Optimal Harvest Time Research Articles

Evaluating the efficiency of NDVI and climatic data in maize harvest prediction using machine learning

ABSTRACT Accurate anticipation of the maize harvest date is important in the agricultural market, as it ensures the sustainability of food production in response to the increasing global demand for food. This paper proposes a predictive model to determine the optimal harvest time in maize plots using the Normalised Difference Vegetation Index (NDVI) and climatological data. These variables were oversampled and used to train various models, including Random Forest (RF), Gradient Boosting Machine (GBM), Light Gradient Boosting Machine (LGBM), Extreme Gradient Boosting Machine (XGBoost), CatBoost and Support Vector Machine (SVM). Bayesian optimisation has been used to find the best hyperparameters and Shapley values to identify the variables that exert the most significant influence on the prediction in each model instance. As a result of this approach, a model with an accuracy of 92.1% and an Area Under the Curve (AUC) of 0.935 was developed. The variables that determined these results were atmospheric pressure, mean temperature, precipitation, NDVI, and precipitation.

Chronobiology of Viscum album L.: a time series of daily metabolomic fingerprints spanning 27years.

Introduction: European mistletoe (Viscum album L.) has been gaining increasing interest in the field of oncology as a clinically relevant adjunctive treatment in many forms of cancer. In the field of phytopharmacology, harvesting time is pivotal. In the last century, a form of metabolomic fingerprinting based on pattern formation was proposed as a way to determine optimal harvesting times to ensure high quality of mistletoe as raw material for pharmaceutical use. In order to further evaluate the information obtained with this metabolomic fingerprinting method, we analysed a large time series of previously undigitised daily mistletoe chromatograms dating back to the 1950s. Methods: These chromatograms were scanned and evaluated using computerized image analysis, resulting in 12 descriptors for each individual chromatogram. We performed a statistical analysis of the data obtained, investigating statistical distributions, cross-correlations and time self-correlations. Results: The analysed dataset spanning about 27years, contains 19,037 evaluable chromatograms in daily resolution. Based on the distribution and cross-correlation analyses, the 12 descriptors could be clustered into six independent groups describing different aspects of the chromatograms. One descriptor was found to mirror the annual rhythm being well correlated with temperature and a phase shift of 10days. The time self-correlation analysis showed that most other descriptors had a characteristic self-correlation of ∼50days, which points to further infradian rhythms (i.e., more than 24h). Discussion: To our knowledge, this dataset is the largest of its type. The combination of this form of metabolomic fingerprinting with the proposed computer analysis seems to be a promising tool to characterise biological variations of mistletoe. Additional research is underway to further analyse the different rhythms present in this dataset.

Integrating Climate and Satellite Data for Multi-Temporal Pre-Harvest Prediction of Head Rice Yield in Australia

Precise and prompt predictions of crop yields are crucial for optimising farm management, post-harvest operations, and marketing strategies within the agricultural sector. While various machine learning approaches have been employed to forecast crop yield, their application to grain quality, particularly head rice yield (HRY), is less explored. This research collated crop-level HRY data across four seasons (2017/18–2020/21) from Australia’s rice-growing region. Models were developed using the XGBoost algorithm trained at varying time steps up to 16 weeks pre-harvest. The study compared the accuracy of models trained on datasets with climate data alone or paired with vegetative indices using two- and four-week aggregations. The results suggest that model accuracy increases as the harvest date approaches. The dataset combining climate and vegetative indices aggregated over two weeks surpassed industry benchmarks early in the season, achieving the highest accuracy two weeks before harvest (LCCC = 0.65; RMSE = 6.43). The analysis revealed that HRY correlates strongly with agroclimatic conditions nearer harvest, with the significance of vegetative indices-based features increasing as the season progresses. These features, indicative of crop and grain maturity, could aid growers in determining optimal harvest timing. This investigation offers valuable insights into grain quality forecasting, presenting a model adaptable to other regions with accessible climate and satellite data, consequently enhancing farm- and industry-level decision-making.

