Explore the vast range of titles available.

Sugarcane is essential for global sugar production and its compressed juice is a key raw material for industrial products. Sugarcane juice includes various metabolites with abundances and compositional balances influencing product qualities and functionalities. Therefore, understanding the characteristic features of the sugarcane metabolome is important. However, sugarcane compositional variability and stability, even in pretreatment processes for nuclear magnetic resonance (NMR)-based metabolomic studies, remains elusive. The objective of this study is to evaluate sugarcane juice metabolomic variability affected by centrifugation, filtration, and thermal pretreatments, as well as the time-course changes for determining optimal conditions for NMR-based metabolomic approach. The pretreatment processes left the metabolomic compositions unchanged, indicating that these pretreatments are compatible with one another and the studied metabolomes are comparable. The thermal processing provided stability to the metabolome for more than 32 h at room temperature. Based on the determined analytical conditions, we conducted an NMR-based metabolomic study to discriminate the differences in the harvest period and allowed for successfully identifying the characteristic metabolome. Our findings denote that NMR-based sugarcane metabolomics enable us to provide an opportunity to collect a massive amount of data upon collaboration between multiple researchers, resulting in the rapid construction of useful databases for both research purposes and industrial use.

Sugar apples have attracted attention in recent years due to their medicinal and nutritional properties. However, the shelf life of sugar apples is one of the most concerning problems owing to their perishability. This work aimed to determine the ideal harvest time for sugar apple fruits in relation to different classes of carpel interspaces. Therefore, fruits were classified into three stages according to the carpel interspace: stage 1 (0.0 - 2.0 mm); stage 2 (2.1 - 3.0 mm); and stage 3 (3.0 - 4.0 mm). After harvesting, the fruits were evaluated daily in the laboratory regarding their physical and physicochemical aspects until they reached the point of consumption (horticultural maturation). The following variables were evaluated: fruit diameter and length (mm); fruit, peel, pulp, and seed masses (g); color index, including the chromatic attributes L* (luminosity), C* (chroma), and h* (hue angle); bark firmness (N); soluble solids (°Brix); titratable acidity (g citric acid 100 g-1 of pulp-1); pulp yield; and ratio SS/TA. Fruits at stage 3 showed larger diameters, less firmness, and better chromaticity means. Fruits at stages 2 and 3 had eight days of postharvest life. However, fruits at stage 2 took longer for 50% of the fruits to be ready for consumption. The results demonstrate that stages 2 and 3 can be determinants for the harvest time of sugar apples.

The coffee berry borer (CBB), Hypothenemus hampei (Ferrari), is a significant pest impacting coffee-producing regions globally, causing substantial yield and economic losses. Various factors, including the host plant, environmental conditions, and farm management practices, influence CBB infestation. In particular, smallholder farmers often employ different shade management techniques, creating distinct biotic and abiotic conditions that affect CBB damage, distribution, and reproduction. This study aims to assess CBB populations in coffee berries across different locations within the plots, specifically on branches during harvest, post-harvest, and on the ground. The study was conducted in Pangalengan District, Bandung Regency, West Java. The study indicated that both shade and full-sun areas had a significant effect on CBB population dynamics. Coffee has significantly increased infestation rates in full-sun areas, and rapid populations were established, especially adult CBB. However, the shaded area was not suitable for CBB breeding. Nevertheless, though the populations of adult stages decreased markedly, the number of larval CBB with these two periods was still quite appreciable. Based on these findings, the shaded areas are suggested as an effective ecological strategy for managing CBB populations and reducing crop losses in coffee farming.

Seaweed has attracted great attention as a healthy and nutritious food. Traditional seaweed processing plants mainly rely on manual visual inspection to identify and remove inferior seaweed. Accurate and rapid harvest period classification and impurity detection are key to improving productivity and processing speed in seaweed processing plants. Although many studies on seaweed have been conducted in laboratory environments, currently, the plants lack effective tools to obtain real-time and reliable information on seaweed quality. To address this challenge, the deep transfer learning-based computer vision was applied to identify inferior seaweeds, including those from the third harvest, fourth harvest, and impure seaweeds in this work. Specifically, YOLOv8 and YOLOv5 were utilized as base transfer learning models. By loading various pre-trained weight files, this study was able to automatically classify Porphyra haitnensis into four categories based on the harvest period and simultaneously detect four types of common impurities in it. Among the tested models, YOLOv8n-cls achieved the best trade-off in classifying the harvest period, with a Top-1 accuracy of 93.5%. This represented a significant improvement of 16% compared to the performance without transfer learning. The detection speed for a single image was 8.2 ms, and the model size was only 2.82 Mb. On the other hand, YOLOv8n exhibited outstanding performance in impurity detection, with a mean average precision of 99.14%, a single image detection speed of 4.3 ms, and a model size of 5.95 Mb. The results demonstrated the potential of YOLOv8 with transfer learning to objectively assist or even replace decision-making by assembly line workers. This study will not only enhance the quality control, production efficiency, and economic benefits of the seaweed processing industry but also drive the automation equipment and systems of seaweed-related enterprises towards greater intelligence and efficiency. Graphical abstract In order to provide consumers with high-quality seaweed, it is necessary to identify and remove inferior seaweed in seaweed processing factories, such as those from the third harvest, fourth harvest, and impure seaweed. This study employs the deep transfer learning-based YOLOv8 to automatically classify seaweed from different harvest periods and detect impurities in it.

