Quality characteristics of fillets of rainbow trout fed acid or re-esterified rapeseed oils as dietary fat sources

Alternatives to the use of native vegetable oils (VO) as fish oil (FO) replacers in aqua feeds were evaluated. Acid oils are a free fatty acid (FFA)-rich by-product mainly from the refining of VO. Re-esterified oils are the final product of a chemical esterification reaction between acid oils and glycerol, and have less FFA and more monoand diacylglycerols (MAG and DAG), known for being good emulsifiers, than crude VO. Therefore, they could have a higher nutritive value than that of the native and acid oils. In two earlier studies in rainbow trout (Trullàs et al., 2015, 2016), diets including acid and/or re-esterified VO resulted in total fatty acid apparent digestibility coefficients above 95%. Moreover, no negative effects on growth, plasma biochemical parameters and morphology of tissues were observed when compared to the native oil diet. For all these reasons, the present study aimed at assessing their effects on the final quality of fillets of rainbow trout. Triplicate groups of rainbow trout were fed eight experimental diets containing 15% of different types of experimental rapeseed oils in addition to 5% of FO during 72 days. The experimental rapeseed oils were native (RNO), acid (RAO), re-esterified (REO), or blends (66% RN-33% RAO/33% RN-66% RAO or 66% REO-33% RAO/33% REO-66% RAO). Commercial FO was used for the control diet (F). The colorimetric analysis resulted in significant differences only in b* and C* in both fresh and thawed fillets, as well as in significant correlations between the colorimetric parameters among diets. For the total fat content, fillets of fish fed the control diet obtained the highest values, which were higher than those of fish fed diets containing RNO and the blend 66% REO-33% RAO. No differences in texture, liquid holding capacity, and TBARS were found among fillets of fish fed the different diets. Regarding tocopherol concentrations in fillets, α-tocopherol was significantly higher (P < 0.05) in fillets of fish fed the control diet than in those fed RA/RE, while β + γ-tocopherol was significantly lower in fillets of fish fed C than in the rest. Even though the aforementioned differences were found, they did not seem to be relevant concerning the final quality of fille

Evaluation of Riparian Tree Cover and Shading in the Chauga River Watershed Using LiDAR and Deep Learning Land Cover Classification

River systems face negative impacts from development and removal of riparian vegetation that provide critical shading in the face of climate change. This study used supervised deep learning to accurately classify the land cover, including shading, of the Chauga River watershed, located in Oconee County, South Carolina, for 2011 and 2019. The study examined the land cover differences along the Chauga River and its tributaries, inside and outside the Sumter National Forest. LiDAR data were incorporated in solar radiation calculations for the Chauga River inside and outside the National Forest. The deep learning classifications produced land cover maps with high overall accuracy (97.09% for 2011; 97.58% for 2019). The most significant difference in land cover was in tree cover in the 50 m buffer of the tributaries inside the National Forest compared to the tributaries outside the National Forest (2011: 95.39% vs. 81.84%, 2019: 92.86% vs. 82.06%). The solar radiation calculations also confirmed a difference between the area inside and outside the National Forest, with the mean temperature being greater outside the protected area (outside: 455.845 WH/m2; inside: 416,770 WH/m2). This study suggests that anthropogenic influence in the Chauga River watershed is greater in the areas outside the Sumter National Forest, which could cause damage to the river ecosystem if left unchecked in the future as development pressures increase. This study demonstrates the accurate application of deep learning for high-resolution classification of river shading combined with the use of LiDAR data to estimate solar radiation reaching the Chauga River. Techniques to monitor riparian zones and shading at high spatial resolutions are critical for the mitigation of the negative impacts of warming climates on aquatic ecosystems

Effect of guar gum on the physicochemical, thermal, rheological and textural properties of green edam cheese

In attempts to produce a low-fat cheese with a rheology and texture similar to that of a full-fat cheese, guar gum (within 0.0025–0.01%; w/v, final concentration) was added to low-fat milk. The obtained cheeses were characterised regarding their physicochemical, thermal, rheological and textural properties. Control cheeses were also produced with low and full-fat milk. The physicochemical properties of the guar gum modified cheeses were similar to those of the low-fat control. No significant differences were detected in the thermal properties (concerning the enthalpy and profile of water desorption) among all types of cheeses. The rheological behaviour of the 0.0025% modified cheese was very similar to the full-fat control. Overall, no trend was observed in the texture profile (hardness, cohesiveness, gumminess and elasticity) of the modified cheeses versus guar gum concentration, as well as in comparison with the control groups, suggesting that none of the studied polysaccharide concentrations simulated the textural functions of fat in Edam cheese

