AIMS Agriculture and Food最新文献

Pescabivona is a highly appreciated fruit by consumers for its sweet flavour and juicy flesh; however, it has a short shelf life and is susceptible to postharvest damage, such as mechanical injury, loss of texture and alteration of organoleptic properties. Therefore, it's necessary to develop new methods of processing and conservation for this fruit. The aim of this study was to analyse the effects of tray-drying in white peach slices and cubes at 70 ℃ for 12 hours in order to extend their shelf-life and increase its commercial availability over a long period and to obtain a new food product. The physicochemical and sensory properties of dried fruits were assessed during 30 days of storage in polyamide/polyethene (PA/PE) bags containing two gas mixtures (treatments): MAP-N₂ (100% N₂) and MAP-P (78% N₂, 21% O₂ and 0.04% CO₂), at room temperature (20 ± 1 ℃). Both MAP treatments kept the fruit firmness, with MAP-P slightly more effective. Slicing produced fruit with a good appearance and firmness, while cubing produced sweet fruit with a caramel flavour and a chewier firmness. In addition, packing with MAP-N₂ reduced the phenomenon of fruit browning. Overall, this study provides significant information on the drying process (time-temperature treatments) and packaging techniques (MAP) of white-fleshed peach to obtain a novel food product.

Sulfur dioxide is generally used in wine and vinegar production. It is employed to decrease the bacteria' growth, improve the wines' aroma (since it supports the extraction of polyphenols during maceration), protect the wines from chemical oxidation and the musts from chemical and enzymatic oxidation (blocking free radicals and oxidase enzymes such as tyrosinase and laccase). The composition and storage conditions (i.e., pH, temperature, and alcohol levels) affect oenological results. In various countries, competent authorities have imposed legal limits since it can have toxic effects on humans. It is crucial to dose SO₂ levels to allow vinegar production and compliance with legal limits. The iodometric titration named "Ripper test" is the legal method used to dose it in vinegar. In this work, an automatized colorimetric test was validated using the international guidelines ISO/IEC (2017) to allow its use instead of the Ripper test. The test reliability was verified on white, red, and balsamic vinegar with low or high SO₂ content. The automatized test showed linearity, precision, and reproducibility similar to the Ripper test, but the accuracy parameter was not respected for the vinegar with a low concentration of SO₂. Therefore, the automatized colorimetric test can be helpful to dose SO₂ in vinegar with high concentrations of SO₂.

Anther culture is a widely utilized technique in rice breeding because of its simplicity and effectiveness in rapidly obtaining pure lines in the form of doubled haploid plants. The selection of doubled haploid (DH) rice lines derived from anther culture in advanced yield trials is an important step for obtaining superior DH lines. We aimed to determine agronomic performance, including yield and yield stability in order to select lowland DH rice lines that are high yield and have good agronomic performance based on the selection index method. The research was conducted in Indonesia at three locations, i.e., Bogor (West Java), Indramayu (West Java) and Malang (East Java) from July to December 2022. The genotypes tested were 29 DH lines and three check varieties (Inpari-42 Agritan GSR, Inpari-18 Agritan and Bioni63 Ciherang Agritan) using a randomized complete block design (RCBD) with genotypes as a single factor and three replications. High heritability values are found in all agronomic characters, except the percentage of filled grain/panicle, the percentage of empty grain/panicle and productivity. The yield stability based on the Kang method showed that 15 lines were stable and had high productivity. Phenotypic correlation analysis showed that the number of productive tillers, days to flowering, days to harvesting, number of filled grains/panicle and percentage of filled grains all had positive values and significantly correlated with productivity. Phenotypic path analysis showed that the character of days to harvesting, number of filled grains/panicle, number of productive tillers and percentage of filled grains/panicle directly affected the productivity. Based on the weighted selection index, 12 DH lines were selected due to having a positive and higher index (8.54 to 0.28) than the Bioni63 Agritan and Inpari 18 check varieties. Among those lines, 9 DH lines were also stable based on the Kang Method.

Banana is a highly nutrient-dense, widely produced and consumed tropical fruit. Luvhele and mabonde non-commercial unripe banana cultivars were used to produce the flour and substituted the wheat flour at four levels (10%, 20%, 30% and 40%) for dough production. The water and oil holding capacity of the blended flour samples and the pH, titratable acidity, leavening capacity, proximate composition and texture of the dough were determined. Incorporation of Luvhele and Mabonde flour improved the blended flours' water and oil holding capacity. At 0 min and level 40%, the pH of the dough sample decreased from 5.79 (control) to 5.27 in both banana cultivars. The volume of the dough decreased from 195.00 mL (control) at 30 min to 128.33 mL (luvhele) and 125.00 mL (mabonde), respectively. The proximate composition of the blended dough increased in terms of ash, fiber, fat and carbohydrate. However, a decrease in protein and moisture contents at p < 0.05 was also observed. The hardness of the dough increased significantly with increased amounts of unripe banana flour substitutions. On the other hand, the control sample recorded a high cohesiveness (1.22). Doughs added with mabonde flour recorded high adhesion. The results of this work demonstrate that non-commercial unripe banana flour can be used as an alternative functional component for baked products with improved nutritional value.

Ecuador has a significant genetic diversity of maize, which comes in different shapes, sizes and colors and plays a crucial role in food security. This research aimed to evaluate the physicochemical parameters of the extrusion process of two improved maize varieties (INIAP-176 and INIAP-180). The factors under study were two temperatures (140 ℃ and 150 ℃) and two screw speeds (230 rpm and 280 rpm). The applied extrusion conditions showed significant effects on the nutritional content, functional properties, texture attributes and sensory acceptability. The extruded products presented average values of 2.64% moisture, 0.61% ash, 8.54% protein, 0.61% ether extract, 1.55% crude fiber and 88.70 g/100 g were nitrogen-free extract (NFE) about dry weight of sample. Also, extrusion of the two maize varieties at a temperature of 150 ℃ and a screw speed of 280 rpm recorded high values of the expansion index and low levels of bulk density for functional properties. Instrumental texture analysis determined that the best attributes expressed as hardness, fracturability and adhesiveness in the expanded maize obtained from INIAP-176 at a speed of 280 rpm. The application of extrusion in these improved maize varieties allowed the production of high-quality snacks for the consumer.

Coffee is a major industrial crop that creates high economic value in Thailand and other countries worldwide. A lack of certainty in forecasting coffee production could lead to serious operation problems for business. Applying machine learning (ML) to coffee production is crucial since it can help in productivity prediction and increase prediction accuracy rate in response to customer demands. An ML technique of artificial neural network (ANN) model, and a statistical technique of autoregressive integrated moving average (ARIMA) model were adopted in this study to forecast arabica coffee yields. Six variable datasets were collected from 2004 to 2018, including cultivated areas, productivity zone, rainfalls, relative humidity and minimum and maximum temperatures, totaling 180 time-series data points. Their prediction performances were evaluated in terms of correlation coefficient (R²), and root means square error (RMSE). From this work, the ARIMA model was optimized using the fitting model of (p, d, q) amounted to 64 conditions through the Akaike information criteria arriving at (2, 1, 2). The ARIMA results showed that its R² and RMSE were 0.7041 and 0.1348, respectively. Moreover, the R² and RMSE of the ANN model were 0.9299 and 0.0642 by the Levenberg-Marquardt algorithm with TrainLM and LearnGDM training functions, two hidden layers and six processing elements. Both models were acceptable in forecasting the annual arabica coffee production, but the ANN model appeared to perform better.