Centre for the Research and Technology of Agro-Environmental and Biological Sciences

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Publications

Sewage sludge fertilization—A case study of Sweet Potato yield and heavy metal accumulation

Publication . Ragonezi, Carla; Nunes, Nuno; Oliveira, Maria Cristina O.; Freitas, José G. R. de; Ganança, José Filipe T.; Carvalho, Miguel Â. A. Pinheiro de

Sewage sludge (SS) is derived from wastewater treatment plants and can be used as a biofertilizer when properly stabilized. This work aimed to evaluate SS application for agricultural production improvement. SS was tested on Porto Santo Island (Portugal). The experiment was randomly designed with three 25 m2 plots for each treatment (2 SS concentrations + control without SS) and performed in two consecutive cycles. For the first cycle, dehydrated sludge was mixed with soil, obtaining final concentrations of 0.8 kg/m2 (C1) and 1.6 kg/m2 (C2). Half of the concentration was used for the second cycle. Fifty-eight sweet potato plants were used in each plot. SS application boosted the agronomic parameters of biomass, productivity, and shoot biomass. Furthermore, improvements in soil properties were observed, mainly for pH, CEC, and NO3 -N, with no significant increase in heavy metals. For the edible parts, heavy metal concentrations decreased, and Pb was the only one that still exceeded the maximum limits. The results demonstrated that SS application to low-fertility soil is effective in improving the agronomic parameters of sweet potato and enhancing soil features. Further studies considering other variables, i.e., SS origin, soil properties, and the crop, must be carried out to propose custom applications.

2022Journal article

Open access

Anticipating the Climate Change Impacts on Madeira’s Agriculture: The Characterization and Monitoring of a Vine Agrosystem

Publication . Carvalho, Miguel Â. A. Pinheiro de; Ragonezi, Carla; Oliveira, Maria Cristina O.; Reis, Fábio; Macedo, Fabrício Lopes; Freitas, José G. R. de; Nóbrega, Humberto; Ganança, José Filipe T.

Climate—Madeira Strategy (CMS) foresees two models to describe the climate scenarios for the Madeira region in 2050 and 2070. These scenarios anticipate an average temperature rise of 1.4 to 3.7 ◦C and a decrease in precipitation by 30 to 40%. Consequently, Madeira’s agriculture will suffer the impacts of climate change. To understand these impacts, a baseline of major agrosystem components needs to be established, with the ultimate goal to monitor its consequences in its functioning. CASBio project used the 1961–1991 and 2010–2020 meteorological data series to modulate climate conditions and characterize and monitor six agrosystems for 2 years. One of them was a vineyard, Quinta das Vinhas, representing a typical agrosystem in the Mediterranean climate. The annual and seasonal variation in climatic parameters, soil conditions, microbiological communities, floristic and insect diversity, and crop production was assessed, using a total of 50 parameters. The results were used to establish a baseline of the agrosystem components and their seasonal and annual variation. The major findings are: (i) winter and summer extreme events show a trend in temperature and precipitation supporting a fast change in climate; (ii) a critical imbalance between nitrogen fixing and denitrifying bacteria was identified, especially in summer, that could be determined by the rise in temperature and drought; (iii) among floristic diversity, the therophytes and geophytes confirm to be the most suitable indicators for the rise in temperature and reduction in precipitation in the agrosystems; (iv) an imbalance in favor of C. capitata plague was observed, associated with the summer rise in temperature and decrease in precipitation; (v) despite an increase in most of the grape varieties production, the Madeiran wine local varieties were shown to be less stable in productivity under observed climate conditions. The agrosystem baseline is a starting point for long term monitoring and allows for further quantifying the influence of climate change on agrosystem productivity, resilience, and sustainability.

