Pre- and Postharvest Strategies for Pleurotus ostreatus Mushroom in a Circular Economy Approach

Publisher Copyright: © 2024 by the authors.Mushroom cultivation presents a viable solution for utilizing agro-industrial byproducts as substrates for growth. This process enables the transformation of low-economic-value waste into nutritional foods. Enhancing the yield and quality of preharvest edible mushrooms, along with effectively preserving postharvest mushrooms, stands as a significant challenge in advancing the industry. Implementing pre- and postharvest strategies for Pleurotus ostreatus (Jacq.) P. Kumm (oyster mushroom) within a circular economy framework involves optimizing resource use, minimizing waste, and creating a sustainable and environmentally friendly production system. This review aimed to analyze the development and innovation of the different themes and trends by bibliometric analysis with a critical literature review. Furthermore, this review outlines the cultivation techniques for Pleurotus ostreatus, encompassing preharvest steps such as spawn production, substrate preparation, and the entire mushroom growth process, which includes substrate colonization, fruiting, harvesting, and, finally, the postharvest. While novel methodologies are being explored for maintaining quality and extending shelf-life, the evaluation of the environmental impact of the entire mushroom production to identify areas for improvement is needed. By integrating this knowledge, strategies can be developed for a more sustainable and circular approach to Pleurotus ostreatus mushroom cultivation, promoting environmental stewardship and long-term viability in this industry.publishersversionpublishe

Digitization of crop nitrogen modelling: A review

Applying the correct dose of nitrogen (N) fertilizer to crops is extremely important. The current predictive models of yield and soil–crop dynamics during the crop growing season currently combine information about soil, climate, crops, and agricultural practices to predict the N needs of plants and optimize its application. Recent advances in remote sensing technology have also contributed to digital modelling of crop N requirements. These sensors provide detailed data, allowing for real-time adjustments in order to increase nutrient application accuracy. Combining these with other tools such as geographic information systems, data analysis, and their integration in modelling with experimental approaches in techniques such as machine learning (ML) and artificial intelligence, it is possible to develop digital twins for complex agricultural systems. Creating digital twins from the physical field can simulate the impact of different events and actions. In this article, we review the state-of-the-art of modelling N needs by crops, starting by exploring N dynamics in the soil−plant system; we demonstrate different classical approaches to modelling these dynamics so as to predict the needs and to define the optimal fertilization doses of this nutrient. Therefore, this article reviews the currently available information from Google Scholar and ScienceDirect, using relevant studies on N dynamics in agricultural systems, different modelling approaches used to simulate crop growth and N dynamics, and the application of digital tools and technologies for modelling proposed crops. The cited articles were selected following the exclusion criteria, resulting in a total of 66 articles. Finally, we present digital tools and technologies that increase the accuracy of model estimates and improve the simulation and presentation of estimated results to the manager in order to facilitate decision-making processes

Characterising the agriculture 4.0 landscape - Emerging trends, challenges and opportunities

ReviewInvestment in technological research is imperative to stimulate the development of sustainable solutions for the agricultural sector. Advances in Internet of Things, sensors and sensor networks, robotics, artificial intelligence, big data, cloud computing, etc. foster the transition towards the Agriculture 4.0 era. This fourth revolution is currently seen as a possible solution for improving agricultural growth, ensuring the future needs of the global population in a fair, resilient and sustainable way. In this context, this article aims at characterising the current Agriculture 4.0 landscape. Emerging trends were compiled using a semi-automated process by analysing relevant scientific publications published in the past ten years. Subsequently, a literature review focusing these trends was conducted, with a particular emphasis on their applications in real environments. From the results of the study, some challenges are discussed, as well as opportunities for future research. Finally, a high-level cloud-based IoT architecture is presented, serving as foundation for designing future smart agricultural systems. It is expected that this work will positively impact the research around Agriculture 4.0 systems, providing a clear characterisation of the concept along with guidelines to assist the actors in a successful transition towards the digitalisation of the sectorinfo:eu-repo/semantics/publishedVersio