Bioeconomics of juvenile seahorse (Hippocampus erectus) culture: Optimal harvest time

AbstractThe culture of seahorses Hippocampus erectus in captivity represents a window of opportunity for the diversification of the aquaculture activity in the ornamental industry. In this study, we have constructed a bioeconomic model to evaluate the optimal harvest time (OHT) over a culture period of 562 days. The bioeconomic model was integrated with three submodels: biological, technological, and economic. Three different mortality rates were used for different periods in culture, registering a higher survival in the period from 0 to 60 days with a rate of 53.4%. The sensitivity analysis showed that the mortality rate in this period was the parameter with the greatest influence on the benefits. The Von Bertalanffy growth model was indicated to describe the growth of H. erectus given its statistical significance using Theil's inequality coefficient, registering parameters of (L∞ = 141.62 mm) and (k = 0.0049 month‐1). The bioeconomic model determined the OHT in the 4th month of culture, the time when the maximum profit is recorded. It is concluded that the culture presents challenges to be addressed although the bioeconomic model allows for demonstrating the OHT.

Content of secondary metabolites and antioxidant activities of Lonicera japonica flowers at different developmental stages from Shandong province

This study established an ultrasound-assisted extraction-high performance liquid chromatography method for simulta-neously determinining the content of 11 bioactive compounds including iridoids, phenolic acids, and flavonoids in Lonicera japonica flowers. The flowers at six stages from the rice bud stage(ML) to the golden flower stage(JH) of L. japonica varieties 'Sijuhua' and 'Beihua No.1' in two planting bases in Shandong province were collected. The established method was employed to determine the content of 11 target compounds, on the basis of which the dynamics of active components in L. japonica sampels during different development stages was investigated. The correlation analysis was carried out to reveal the correlations of the content of iridoids, phenolic acids, and flavonoids. Furthermore, the antioxidant activities of samples at different developmental stages were determined, and the relationship between antioxidant activity and chemical components was analyzed by the correlation analysis. The results showed that the total content of the 11 components in 'Sijihua' changed in a "W" pattern from the ML to JH, being the highest at the ML and the second at the slight white stage(EB). The total content of 11 compounds in 'Beihua No.1' was the highest at the ML and decreased gra-dually from the ML to JH. The samples of 'Sijihua' had higher content of iridoids and lower content of phenolic acids than those of 'Beihua No.1'. The content of flavonoids and phenolic acids showed a positive correlation(R~2=0.90, P<0.05) in 'Sijihua' but no obvious correlation in 'Beihua No.1'. The antioxidant activity and phenolic acid content showed positive correlations, with the determination coefficients(R~2) of 0.84(P<0.05) in 'Beihua No.1' and 0.73(P<0.05) in 'Sijihua'. The antioxidant activity of both varieties was the strongest at the ML and the second at the EB. This study revealed that the content dynamics of iridoids, phenolic acids, and flavonoids in 'Sijihua' and 'Beihua No.1' cultivated in Shandong province during different developmental stages. The results indicated that the antioxidant activity of L. japonica flowers was significantly correlated with the content of phenolic acids at different deve-lopmental stages, which provided a basis for determining the optimum harvest time of L. japonica flowers.

The Composition of Volatiles and the Role of Non-Traditional LOX on Target Metabolites in Virgin Olive Oil from Autochthonous Dalmatian Cultivars.

The lipoxygenase pathway has a significant influence on the composition of the volatile components of virgin olive oil (VOO). In this work, the influence of the maturity index (MI) on the activity of the lipoxygenase enzyme (LOX) in the fruits of the autochthonous Dalmatian olive cultivars Oblica, Levantinka and Lastovka was studied. The analysis of the primary oxidation products of linoleic acid in the studied cultivars showed that LOX synthesises a mixture of 9- and 13-hydroperoxides of octadecenoic acid in a ratio of about 1:2, which makes it a non-traditional plant LOX. By processing the fruits of MI~3, we obtained VOOs with the highest concentration of desirable C6 volatile compounds among the cultivars studied. We confirmed a positive correlation between MI, the enzyme activity LOX and the concentration of hexyl acetate and hexanol in cultivars Oblica and Lastovka, while no positive correlation with hexanol was observed in the cultivar Levantinka. A significant negative correlation was found between total phenolic compounds in VOO and LOX enzyme activity, followed by an increase in the MI of fruits. This article contributes to the selection of the optimal harvest time for the production of VOOs with the desired aromatic properties and to the knowledge of the varietal characteristics of VOOs.

