental challenges associated with their accumulation.

Detecting N-deficiency early in a plant’s development before visual symptoms becomes pronounced, and irreparable damage done is crucial to maintaining optimum grain yield and biomass production. Chlorophyll fluorescence technology (CFT) is a quick, non-invasive, non-destructive, and informative technique that is used to study the physiological status of plants at any given stage of development. The objective of the study was to determine the photosynthetic and growth responses of N-deficient maize seedling. Two N treatments, 10 t/ha N and 50 t/ha N were evaluated in a greenhouse in a completely randomized design with 12 replications. Results showed a significantly (p<0.05) higher CO₂ assimilation rate, maximum quantum yield of PSII photochemistry, effective quantum yield of PSII photochemistry, and chlorophyll concentration in plants that received 50 t/ha N compared to plants on 10 t/ha N at 3 and 4 weeks after fertilizer application (WAFA). In contrast, plants on 10 t/ha showed higher level of non-photochemical stress due to up regulation of nitric oxide production in PSII [Y(NO)] than plants on 50 t/ha. Non-photochemical quenching due to down regulation of nitric oxide production in PSII [Y(NPQ)] was comparable (P>0.05) in both treatments. There was no significant difference in plant height, although wider stem girth was recorded in plants on 50 t/ha. The significantly higher levels of Y(NO) in plants on 10 t/ha N suggests an alteration in nitrogen metabolism, and increased production of reactive nitrogen species which may potentially cause cellular damage if not diagnosed early and managed adequately.

Livestock manure management, especially related to the soil fertilisation practice, is responsible for most of the emissions in agriculture. These include ammonia emissions (NH₃) which, together with other nitrogen forms such as nitrate ions (NO3-), play a key role in environmental problems, affecting water, soil and air quality. Within the digital agriculture framework, monitoring of manure spreading through Earth Observation data could provide relevant information both to mitigate pollutants emission, and in agricultural practice management. Objective of the activity is to present a GIS-based tool on an Open-Source platform, developed for susceptibility estimation of sewage spreading occurrence in agricultural areas. The tool is based on the analysis of multispectral and hyperspectral satellite time series at various resolutions, in synergy with field data and ancillary information collected from regional repositories, to produce a series of classified and prioritised spatially explicit information. Spectral analysis of satellite acquisitions has been performed, thus enabling the semi-automatic identification of manure spreads through a classification process based on specific indices defined ad hoc; information on most relevant manure sources in the area such as farm and biodigester has been selected. Field campaigns from October to March were carried out to validate the spreading event. Po plain, (wide agricultural region in Italy) has been selected as a case study to demonstrate the ability of the proposed tool in supporting the monitoring of manure spreading. Therefore, a good agreement was found between the results obtained with the susceptibility map, applying the GIS-based tool, and the areas detected.

Tomato (Solanum lycopersicum L), popular vegetable grown in traditional and alternative farming systems, such as agroforestry. The study focuses to assess the impact of insect damage caused by (potato beetle (Leptinotarsa decemlineata), cotton bollworm (Helicoverpa armigera)), fungal infections by (Phytophthora infestans), and wildlife damage from (rabbits (Oryctolagus cuniculus), roe deer (Capreolus capreolus)) on three tomato genotypes, Szentlőrinckáta, ACE55, and Roma. Were grown in random block design with five replicates, on both sides of a hedgerow in Hungary MATE. The plots were situated at five different distances (3m, 6m, 9m, 12m, and 15m) from the hedgerow on both windy and protected sides.

The results indicate the choice of tomato variety had a significant effect on fruit production; ACE55 yielded less healthy green and red fruits compared to Roma and Szentlőrinckáta. Tomato variety, side, and distance significantly influenced insect damage and overall yield in tomato plants. Fungal damage was not serious in 2022 - and was not significantly affected by variety, side, and distance. Potato beetle damage was more prevalent on the protected side, ACE55 had significantly fewer damaged fruits compared to both Roma and Szentlőrinckáta. Wild animal damage was significantly affected by distance from the hedgerow.

Insect damage was higher on the protected side and lower on the windy side of the hedgerow, depending on insects and survey date. Despite higher insect damage, the protected side promoted healthy red and green fruit production, particularly Roma and Szentlőrinckáta.

RuBisCO is the main photosynthetic enzyme of carbon assimilatory pathways in nature. Despite being the most abundant protein on earth, RuBisCO is still relatively underutilized in the food chain. Although having sequence and structure details in the database, studies on evolutionary relationships have few instances. A bioinformatics and in silico study was conducted to check sequence and structural differences of RuBisCO among different photosynthetic organisms. RuBisCO from Oryza sativa showed abundance of charged amino acids, salt-bridges and intra-protein interactions and was more hydrophilic in nature compared to Nostoc sp., Chlamydomonas reinhardtii, and Nicotiana tabacum. From molecular dynamics simulations, lower root mean square deviation and root mean square fluctuation indicate that RuBisCO from Oryza sativa was more stable followed by Nicotiana tabacum and lower radius of gyrations indicates their tightly packing. From this study, it was clear that some specific evolutions in charged amino acids of RuBisCO of monocot i.e., Oryza sativa make it more stable and stronger than other plant groups. The study concludes more stable nature of RuBisCO from monocot Oryza sativa.

Predawn leaf water potential (Ψ_pd), commonly accessed by using a Scholander type pressure chamber, is the main parameter to determine plant water status and it has been largely used to support irrigation management. However, this methodology is laborious, time-consuming and invasive, limiting its usage in mapping the water status of plants in large plantation areas. In this study, a low-cost hyperspectral proximal sensor to estimate Ψ_pd in grapevine (Vitis vinifera L.) was examined. For this, both Ψ_pd and spectral reflectance (340-850 nm) were accessed in grapevines in a commercial vineyard located at Douro Wine Region, northeast Portugal. A machine learning algorithm was tested and validated to assess grapevine water status. The experiment was performed in a randomized design with 12 grapevines (Touriga Nacional) per irrigation treatment, which were: non-irrigated, irrigation to replace 30% evapotranspired (Etc) water volume, and 60% Etc. The Ψ_pd and spectral data were determined weekly over six consecutive weeks, totaling 216 observations. The dataset was analyzed using Principal Component Analysis (PCA), and the machine learning regression algorithm applied was Random Forest (RF). Results from the validation dataset (n = 65 observations) for the RF tested exhibited a root mean square error (RMSE) of 0.25 MPa, mean absolute error (MAPE) of 29.55% and an R² value of 0.94. These results demonstrate that the hyperspectral sensor and RF algorithm can be accurately used to predict Ψ_pd in vineyards regardless of plant water status. This methodology emerges as a tool to assist vineyards producers in making decisions on irrigation management.