Background Astragalus membranaceus var. mongholicus (Astragalus), acknowledged as a pivotal “One Root of Medicine and Food”, boasts dual applications in both culinary and medicinal domains. The growth and metabolite accumulation of medicinal roots during the harvest period is intricately regulated by a transcriptional regulatory network. One key challenge is to accurately pinpoint the harvest date during the transition from conventional yield content of medicinal materials to high and to identify the core regulators governing such a critical transition. To solve this problem, we performed a correlation analysis of phenotypic, transcriptome, and metabolome dynamics during the harvesting of Astragalus roots. Results First, our analysis identified stage-specific expression patterns for a significant proportion of the Astragalus root genes and unraveled the chronology of events that happen at the early and later stages of root harvest. Then, the results showed that different root developmental stages can be depicted by co-expressed genes of Astragalus. Moreover, we identified the key components and transcriptional regulation processes that determine root development during harvest. Furthermore, through correlating phenotypes, transcriptomes, and metabolomes at different harvesting periods, period D (Nov.6) was identified as the critical period of yield and flavonoid content increase, which is consistent with morphological and metabolic changes. In particular, we identified a flavonoid biosynthesis metabolite, isoliquiritigenin, as a core regulator of the synthesis of associated secondary metabolites in Astragalus. Further analyses and experiments showed that HMGCR , 4CL , CHS , and SQLE , along with its associated differentially expressed genes, induced conversion of metabolism processes, including the biosynthesis of isoflavones and triterpenoid saponins substances, thus leading to the transition to higher medicinal materials yield and active ingredient content. Conclusions The findings of this work will clarify the differences in the biosynthetic mechanism of astragaloside IV and calycosin 7-O-β-D-glucopyranoside accumulation between the four harvesting periods, which will guide the harvesting and production of Astragalus.

This study covers the morphological characteristics, growth behavior, and cultivation of yard-long beans (green and red surface fruits) as vegetable for urban communities. This study shows many similarities in the morphological traits (leaf shape and color, as well as the number of leaflets) and growth behavior (climbing growth, flowering time, fruiting, and harvesting) between the two cultivars. The green-fruited cultivar had smaller leaves and fever leaves, lesser leaf weight, thinner petioles, and lower SPAD value compared to the red-fruited one. In both cultivars, the leaves slightly wilt at midday, but this did not have a negative effect on fruit growth and average fruit size in the long term. The fruits can be harvested 8–10 days after the petals and stamens have fallen. The earliest matured pods also become the longest and heaviest. After harvesting the initial pod, it will flower and bear fruit again on the same bunch. However, in the same bunch and at the same time only 1 or 2 pods will grow to marketable size. The green cultivar produced a larger fruit yield than the red, but their quality was comparable. Both yard-long bean cultivars responded to the solar tracking phenomenon, the upper surface of the leaf being dominantly oriented to the east.

Salvia atropatana is a medicinal plant native to Middle Eastern countries. It has been traditionally used in Turkish and Iranian folk medicine to treat infections, wounds, inflammatory diseases, spastic conditions, and diabetes. Its therapeutic potential has been attributed to its essential oil, polyphenolic acid, flavonoid, and diterpenoid content. The aim of the study was to determine the optimal conditions of in vitro S. atropatana shoot culture to enhance proliferation and secondary metabolite production. It examined the effects of various cytokinins and culture duration on culture growth parameters and phenolic compound accumulation. Exogenous cytokinin supplementation significantly enhanced shoot proliferation, with the highest proliferation ratio (6.3) observed with 1 and 2 mg/L 6-benzylaminopurine (BAP). Biomass accumulation was the highest at 0.5 mg/L BAP, followed by 1 and 2 mg/L meta-toplin (mTOP). Phenolic profiling identified nine compounds, with rosmarinic acid (RA) as the dominant metabolite. The highest RA content (16 mg/g dry weight) was achieved with 1 and 2 mg/L BAP and 0.5 mg/L of its ryboside. The TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method identified 1 mg/L BAP as the optimal treatment, balancing high proliferation, biomass, and polyphenol accumulation. Extending culture duration to 50 days increased biomass and phenolic content reaching 19.25 mg/g dry weight. However, morphological changes, including apical necrosis, were observed, and a significantly longer cultivation period was needed, questioning the value of the procedure. This study provides a basis for scalable in vitro production of bioactive compounds in S. atropatana.