Management Information Systems for Tree Fruit–2: Design of a Mango Harvest Forecast Engine

Spatially enabled yield forecasting is a key component of farm Management Information Systems (MISs) for broadacre grain production, enabling management decisions such as variable rate fertilization. However, such a capability has been lacking for soft (fleshy)-tree-fruit harvest load, with relevant tools for automated assessment having been developed only recently. Such tools include improved estimates of the heat units required for fruit maturation and in-field machine vision for flower and fruit count and fruit sizing. Feedback on the need for and issues in forecasting were documented. A mango ‘harvest forecast engine’ was designed for the forecasting of harvest timing and fruit load, to aid harvest management. Inputs include 15 min interval temperature data per orchard block, weekly manual or machine-vision-derived estimates of flowering, and preharvest manual or machine-vision-derived estimates of fruit load on an orchard block level across the farm. Outputs include predicted optimal harvest time and fruit load, on a per block and per week basis, to inform harvest scheduling. Use cases are provided, including forecast of the order of harvest of blocks within the orchard, management of harvest windows to match harvesting resources such as staff availability, and within block spatial allocation of resources, such as adequate placement of harvest field bin and frost fans. Design requirements for an effective harvest MIS software artefact incorporating the forecast engine are documented, including an integrated database supporting spatial query, data analysis, processing and mapping, an integrated geospatial database for managing of large spatial–temporal datasets, and use of dynamic web map services to enable rapid visualization of large datasets.

Physical, Chemical and Enzymatic Changes in Amla (Emblica officinalis) Fruit during Growth and Maturation.

Amla (Emblica officinalis) is one of the most prominent fruits in terms of nutritional and medicinal properties and is utilized for the preparation of many traditional processed foods and in Ayurvedic formulations. This study aims to investigate the enzyme activity and physical and chemical quality parameters during the growth and development stages of amla fruit for the determination of proper harvesting time to get optimum nutrient contents of fruit. The amla fruits of the chakaiya variety were harvested at 135 to 270 days after fruit set (DAFS) in 2021 and 2022 to study the various physical, chemical and enzymatic changes during growth and maturation. The geometrical and gravimetric attributes of the fruit, viz. diameter, height, weight, volume, surface area, sphericity, aspect ratio, and radius of curvature increased. However, density decreased with the growth and maturation of the fruit. Furthermore, the rolling resistance, yellowness index and firmness of the fruit increased during the entire harvesting period of 135 to 270 DAFS. Total soluble solids and titratable acidity of the fruits increased only up to 195 DAFS and after that, continuously decreased. In contrast, ascorbic acid concentration grew in the entire growth and development period. Tannic, phenolic compounds and naringin content of the fruit steadily dropped until the final stage of harvest. Pectin Methyl Esterase (PME) activity was detected very low, 0.009 unit/ml at 135 DAFS, but as the fruit grew and matured, activity increased to 0.307 unit/ml at 270 DAFS. Polygalactouronase (PG) activity was not detected until 210 DAFS and, thereforesignificantly increased with maturity. Considering the optimal value of all studied physical, chemical and enzymatic attributes of the fruit during the entire harvesting period of 135 to 270 DAFS, the optimal harvesting time of the fruit was 210 DAFS.

How does harvest time affect the major fatty acids and bioactive compounds in hazelnut cultivars (Corylus avellana L.)?

This study was conducted to investigate the effects of harvest time on the protein, oil, fatty acids and bioactive compounds in hazelnut cultivars (Corylus avellana L. cvs. ‘Tombul’, ‘Palaz’, ‘Çakıldak’, ‘Okay 28’ and ‘Allahverdi’). The harvest was carried out at 7 different periods with weekly intervals from 20 July to 31 August. As the harvest time progressed, increases and decreases were detected in protein, oil, fatty acids and bioactive compounds. The highest oil content was measured in the H5 and H6 harvest periods. The highest content was determined in H3 for oleic acid. Higher total phenolics, total flavonoids and antioxidant activity were obtained in the first 3 harvest periods than in the other periods. The present findings revealed that the protein, fatty acids and bioactive compounds in hazelnut cultivars may differ according to the harvest time. The results obtained will provide clearer ideas to both the industry and the producers about the optimum harvest time for the intended use of these cultivars.