The AutoICE Challenge

Mapping sea ice in the Arctic is essential for maritime navigation, and growing vessel traffic highlights the necessity of the timeliness and accuracy of sea ice charts. In addition, with the increased availability of satellite imagery, automation is becoming more important. The AutoICE Challenge investigates the possibility of creating deep learning models capable of mapping multiple sea ice parameters automatically from spaceborne synthetic aperture radar (SAR) imagery and assesses the current state of the automatic-sea-ice-mapping scientific field. This was achieved by providing the tools and encouraging participants to adopt the paradigm of retrieving multiple sea ice parameters rather than the current focus on single sea ice parameters, such as concentration. The paper documents the efforts and analyses, compares, and discusses the performance of the top-five participants’ submissions. Participants were tasked with the development of machine learning algorithms mapping the total sea ice concentration, stage of development, and floe size using a state-of-the-art sea ice dataset with dual-polarised Sentinel-1 SAR images and 22 other relevant variables while using professionally labelled sea ice charts from multiple national ice services as reference data. The challenge had 129 teams representing a total of 179 participants, with 34 teams delivering 494 submissions, resulting in a participation rate of 26.4 %, and it was won by a team from the University of Waterloo. Participants were successful in training models capable of retrieving multiple sea ice parameters with convolutional neural networks and vision transformer models. The top participants scored best on the total sea ice concentration and stage of development, while the floe size was more difficult. Furthermore, participants offered intriguing approaches and ideas that could help propel future research within automatic sea ice mapping, such as applying high downsampling of SAR data to improve model efficiency and produce better results

Impact of the Strong Republic Nautical Highway on the movement of selected agricultural products in the Philippines

The Philippines is an archipelago of approximately 7,107 islands. It has a long coastline that extends to 36,289 kilometers. One of the persistent issues raised by shippers was the high cost of transport from Mindanao to Manila. Among others, Roll-on/roll-off (Ro-Ro) shipping was proposed as a solution to the transport problem. In 2003 the Strong Republic Nautical Highway (SRNH) was formally launched and consists of three main nautical highways: the Western Nautical Highway, the Central Nautical Highway and the Eastern Nautical Highway. Currently, only the Western Nautical Highway is analyzed in this study since it is the only operational network in the SRNH. After the integration of the nautical highway system, many areas were developed, the inter-island shipping industry was restructured, transportation costs were reduced, tourism was enhanced, and logistics operations and strategy of industries were changed. This study identified and assessed the impact of the SNRH on the movement of perishable agricultural goods specifically palay and banana, from Mindanao to Manila. The movement of the goods (banana and palay) is evaluated based on the production and consumption of each region. The evaluation of the cost for each trip and trip distribution were analyzed using operations research (optimization), transportation model, and transshipment model through the EMME program. Considering trucks and jeepneys via RORO, and long haul via conventional shipping, results showed that as the distance increases, the unit cost of transporting via RORO also increases. Results of the simulation show that transporting banana and palay via RORO remain to be more cost effective than moving them via long-haul shipping over short distances

Effects of forage to concentrate ratio in dairy ewes in early-lactation: 2. Milk fatty acid profile and cheese-yielding traits

Póster presentado al: 2017 ADSA Annual Meeting #T292. Pittsburgh, Pennsylvania (Estados Unidos), 25-28 de junio de 2017.As the second part of the study reported by Elhadi et al. (Abstract M331),the effects of forage:concentrate ratio (F:C, %) were studied in 72 dairyewes (Manchega, MN, n = 36; Lacaune, LC, n = 36) in early lactation.Treatments were: high- (HF, 70:30), medium- (MF, 55:45) and low-forage(LF, 40:60). Ewes were fed indoors, in pens of 6, the HF diet during 4 wkand then the experimental diets (wk 5 to 8). Milk was sampled individuallyon wk 7 for composition (NIR system; Foss, Nordersted, DE) andcoagulation traits (Optigraph; Ysebaert, Frepillon, FR). Tank milk sampleswere collected by group and fat extracted (2000 × g, 15 min, 4°C) andconverted to FAME by base catalyzed transesterification for FA analysis bygas- chromatography. Milk composition varied by breed, being richer formain components in MN than in LC (P 16 increased in the LC (2%; P = 0.031),whereas C > 16 and C16 decreased (−2% and −5%, respectively; P <0.05) and C < 16 increased, in the MN (6%; P = 0.010). Changes inatherogenicity index were negligible. No effect of concentrate was detectedon rennet coagulation time, rate of curd aggregation and laboratory cheeseyieldin both breeds (P = 0.95 to 0.052), except for firmness at min 45 andrate of curd aggregation, that increased (23% and 47%, respectively; P <0.05) in the HF vs. MF comparison in MN ewes. In conclusion, slightchanges in FA profile, and no benefits in cheese traits, were detected whenthe ratio forage:concentrate fell below the level required to satisfy thenutrition requirements of medium and high yielding dairy ewes.Peer reviewe