Marine macroalgae are well known to release a wide spectrum of volatile organic components, the release of which is affected by environmental factors. This paper aimed to identify the essential oil (EO) compounds of the brown algae Cystoseira compressa collected in the Adriatic Sea monthly, from May until August. EOs were isolated by hydrodistillation using a Clavenger-type apparatus and analyzed by gas chromatography coupled with mass spectrometry (GC–MS). One hundred four compounds were identified in the volatile fraction of C. compressa, accounting for 84.37–89.43% of the total oil. Samples from May, June, and July were characterized by a high share of fatty acids (56, 69, and 34% respectively) with palmitic acid being the dominant one, while in the August sample, a high content of alcohols (mainly phytol and oleyl alcohol) was found. Changes in the other minor components, which could be important for the overall aroma and biological activities of the algal samples, have also been noted during the vegetation periods. The results of this paper contribute to studies of algal EOs and present the first report on C. compressa EOs.

In order to accurately establish a discrete element model for the whole plant flexibility of upright rice during the harvesting period, several physical characteristics, such as geometric features, moisture content, and density, of the entire rice plant were measured, along with frictional properties, such as the static and rolling friction coefficients, and mechanical properties, including the elastic modulus and restitution coefficient. A flexible and upright discrete element model of the rice plant was established using the DEM method based on the Hertz–Mindlin (no slip) and Hertz–Mindlin with bonding mechanical models. The parameters were optimized through Plackett–Burman screening experiments, steepest ascent experiments, and Box–Behnken optimization experiments to accurately determine the discrete element model parameters of each component of the rice plant. The calibration process of the contact parameters between rice grains and steel was analyzed in detail as an example, resulting in a calibration error of 0.68% for the natural repose angle. Taking the calibration of the contact parameters between the main stem and steel as an example, a detailed analysis of the calibration process was conducted. The calibration resulted in a calibration error of 2.76% for the natural repose angle and 2.33% for deflection. This study lays the foundation for understanding the mechanical response of rice and machinery when they are coupled together. Additionally, it provides valuable references for establishing discrete element models of plant species other than rice.

This study investigated the impact of variety and harvest time on the visual appearance, nutritional quality, and functional active substances of six lotus root cultivars: “Xinsanwu”, “Wuzhi No. 2”, “Baiyuzhan”, “Huaqilian”, “Elian No. 6”, and “Elian No. 5”. Samples were collected monthly from December 2023 to April 2024. A nutrient analysis revealed a decrease in the water content with a delayed harvest. The total soluble solids and soluble sugar content peaked towards the end and middle-to-late harvest periods, respectively. Starch levels initially increased before declining, while the soluble protein exhibited a triphasic trend with an initial rise, a dip, and a final increase. The vitamin C (Vc) content varied across cultivars. Functional active substances displayed dynamic changes. The total phenolics initially decreased, then increased, before ultimately declining again. The total flavonoid content varied by both cultivar and harvest time. The phenolic acid and flavonoid content mirrored the trends observed for total phenolics and total flavonoids. Gastrodin was the most abundant non-flavonoid compound across all varieties. “Wuzhi No. 2” and “Baiyuzhan” displayed higher levels of functional active substances and starch, while the Elian series and “Xinsanwu” cultivar exhibited a greater content of Vc, soluble sugar, and soluble protein. Specific harvest periods yielded optimal results: “Wuzhi No. 2” (H1 and H5), “Huaqilian” (H2), and “Baiyuzhan” (H3 and H4) demonstrated a high nutrient and functional active substance content. Overall, the lotus roots harvested in period H4 achieved the highest score. Overall, this study provides the foothold for the rapid identification of superior lotus root cultivars and the valorization of lotus root by-products via advanced processing methods. Additionally, it offers valuable insights for market participants and consumers to select optimal varieties and harvest times based on their specific needs.