Revealing the structural changes of lignin in Chinese quince (Chaenomeles sinensis) fruit as it matures

Chinese quince fruits (Chaenomeles sinensis) contain substantial amounts of lignin; however, the exact structure of lignin remains to be investigated. In this study, milled wood lignins (Milled wood lignin (MWL)-1, MWL-2, MWL-3, MWL-4, MWL-5, and MWL-6) were extracted from fruits harvested once a month from May to October 2019 to investigate their structural evolution during fruit growth. The samples were characterized via High-performance anion exchange chromatography (HPAEC), Fourier transform–infrared spectroscopy (FT-IR), gel permeation chromatography (GPC), thermogravimetric (TGA), pyrolysis–gas chromatography/mass spectrometry (Py–GC/MS) and NMR (2D-heteronuclear single quantum coherence (HSQC) and 31P). The MWL samples in all fruit growth stages were GS-type lignin and lignin core undergoing minimal alterations during fruit development. The predominant linkage in the lignin structure was β-O-4′, followed by β-β' and β-5′. Galactose and glucose were the main monosaccharides associated with MWL. In MWL-6, the lignin exhibited the highest homogeneity and thermal stability. As the fruit matured, a gradual increase in the β-O-4′ proportion and the ratio of S/G was observed. The results provide comprehensive characterization of the cell wall lignin of quince fruit as it matures. This study could inspire innovative applications of quince fruit lignin and provide the optimal harvest time for lignin utilization.

Lingonberry (Vaccinium vitis-idaea L.) fruits: Potential characterization of flavor and functional profiles during ripening based on UHPLC-QqQ-MS/MS

As a 'superfruit', the sour and astringent flavor of lingonberries seriously limits consumer acceptance and unravelling the intrinsic link between specific flavor and chemical constituents is urgent. This study proposed a comparative qualitative and quantitative analysis for flavor and functional phytochemicals in lingonberry fruits based on UHPLC-QqQ-MS/MS in multiple reaction monitoring (MRM). After systematic MRM parameters optimization, the developed method showed good precision (RSD < 4.4%) and recovery (99.89 ∼ 105.21%) within 6 min. The results revealed the distribution of 18 flavor and functional components of lingonberries during different ripening periods. In addition, it was surprisingly found that citric acid (7.94–15.58 mg/g DW) and (+)-catechin (0.52–4.13 mg/g DW) were the components contributing to the sour and astringent flavor of lingonberries, cyanidin-3-O-galactoside (0.48–4.17 mg/g DW) was the primary component affecting color, and benzoic acid (3.67–19.45 mg/g DW) was the typical functional component. Furthermore, biosynthetic gene transcript levels showed positive correlations with the chemical composition metabolic profile in lingonberry fruits at different ripening stages. In conclusion, this work provided a rapid and sensitive analysis and the dynamic changes of flavor and functional phytochemicals for quality control, optimal harvesting time and application of lingonberry fruits.

Monitoring of key Camellia Oleifera phenology features using field cameras and deep learning

A rapid and accurate yield estimation is of great significance to the management and sustainable development of Camellia Oleifera forests. Consequently, the simultaneous and accurate detection of key phenology features of Camellia Oleifera (buds, flowers, fruits) is crucial for precise yield estimation. This not only enables robotic harvesting but also allows for the prediction of peak flowering and fruit ripening periods to determine the optimal harvesting time. However, in recent studies, only Camellia Oleifera fruits have been marked and detected. Therefore, to enable rapid yield estimation, it is necessary to simultaneously detect the key phenology stages (buds, flowers, fruits) of Camellia Oleifera. In this study, we annotated, trained, and predicted Camellia Oleifera buds, flowers, and fruits collected via field cameras to observe their daily quantitative changes. Quantity change curves were generated to estimate crucial phenology stages. Phenology feature detection and transfer learning were performed using the YOLO v5 model, widely used YOLO v3 model, and CenterNet model with center point prediction, all trained on the same dataset. The best model for phenology feature detection was selected based on a comparison of average precision, with the YOLO v5 model achieving a higher mean Average Precision (mAP) value of 91.31 % compared to the CenterNet (85.43 %) and YOLO v3 (81.00 %) models. In YOLO v5, the AP values for bud, flower, and fruit detection were 82.80 %, 98.13 %, and 92.99 %, respectively, surpassing the CenterNet model by 3.97 %, 2.44 %, and 11.23 %, and the YOLO v3 model by 6.39 %, 17.13 %, and 11.67 %. The image size was adapted from 4000 × 3000 pixels to 512 × 512 pixels for model optimization. Additionally, data from the Seedling Center of Liuyang City collected at different years and times were utilized to showcase the generalizability and scalability of the selected models, resulting in mAP values of 86.14 %, 80.17 %, and 69.20 % for the three above-mentioned models respectively. The plotted phenology change curves unveiled that Camellia Oleifera undergoes four stages: fruit enlargement period, bud enlargement period, flowering period, and flower wilting period. The conclusion can be drawn that using field cameras and YOLOv5 can simultaneously achieve real-time detection of key phenology features (buds, flowers, and fruits) of Camellia Oleifera, in order to further record crucial phenology patterns (such as flowering peaks and fruit ripening periods). This study offers theoretical references and scientific evidence for monitoring changes in key phenology features of Camellia Oleifera.

