Flexitarians have reduced their meat consumption showing a rising interest in plant-based meat alternatives with 'meaty' characteristics, and we are witnessing an unprecedented growth of meat ...substitutes in the Western market. However, to our knowledge, no information regarding the 'simulated beef burgers' nutritional profile compared to similar meat products has been published yet. Here we show that, whilst both plant-based and meat-based burgers have similar protein profile and saturated fat content, the former are richer in minerals and polyunsaturated fatty acids. We found that the most abundant minerals in both categories were Na, K, P, S, Ca, and Mg; being Na and S content similar between groups. Only six amino acids differed between categories, being hydroxyproline exclusively in meat-based burgers. Plant-based burgers revealed fourfold greater content of n-6 than meat-based burgers, and greater short-chain fatty acids proportion. Our results demonstrate how 'simulated beef' products may be authenticated based on some specific nutrients and are a good source of minerals. We believe that there is a need to provide complete and unbiased nutritional information on these 'new' vegan products so that consumers can adjust their diet to nutritional needs.
Although organic farming and agroecology are normally not associated with the use of new technologies, it’s rapid growth, new technologies are being adopted to mitigate environmental impacts of ...intensive production implemented with external material and energy inputs. GPS, satellite images, GIS, drones, help conventional farming in precision supply of water, pesticides, fertilizers. Prescription maps define the right place and moment for interventions of machinery fleets. Yield goal remains the key objective, integrating a more efficient use or resources toward an economic-environmental sustainability. Technological smart farming allows extractive agriculture entering the sustainability era. Societies that practice agroecology through the development of human-environmental co-evolutionary systems represent a solid model of sustainability. These systems are characterized by high-quality agroecosystems and landscapes, social inclusion, and viable economies. This book explores the challenges posed by the new geographic information technologies in agroecology and organic farming. It discusses the differences among technology-laden conventional farming systems and the role of technologies in strengthening the potential of agroecology. The first part reviews the new tools offered by geographic information technologies to farmers and people. The second part provides case studies of most promising application of technologies in organic farming and agroecology: the diffusion of hyperspectral imagery, the role of positioning systems, the integration of drones with satellite imagery. The third part of the book, explores the role of agroecology using a multiscale approach from the farm to the landscape level. This section explores the potential of Geodesign in promoting alliances between farmers and people, and strengthening food networks, whether through proximity urban farming or asserting land rights in remote areas in the spirit of agroecological transition. The Open Access version of this book, available at www.taylorfrancis.com, has been made available under a Creative Commons 4.0 license.
The list of standard abbreviations for JDS is available at adsa.org/jds-abbreviations-24. Nonstandard abbreviations are available in the Notes.
Portable infrared-based instruments have made important ...contributions in different research fields. Within the dairy supply chain, for example, most of portable devices are based on near-infrared spectroscopy (NIRS) and are nowadays an important support for farmers and operators of the dairy sector, allowing fast and real-time decision-making, particularly for feed and milk quality evaluation and animal health and welfare monitoring. The affordability, portability, and ease of use of these instruments have been pivotal factors for their implementation on farm. In fact, pocket-sized devices enable nonexpert users to perform quick, low-cost, and nondestructive analysis on various matrixes without complex preparation. Because bovine colostrum (BC) quality is mostly given by the IgG level, evaluating the ability of portable NIRS tools to measure antibody concentration is advisable. In this study we used the wireless device SCiO manufactured by Consumer Physics Inc. (Tel Aviv, Israel) to collect BC spectra and then attempt to predict IgG concentration and gross and fine composition in individual samples collected immediately after calving (<6 h) in primiparous and pluriparous Holstein cows on 9 Italian farms. Chemometric analyses revealed that SCiO has promising predictive performance for colostral IgG concentration, total Ig concentration, fat, and AA. The coefficient of determination of cross-validation (R2CV) was in fact ≥0.75). Excellent accuracy was observed for dry matter, protein, and S prediction in cross-validation and good prediction ability in external validation (R2CV ≥ 0.93; the coefficient of determination of external validation, R2V, was ≥0.82). Nonetheless, SCiO's ability to discriminate between good- and low-quality samples (IgG ≥ vs. < 50 g/L) was satisfactory. The affordable cost, the accurate predictions, and the user-friendly design, coupled with the increased interest in BC within the dairy sector, may boost the collection of extensive BC data for management and genetic purposes in the near future.