Current Trends, Challenges, and Future Perspectives

This work was supported in part by the Fundação para a Ciência e a Tecnologia (FCT), Portugal, through the research units UNINOVA-CTS (UIDB/00066/2020), GeoBioTec (UIDP/04035/2020), CEF (UIDB/00239/2020), and the Associate Laboratory TERRA (LA/P/0092/2020). Publisher Copyright: © 2023 by the authors.Progress in agricultural productivity and sustainability hinges on strategic investments in technological research. Evolving technologies such as the Internet of Things, sensors, robotics, Artificial Intelligence, Machine Learning, Big Data, and Cloud Computing are propelling the agricultural sector towards the transformative Agriculture 4.0 paradigm. The present systematic literature review employs the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to explore the usage of Machine Learning in agriculture. The study investigates the foremost applications of Machine Learning, including crop, water, soil, and animal management, revealing its important role in revolutionising traditional agricultural practices. Furthermore, it assesses the substantial impacts and outcomes of Machine Learning adoption and highlights some challenges associated with its integration in agricultural systems. This review not only provides valuable insights into the current landscape of Machine Learning applications in agriculture, but it also outlines promising directions for future research and innovation in this rapidly evolving field.publishersversionpublishe

Measuring the Influence of Key Management Decisions on the Nitrogen Nutritional Status of Annual Ryegrass-Based Forage Crops

Publisher Copyright: © 2024 by the authors. The APC was funded by national funds through the Fundação para a Ciência e a Tecnologia, I.P. (Portuguese Foundation for Science and Technology) by the project UIDB/05064/2020 (VALORIZA—Research Centre for Endogenous Resource Valorization) and by national funds from Fundação para a Ciência e a Tecnologia (FCT), Portugal, through the research unit UIDP/04035/2020 (GeoBioTec).Increasing nitrogen use efficiency (NUE) by improving agricultural practices and soil knowledge, and implementing precision agriculture, is essential to reduce the overuse of fertilizers and increase nutrient retention. This study aimed to optimize N management in agriculture by establishing a critical N dilution curve (CNDC) and analyzing variations in NUE and the N nutrition index (NNI) among different crops under various treatments. Using a Bayesian model, the CNDC was determined as %Nc = 3.63 × PDM−0.71. The results showed that plant dry matter (PDM) and plant N content (PNC) varied significantly with crop type and sampling moments. Strong positive correlations are presented by PDM with N uptake (NUp) (0.89) and NNI (0.88), along with an inverse correlation with critical N concentration (−0.95). The study found that crops under irrigation conditions had higher NUp and higher NNI. This study provides valuable insights into the influence of key management decisions on the N nutritional status of annual ryegrass-based forage crops. The results highlight the critical role of accurate and conscious decision-making in improving NUE and crop yields, emphasizing the complex interactions between biomass production and N dynamics in crops. The conclusions allow significant benefits to be realized, contributing to the sustainability of agricultural systems.publishersversionpublishe

Elemental Composition of Commercial Herbal Tea Plants and Respective Infusions

Funding Information: Funding: This work received funding support from national funds from Fundação para a Ciência e a Tecnologia, I.P. (FCT), Portugal, through the research units UIDB/04035/2020 (GeoBioTec) and UIDB/00239/2020 (CEF). Publisher Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland.This study evaluated the elemental composition of 25 herbal tea plants commonly used in infusions by Portuguese consumers and the contribution to the elemental daily intake of some essential elements. Hydrocotyle asiatica (L.), Matricaria chamomilla (L.), and Melissa officinalis (L.) samples are a rich source of K with around 6.0 mg g−1 while the Asteraceae Silybum marianum (L.) and Echinacea angustifolia (DC.) exhibited 4.9 and 5.6 mg g−1 Ca, respectively. The highest concentrations of S and Zn were noted in Hydrocotyle asiatica (L.), while the highest concentration of Sr was found in Cassia angustifolia (Vahl.). In general, a large variability in the concentrations among different families and plant organs had been observed, except Cu with levels around 30 µg g−1. The principal component analysis (PCA) showed positive correlations between Zn and S and Sr and Ca, also revealing that Hydrocotyle asiatica (L.), Echinacea angustifolia (DC.), Silybum marianum (L.), and Cassia angustifolia (Vahl.) samples, stands out about all other samples regarding the enrichment of macro and micronutrients. The elemental solubility of macronutrients in the infusion is greater than the micronutrient solubility, despite the contribution to the recommended daily intake was weak. As a whole, Cynara scolymus (L.) and Hibiscus sabdariffa (L.) are the species with the best elemental solubilities, followed by Hydrocotyle asiatica (L.). No harmful elements, such as As and Pb, were observed in both the raw material and the infusions.publishersversionpublishe