Результаты лабораторно-полевых испытаний процесса глубокорыхления глубокорыхлителем РВН-3

Sunflower harvesting is the final stage in its cultivation; it is the most labor-intensive and responsible operation, as it requires a lot of labor and the availability of specialized equipment. Important factors influencing the quality indicators of sunflower harvesting are the timing of harvesting and the technical means used. The optimal time for sunflower harvesting occurs when the seed moisture content is 12-14%; at this humidity, as a rule, self-shedding of the seeds does not occur. Reducing direct losses of sunflower seeds behind a combine harvester largely depends on the harvesting equipment used. Currently, there are a large number of them, they have different designs, but not all of them meet agricultural requirements. The article presents the test results of sunflower harvesting devices PRP-8 and PRP-12. Keywords: HARVESTING, HARVEST, SUNFLOWER, HARVESTER, MOUNTED HARVESTING ADAPTERS, ENERGY EQUIPMENT, TECHNOLOGICAL PROCESS

Rapid Determination of Different Ripening Stages of Occidental Pears (Pyrus communis L.) by Volatile Organic Compounds Using Proton-Transfer-Reaction Mass Spectrometry (PTR-MS).

Determination of Occidental pear (Pyrus communis) ripening is difficult because the appearance of Occidental pears does not change significantly during the ripening process. Occidental pears at different ripening stages release different volatile organic compounds (VOCs), which can be used to determine fruit ripeness non-destructively and rapidly. In this study, VOCs were detected using proton-transfer-reaction mass spectrometry (PTR-MS). Notably, data were acquired within 1 min. Occidental pears harvested at five separate times were divided into three ripening stages: unripe, ripe, and overripe. The results showed that the composition of VOCs differed depending on the ripening stage. In particular, the concentrations of esters and terpenes significantly increased during the overripe stage. Three ripening stages were clearly discriminated by heatmap clustering and principal component analysis (PCA). This study provided a rapid and non-destructive method to evaluate the ripening stages of Occidental pears. The result can help fruit farmers to decide the optimum harvest time and hence reduce their economic losses.

Исследование уборки урожая подсолнечника современными энергосредствами с использованием навесных уборочных адаптеров ПРП-8 И ПРП-12

Sunflower harvesting is the final stage in its cultivation; it is the most labor-intensive and responsible operation, as it requires a lot of labor and the availability of specialized equipment. Important factors influencing the quality indicators of sunflower harvesting are the timing of harvesting and the technical means used. The optimal time for sunflower harvesting occurs when the seed moisture content is 12-14%; at this humidity, as a rule, self-shedding of the seeds does not occur. Reducing direct losses of sunflower seeds behind a combine harvester largely depends on the harvesting equipment used. Currently, there are a large number of them, they have different designs, but not all of them meet agricultural requirements. The article presents the test results of sunflower harvesting devices PRP-8 and PRP-12. Keywords: HARVESTING, HARVEST, SUNFLOWER, HARVESTER, MOUNTED HARVESTING ADAPTERS, ENERGY EQUIPMENT, TECHNOLOGICAL PROCESS

Effect of augmented nutrient composition and fertigation system on biomass yield and cannabinoid content of medicinal cannabis (Cannabis sativa L.) cultivation.