Abstract
Despite the ongoing impacts of climate change around the world, fossil fuels continue to drive the global economy. The socio-environmental impacts of oil development at the local level are ...widely recognized, especially in high biocultural diversity areas, highlighting the need to develop and implement effective policies that protect both biodiversity and human rights. In consideration of the estimated remaining carbon budget to limit global warming at 1.5 °C, as well as Ecuador’s past attempts at limiting carbon extraction through the Yasuni-ITT Initiative, we adopt a new framework to identify ‘unburnable carbon areas’ with the goal of eventually phasing out fossil fuels. In the Ecuadorian Amazon—one of Earth’s high-biodiversity wilderness areas and home to uncontacted indigenous populations—50 years of widespread oil production is jeopardizing tropical ecosystems. Using the Ecuadorian Amazon as a paradigmatic case study, our research explores the feasibility of implementing energy transition paths based on unburnable carbon areas through spatial multicriteria decision analysis that is based on different approaches to territory management. We modeled interactions between oil development and areas with high biocultural sensitivities using environmental, socio-cultural, and oil-related geospatial information. We found that, for all simulations, concessions that should remain unburnable are mainly located in the south-central sector of Ecuadorian Amazon, surrounding the Yasuní National Park and the intangible zone for uncontacted indigenous people, where no reserves have been identified and oil infrastructure (wells, pipelines, etc) has not been deployed. In the Northern sector, particularly along the ‘Auca’ oil road system, the eventual continuation of fossil production requires best practices to minimize environmental impacts and respect human rights. Our spatial multicriteria approach based on geographical criteria can be replicated in different place contexts to explore different scenarios for effective climate mitigation policies.
The western Amazon is one of the world's last high-biodiversity wilderness areas, characterized by extraordinary species richness and large tracts of roadless humid tropical forest. It is also home ...to an active hydrocarbon (oil and gas) sector, characterized by operations in extremely remote areas that require new access routes. Here, we present the first integrated analysis of the hydrocarbon sector and its associated road-building in the western Amazon. Specifically, we document the (a) current panorama, including location and development status of all oil and gas discoveries, of the sector, and (b) current and future scenario of access (i.e. access road versus roadless access) to discoveries. We present an updated 2014 western Amazon hydrocarbon map illustrating that oil and gas blocks now cover 733 414 km2, an area much larger than the US state of Texas, and have been expanding since the last assessment in 2008. In terms of access, we documented 11 examples of the access road model and six examples of roadless access across the region. Finally, we documented 35 confirmed and or suspected untapped hydrocarbon discoveries across the western Amazon. In the Discussion, we argue that if these reserves must be developed, use of the offshore inland model-a method that strategically avoids the construction of access roads-is crucial to minimizing ecological impacts in one of the most globally important conservation regions.
The aim of the present study was to investigate the ability of a handheld near-infrared spectrometer to predict total and gelatinized starch, insoluble fibrous fractions, and mineral content in ...extruded dry dog food. Intact and ground samples were compared to determine if the homogenization could improve the prediction performance of the instrument. Reference analyses were performed on 81 samples for starch and 99 for neutral detergent fiber (NDF), acid detergent fiber (ADF), acid detergent lignin (ADL), and minerals, and reflectance infrared spectra (740 to 1070 nm) were recorded with a SCiO™ near-infrared (NIR) spectrometer. Prediction models were developed using modified partial least squares regression and both internal (leave-one-out cross-validation) and external validation. The best prediction models in cross-validation using ground samples were obtained for gelatinized starch (residual predictive deviation, RPD = 2.54) and total starch (RPD = 2.33), and S (RPD = 1.92), while the best using intact samples were obtained for gelatinized starch (RPD = 2.45), total starch (RPD = 2.08), and K (RPD = 1.98). Through external validation, the best statistics were obtained for gelatinized starch, with an RPD of 2.55 and 2.03 in ground and intact samples, respectively. Overall, there was no difference in prediction models accuracy using ground or intact samples. In conclusion, the miniaturized NIR instrument offers the potential for screening purposes only for total and gelatinized starch, S, and K, whereas the results do not support its applicability for the other traits.