2022Journal article

Open access

Encapsulation with Natural Polymers to Improve the Properties of Biostimulants in Agriculture

Publication . Jiménez-Arias, David; Morales-Sierra, Sarai; Silva, Patrícia; Carrêlo, Henrique; Gonçalves, Adriana; Ganança, José Filipe Teixeira; Nunes, Nuno; Gouveia, Carla S. S.; Alves, Sónia; Borges, João Paulo; Carvalho, Miguel Â. A. Pinheiro de

Encapsulation in agriculture today is practically focused on agrochemicals such as pes ticides, herbicides, fungicides, or fertilizers to enhance the protective or nutritive aspects of the entrapped active ingredients. However, one of the most promising and environmentally friendly technologies, biostimulants, is hardly explored in this field. Encapsulation of biostimulants could indeed be an excellent means of counteracting the problems posed by their nature: they are easily biodegradable, and most of them run off through the soil, losing most of the compounds, thus becoming inaccessible to plants. In this respect, encapsulation seems to be a practical and profitable way to increase the stability and durability of biostimulants under field conditions. This review paper aims to provide researchers working on plant biostimulants with a quick overview of how to get started with encapsulation. Here we describe different techniques and offer protocols and suggestions for introduction to polymer science to improve the properties of biostimulants for future agricultural applications.

2022Journal article

Open access

Distribution of Genetic Diversity in Beta patula Aiton Populations from Madeira Archipelago, Portugal

Publication . Ragonezi, Carla; Nóbrega, Humberto; Leite, Maria Inês; Freitas, José G. R. de; Macedo, Fabrício Lopes; Carvalho, Miguel Â. A. Pinheiro de

Beta patula Aiton is a crop wild relative (CWR) which belongs to the Gene Pool 1b and is considered a Critically Endangered species, and is present in very specific environments, such as the Desembarcadouro islet (DI) in Ponta de São Lourenço or Chão islet (CI) in the Desertas Islands. The ISOPlexis Center (University of Madeira) has been providing continuous support for its in situ conservation by keeping a management plan of wild populations and an ex situ conservation strategy through the storage of accessions in the ISOPlexis GeneBank. The present work intends to present the spatial distribution of genetic variability and diversity in these B. patula populations using eight polymorphic Simple Sequence Repeat (SSR) markers. The overall results lead to the identification of three spots with a high genetic diversity. CI with a small cluster of individuals shows a genetic footprint different from DI, having unique alleles present in its population. DI has two distinct areas: the western area, with a higher individual density but with a lower genetic diversity and higher allele fixation; and the central area, with a lower individual count but with a higher genetic diversity and with the presence of unique alleles. Despite some genetic differences, the comparison of the two islets’ DI and CI populations shows that they have more similarities than differences. Analysis of the Molecular Variance, based on the hierarchical cluster, showed a 9% diversity between populations, 68% among individuals, and 23% within individuals. This data will be used for the establishment of a protocol to monitor and manage B. patula genetic diversity under a genetic reserve, subsequently contributing to the European Genetic Reserve network implementation and the protection of this important CWR.

2022Journal article

Open access

Estimation of Productivity and Above-Ground Biomass for Corn (Zea mays) via Vegetation Indices in Madeira Island

Publication . Macedo, Fabrício Lopes; Nóbrega, Humberto; Freitas, José G. R. de; Ragonezi, Carla; Pinto, Lino; Rosa, Joana; Carvalho, Miguel A. A. Pinheiro

The advancement of technology associated with the field, especially the use of unmanned aerial vehicles (UAV) coupled with multispectral cameras, allows us to monitor the condition of crops in real time and contribute to the field of machine learning. The objective of this study was to estimate both productivity and above-ground biomass (AGB) for the corn crop by applying different vegetation indices (VIs) via high-resolution aerial imagery. Among the indices tested, strong correlations were obtained between productivity and the normalized difference vegetation index (NDVI) with a significance level of p < 0.05 (0.719), as well as for the normalized difference red edge (NDRE), or green normalized difference vegetation index (GNDVI) with crop productivity (p < 0.01), respectively 0.809 and 0.859. The AGB results align with those obtained previously; GNDVI and NDRE showed high correlations, but now with a significance level of p < 0.05 (0.758 and 0.695). Both GNDVI and NDRE indices showed coefficients of determination for productivity and AGB estimation with 0.738 and 0.654, and 0.701 and 0.632, respectively. The use of the GNDVI and NDRE indices shows excellent results for estimating productivity as well as AGB for the corn crop, both at the spatial and numerical levels. The possibility of predicting crop productivity is an essential tool for producers, since it allows them to make timely decisions to correct any deficit present in their agricultural plots, and further contributes to AI integration for drone digital optimization.

2023Journal article

Open access