Growing evidence underscores the role of nutrients and fertigation systems in soilless production, influencing medicinal cannabis biomass and secondary metabolite content. This study delves into the impact of enhanced nutrient regimes on the 'ionome' and its ramifications for biomass and cannabinoid production in medicinal cannabis, comparing two distinct fertigation systems: recirculation and drain-to-waste. Notably, we assess the optimal harvest time for maximizing profitability. In comparing the experimental variant with elevated levels of phosphorus (P), potassium (K), and iron (Fe) in the nutrient solution to the control variant, we observe distinct patterns in element composition across stems, leaves, and flowers, with significant differences between fertigation systems. Total nitrogen content was determined through the Kjeldahl method. Flame atomic absorption spectrometry (FAAS) and inductively coupled plasma optical emission spectrometry (ICP-OES) were employed for elemental analysis. Cannabinoid identification and quantification used high-performance liquid chromatography with a diode-array detector (HPLC/DAD). Followed statistical analyses included ANOVA and Tukey's HSD test. Although the augmented nutrient regimen does not substantially increase plant biomass, interesting differences emerge between the two fertigation systems. The recirculation fertigation system proves more profitable during the recommended harvest period. Nonetheless, the altered nutrient regime does not yield statistically significant differences in final inflorescence harvest mass or cannabinoid concentrations in medicinal cannabis. The choice of fertigation system influences the quantity and quality of harvested inflorescence. To optimize the balance between the dry biomass yield of flowers and cannabinoid concentration, primarily total THC yield (sum of tetrahydrocannabinolic acid, Δ9-tetrahydrocannabinol, and Δ8-tetrahydrocannabinol), we propose the 11th week of cultivation as the suitable harvest time for the recirculation system. Importantly, the recirculation system consistently outperformed the drain-to-waste system, especially after the ninth week, resulting in significantly higher total THC yields. Enriched nutrition, when compared with control, increased THC yield up to 50.7%, with a remarkable 182% surge in the recirculation system when compared with the drain-to-waste system.

Optimum Seed Harvest Time of Trifolium lupinaster L. in Relation to Flowering, Pods and Seed Characteristics

Background: Pod splitting is the main cause of the low seed yield of legume forage grasses. In the present study, the flowering pattern, seed maturity characteristics and the optimum seed harvesting time of Trifolium lupinaster L. were investigated to improve seed yield and quality. Methods: All the required observations for this study were completed in the new line nursery from July to October 2022. Flowering habits of populations, individual plants, inflorescences and florets were observed for two consecutive months from July 1 to September 1 and daily temperatures and humidity were recorded.Observations on the state of seed and pod development were made by sampling and measuring in three batches every three days from July 25 to August 23 starting from the 12th day after the first flower and continuing until the first day of the season. Starting from July 15, seed yield and constitutive factors were measured every 10 d until September 5th. Result: The results showed that the flowering period of T. lupinaster L. population lasted for 60 days and the peak opening period was on the 11th-20th day after heading began, the florets opened most vigorously at 11:00-13:00 every day and inflorescences were opened more vigorously at 15:00 every day. The opening pattern of florets and inflorescences was greatly affected by temperature and humidity. The fresh weight of pod skin and seeds reached the maximum on the 15th day after flowering; the length and width of pods and seeds reached the maximum on the 18th day; the water content of pod skin and seeds began to decrease sharply on the 21st day, while the pods began to crack and the surface of the seeds dried and hardened; the water content of seeds decreased to below the safe storage moisture at 27 days. Our resuts showed that mid-August was the optimum seed harvesting period for T. lupinaster L.