Of late, “A2 milk” has gained prominence in the dairy sector due to its potential implications in human health. Consequently, the frequency of A2 homozygous animals has considerably increased in many ...countries. To elucidate the potential implications that beta casein (β-CN) A1 and A2 may have on cheese-making traits, it is fundamental to investigate the relationships between the genetic polymorphisms and cheese-making traits at the dairy plant level. Thus, the aim of the present study was to evaluate the relevance of the β-CN A1/A2 polymorphism on detailed protein profile and cheese-making process in bulk milk. Based on the β-CN genotype of individual cows, 5 milk pools diverging for presence of the 2 β-CN variants were obtained: (1) 100% A1; (2) 75% A1 and 25% A2; (3) 50% A1 and 50% A2; (4) 25% A1 and 75% A2; and (5) 100% A2. For each cheese-making day (n = 6), 25 L of milk (divided into 5 pools, 5 L each) were processed, for a total of 30 cheese-making processes. Cheese yield, curd nutrient recovery, whey composition, and cheese composition were assessed. For every cheese-making process, detailed milk protein fractions were determined through reversed-phase HPLC. Data were analyzed by fitting a mixed model, which included the fixed effects of the 5 different pools, the protein and fat content as a covariate, and the random effect of the cheese-making sessions. Results showed that the percentage of κ-CN significantly decreased up to 2% when the proportion of β-CN A2 in the pool was ≥25%. An increase in the relative content of β-CN A2 (≥50% of total milk processed) was also associated with a significantly lower cheese yield both 1 and 48 h after cheese production, whereas no effects were observed after 7 d of ripening. Concordantly, recovery of nutrients reflected a more efficient process when the inclusion of β-CN A2 was ≤75%. Finally, no differences in the final cheese composition obtained by the different β-CN pools were observed.
The pet food industry is interested in performing fast analyses to control the nutritional quality of their products. This study assessed the feasibility of near-infrared spectroscopy to predict ...mineral content in extruded dry dog food. Mineral content in commercial dry dog food samples (
= 119) was quantified by inductively coupled plasma optical emission spectrometry and reflectance spectra (850-2500 nm) captured with FOSS NIRS DS2500 spectrometer. Calibration models were built using modified partial least square regression and leave-one-out cross-validation. The best prediction models were obtained for S (coefficient of determination
= 0.89), K (
= 0.85), and Li (
= 0.74), followed by P, B, and Sr (
= 0.72 each). Only prediction models for S and K were adequate for screening purposes. This study supports that minerals are difficult to determine with NIRS if they are not associated with organic molecules.
This study evaluated the potential use of mid-infrared spectroscopy to predict milk coagulation traits in bulk milk from Mediterranean Italian buffaloes. A total of 1736 bulk milk samples from 55 ...farms in central Italy were collected during the official milk quality testing system. The prediction models were developed based on modified partial least-squares regression with 75% of the samples and validated with the remaining samples. All bulk milk samples coagulated between 7.37 and 29.45 min. Average values for milk coagulation traits in the calibration set were 17.71 min, 3.29 min, and 38.83 mm for rennet coagulation time, curd firming time, and curd firmness, respectively. The validation set included samples with similar mean and standard deviation for each trait. The prediction models showed the greatest coefficient of determination of external validation (0.57) and the ratio of prediction to deviation (1.52) for curd firmness. Similar fitting statistics of the prediction models were obtained for rennet coagulation time and curd firming time. In conclusion, the prediction models for all three coagulation traits were below the threshold to consider the prediction models adequate even for rough screening of the samples.
Recent GIS technologies are shaping the direction of Precision Agriculture and Viticulture. Sentinel-2 satellites and UAVs are key resources for multi-spectral analyses of vegetation. Despite being ...extensively adopted in numerous applications and scenarios, the pros and cons of both platforms are still debated. Researchers have currently investigated different aspects of these sources, mainly comparing different vegetation indexes and exploring potential relationships with agronomic variables. However, due to the costs and limitations of such an approach, a standardized methodology for agronomic purposes is still missing. This study aims to fill such a methodology gap by overcoming the potential flaws or shortages of previous works. To achieve this, an image acquisition campaign covering 6 months and over 17 hectares was carried out, followed by an NDVI comparison between Sentinel-2 and UAV to eventually explore relationships with agronomic variables. Comparative analyses were performed by using both classical (Ordinary Least Squares regression and Pearson Correlation) and spatial (Moran’s Index) statistical approaches: here, 90% of cases show r and MI scores above 0.6 for plain images, with these scores expectedly lowering to 72% and 52% when considering segmented images. Moreover, NDVI thematic maps were classified into clusters and validated by the Chi-squared test. Finally, the relationship and distribution of agronomic variables within NDVI and clustered maps were consistently validated through the ANOVA test. The proposed open-source pipeline allows to strengthen existing UAV and satellite applications in Precision Agriculture by integrating more agronomic variables.
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