Production and characterization of green and black olive paste using cream of animal and vegetable origins

Now-a-days the quest for foods with high flavonoid polyphenols content, lower fat concentration and relative high proportion of monounsaturated or polyunsaturated fatty acids is increasing. Following this tendency green and black olive pastes applying soy cream or cream of animal origin were produced equating a subsequent industrial output, and the rheological, physicochemical and sensory characteristics of were characterized. It was found that the cohesiveness, adhesiveness and hardness of the black olive paste having cream of animal origin showed minimal values. Among samples the moisture varied between 67.15 -72.16% and the inorganic residue of the black olive pastes were also significantly lower from the green olive pastes. Minimum and maximum pH values were measured in green olive paste having soy cream and black paste with cream of animal origin, respectively. The crude fat showed significant differences among the olive pastes, whereas the protein content did not vary significantly. The colour of the black paste with cream of animal origin and soy were slightly orange, whereas the green paste remained green. The sensory analysis of the black olive paste including cream of animal origin showed lower average values for consistency and appearance attributes but the opposite occurred with the salty taste and overall assessment. Concerning to the aroma, the black olive pastes showed the highest values, while the green olive pastes kept similar values. It is concluded that the higher pH of the black olive pastes in conjunction with the water contents limits the shelf life and clearly pointed the need a careful microbial control. Considering that the colour parameters of a food is the first contact point of the consumer, these descriptors in the green olive pastes also seemed to have better acceptance, whereas preferences did not followed healthy options

Elemental Composition of Commercial Herbal Tea Plants and Respective Infusions

This study evaluated the elemental composition of 25 herbal tea plants commonly used in infusions by Portuguese consumers and the contribution to the elemental daily intake of some essential elements. Hydrocotyle asiatica (L.), Matricaria chamomilla (L.), and Melissa officinalis (L.) samples are a rich source of K with around 6.0 mg g-1 while the Asteraceae Silybum marianum (L.) and Echinacea angustifolia (DC.) exhibited 4.9 and 5.6 mg g-1 Ca, respectively. The highest concentrations of S and Zn were noted in Hydrocotyle asiatica (L.), while the highest concentration of Sr was found in Cassia angustifolia (Vahl.). In general, a large variability in the concentrations among different families and plant organs had been observed, except Cu with levels around 30 g g-1. The principal component analysis (PCA) showed positive correlations between Zn and S and Sr and Ca, also revealing that Hydrocotyle asiatica (L.), Echinacea angustifolia (DC.), Silybum marianum (L.), and Cassia angustifolia (Vahl.) samples, stands out about all other samples regarding the enrichment of macro and micronutrients. The elemental solubility of macronutrients in the infusion is greater than the micronutrient solubility, despite the contribution to the recommended daily intake was weak. As a whole, Cynara scolymus (L.) and Hibiscus sabdariffa (L.) are the species with the best elemental solubilities, followed by Hydrocotyle asiatica (L.). No harmful elements, such as As and Pb, were observed in both the raw material and the infusionsinfo:eu-repo/semantics/publishedVersio

Development of a functional dark chocolate with baobab pulp

In recent years, cocoa and dark chocolate have attracted the interest of consumers not only for their sensory characteristics but also for their nutritional properties and positive impact on health. The baobab is a fruit of African origin with a sour and slightly sweet flavour, widely consumed by local communities due to its unique nutritional features. The aim of this work was to evaluate the impact of the concentration of baobab flour in the development of functional dark chocolate, including physical, chemical, nutritional and sensory evaluations. The results presented a positive correlation between the incorporation of baobab flour and the antioxidant activity (up to 2297 mmol TE/100 g), vitamin C content (up to 49.7 mg/100 g), calcium (up to 1052 mg/kg), potassium (up to 10,175 mg/kg), phosphorus (up to 795.9 mg/kg), chlorine (up to 235.4 mg/kg) and sulphur (up to 1158 mg/kg). The sensory evaluation of dark chocolate with 3% baobab presented the highest evaluation on the parameters “texture” and “overall flavour”, while the parameter “overall flavour” presented the lowest evaluation on chocolate with 9% baobab. No influence was observed on fatty acid profile, protein, fat and hardness