Establishment and elicitation of liquid adventitious root cultures of Inula crithmoides L. for increased caffeoylquinic acids production and hepatoprotective properties

This study established a liquid adventitious root culture for Inula crithmoides L. focusing on producing extracts rich in hepatoprotective caffeoylquinic acids through elicitation. Adventitious roots were induced from in vitro-grown plant leaves cultured on MS medium supplemented with 1 mg/L IBA. Growth and secondary metabolites accumulation (phenolics, flavonoids, hydroxycinnamic acids) were monitored weekly to determine the optimal harvesting time. Then, the adventitious roots were elicited for 4 weeks with varying concentrations of yeast extract–YE (50, 100 and 200 mg/L) and extracted with ethanol. The extracts were evaluated for their hepatoprotective effects against ethanol-induced hepatotoxicity and analyzed through high-performance liquid chromatography coupled with electrospray ionization mass spectrometry (HPLC–ESI–MS/MS). Roots of greenhouse-cultivated plants were used to compare the results obtained from in vitro -grown adventitious roots. IBA supplementation induced 100% adventitious root formation, with maximum biomass and phenolic accumulation after 4 weeks. Hydroxycinnamic acid levels increased significantly with YE treatment at all the concentrations, particularly in case of chlorogenic acid and di-O-caffeoylquinic acid isomers. The root extracts displayed significant in vitro hepatoprotective effects, particularly at 50 mg/L YE elicitation. Overall, the elicitation of I. crithmoides liquid root cultures with yeast extract offers a promising, efficient, and cost-effective approach for optimizing the production of valuable caffeoylquinic acids having potential pharmaceutical use.

Comprehensive analysis of quality and bioactive compounds in umbu-cajá fruit during different ripening stages

Umbu-cajá (Spondias tuberosa x S. mombin) is a tropical fruit with potential health benefits due to its bioactive compounds. The objective of this study was to identify the optimal harvest point for enhanced nutritional value and consumer appeal of umbu-cajá. Umbu-cajá fruit was collected at five ripening stages (S1 to S5). Immature fruit (S1) had a higher pulp yield but a lower seed yield, suggesting an inverse relationship between these fruit components. Stage 3 (S3) was identified as the optimal harvest time, as it maintained stable pulp and seed mass, corresponding to the ideal physiological maturity point for human consumption. The respiration rate increased significantly at stages S4 and S5, indicating that Spondias sp. could be classified as a climacteric fruit. Color analysis revealed increased yellowness during ripening, which is indicative of the development of desirable attributes such as sweetness and soft texture in hipened fruits. Compositional analysis demonstrated that moisture content decreased while ash and solids content increased during ripening, reflecting appropriate maturity for human consumption. The ratio of soluble solids to acidity increased, suggesting enhanced sweetness as the fruits ripened. The levels of antioxidants, except for anthocyanins, decreased during ripening, with the latter increasing up to stage S3, thereby providing the fruit with its vibrant colors. The compositional changes underscore the importance of considering both nutritional and sensory attributes in determining the optimal harvest time. Moreover, the increased antioxidant content at early ripening stages signifies the fruit's potential as a valuable source of health-promoting compounds. This study contributes to optimizing the quality of umbu-cajá and offers valuable information for sustainable production and improved consumption of these fruits. By identifying the ideal harvest time and evaluating the changes in bioactive compounds and quality attributes during ripening, this research aids in promoting healthier dietary choices and supporting the fruit industry. The findings have implications for producers, retailers, and consumers, providing a scientific basis for enhancing the nutritional value and flavor profile of umbu-cajá at the optimal stage of ripening.

Optimization of Feed Ration Size in Aquatic System According to the Optimal Control Approach: Implications of Using the von Bertalanffy Growth Model

Rationing aquaculture farming feed is challenging for producers due to high feed costs, representing 30%–60% of the total operating costs. Therefore, optimal timing of feeding could lead to improved economic returns from an aquatic system. An optimal dynamic feeding model has been determined considering the von Bertalanffy growth model. A bioeconomic model of tilapia production in Mexico for specific markets was used for numerical illustration. The von Bertalanffy growth model was parameterized with experimental data from tilapia (Oreochromis niloticus) fed four ration sizes (50%, 80%, 100%, and satiety), in order to determine different optimal rationing for different fish sizes (200, 300, and 400 g), market prices (Monterrey, Cancún, Mexico City, and On site), and optimal harvesting times (OHT), considering the time value of money. The results of the modeled optimal feeding trajectories show a continuous decrease from stocking to reach a minimum value and then slightly approaching the harvest size. This result contrasts with the recommendations of the feed suppliers and with those found when a potential growth model was used. The results in the case study showed that the Monterrey market presented the highest present value of the benefits in the OHT and the different market sizes. The implications of the Bertalanffy model for optimal rationing trajectories are presented in the discussion.