Optimal Harvesting Research Articles

The Impact of D2 Versus D1 Lymphadenectomy in Siewert II Gastroesophageal Junction (GEJ) Cancer

BackgroundAlthough multiple treatment options exist for gastroesophageal junction (GEJ) cancer, surgery remains the mainstay for potential cure. Extended nodal dissection with a D2 lymphadenectomy (LAD) remains controversial for Siewert II GEJ cancer. Although D2 LAD may lead to a greater lymph node harvest, its effect on survival remains elusive. The authors hypothesized that additional D2 dissection in Siewert II GEJ cancer does not lead to increased survival.MethodsThis study reviewed Siewert II patients who received a D1 or D2 LAD in addition to minimally invasive esophagectomy (MIE) after receiving neoadjuvant chemoradiation or perioperative chemotherapy (2012–2022). The patients were followed for up to 5 years. The outcomes measured were survival, number of nodes sampled, and operative time. The association between D1 or D2 LAD and overall survival was analyzed with Kaplan-Meier methods and a multivariable Cox regression model.ResultsAmong 155 patients, 74 % underwent D1 and 26 % underwent D2 LAD. The patients with D2 had more than 15 lymph nodes harvested more frequently than those who had D1 (83 % vs 48 %; p < 0.001), with no difference in positive nodes (2.8 ± 5.2 vs 2.1 ± 4.2; p = 0.4). The patients with D2 LAD had a longer median operative time than those who with D1 LAD (362 vs 244 min; p < 0.001). In Kaplan-Meier and multivariable Cox regression models, overall survival did not differ significantly between the patients undergoing D2 and those who had D1 (adjusted hazard ratio [aHR], 0.52; 95 % confidence interval [CI], 0.25–1.00; p = 0.067).ConclusionsLittle consensus exists regarding the optimal lymph node harvest for GEJ cancers. In Siewert II cancer, D2 LAD may not be mandatory and may lead to increased operative morbidity with no significant difference in survival.

3D positioning of Camellia oleifera fruit-grabbing points for robotic harvesting

Camellia oleifera is an oilseed crop with high economic value. The short optimum harvest period and high labour costs of C. oleifera harvesting have prompted research on intelligent robotic harvesting. This study focused on the determination of grabbing points for the robotic harvesting of C. oleifera fruits, providing a basis for the decision making of the fruit-picking robot. A relatively simple 2D convolutional neural network (CNN) and stereoscopic vision replaced the complex 3D CNN to realise the 3D positioning of the fruit. Apple datasets were used for the pretraining of the model and knowledge transfer, which shared a certain degree of similarity to C. oleifera fruit. In addition, a fully automatic coordinate conversion method has been proposed to transform the fruit position information in the image into its 3D position in the robot coordinate system. Results showed that the You Only Look Once (YOLO)v8x model trained using 1012 annotated samples achieved the highest performance for fruit detection, with mAP50 of 0.96 on the testing dataset. With knowledge transfer based on the apple datasets, YOLOv8x using few-shot learning realised a testing mAP50 of 0.95, reducing manual annotation. Moreover, the error in the 3D coordinate calculation was lower than 2.1 cm on the three axes. The proposed method provides the 3D coordinates of the grabbing point for the target fruit in the robot coordinate system, which can be transferred directly to the robot control system to execute fruit-picking actions. This dataset was published online to reproduce the results of this study.

Changes in growth characteristics and ginsenoside contents of wild-simulated ginseng with different harvest times in South Korea

Wild-simulated ginseng (WSG, Panax ginseng C.A. Meyer) is grown in mountainous forests, without the chemical treatment or installation of artificial facilities. This study aimed to investigate monthly changes in growth characteristics and ginsenoside contents in WSG to suggest the optimal harvest time. Four-year-old WSG were collected in the same area every month, and their growth characteristics and ginsenoside contents were measured. The growth characteristics of aerial and root parts were measured from May to July and from March to December, respectively. For the aerial part, most growth characteristics of WSG decreased over time, except for stem length. For the root part, rhizome length increased over time except for September, while the root diameter and weight of root part were mostly consistent. The root length increased by September, while the number of rootlets was the highest at May. At July, the total ginsenoside content of WSG was significantly the highest, while the total ginsenoside content at October was the lowest. This result was believed to be due to the F2, Rd, and Rg1 contents of the aerial part, rather than the root part. Also, based on these growths and the ginsenoside contents of WSG, the optimal harvest time for WSG is considered to be late spring–summer (May–July) when the aerial part can be identified.

Nutritive value of indian dwarf wheat ears as feed

Interest in growing ancient wheat species and studying the possibility of their use as raw material for feed preparation has increased recently. Indian dwarf wheat (Triticum sphaerococcum Percival) is one of the promising grain crops. The aim of the study was to determine the nutritive value of ears of Indian dwarf wheat in different phases of ripeness for use as raw material in the production of feed in comparison with soft wheat and to determine the rational time frame of their harvesting for feed preparation. Harvesting was carried out by combing without threshing and separation of grain heap in different phases of maturity. The feed was prepared from the grain heap. Chemical analyses of feed samples were performed according to standard methods. The mid-wax ripeness phase is the optimum harvesting time of Indian dwarf wheat for preparation of feed from its ears. Its ears in this phase contain maximum essential amino acids and minimum cellulose. Feed prepared from ears of Indian dwarf wheat has a better quality than feed from soft wheat, as it contains 1.06–2.23 % more of the sum of essential amino acids and 1–5 % more of individual amino acids. This allows the crop to be used in feed preparation to improve protein quality. But its 4–10 % more higher cellulose content than feed from soft wheat is a disadvantage. Grain heap (ears) of Indian dwarf wheat, harvested without threshing in the phase of early wax and mid-wax ripeness, can be a source of increasing the nutritive value of feeds, as it contains more essential amino acids than soft wheat.

Evaluation of Pre-Harvest Nutrient Composition and Functional Active Substances in Various Lotus Roots.

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.

Seasonal dynamics of phytometabolites content in Assam tea, Camellia sinensis var. assamica by LC-MS/MS: Implications for quality

The study examines the seasonal variation in phytometabolite content in Camellia sinensis var. assamica, a prevalent tea variety in Northeast India. Focusing on both bud and dormant leaf (banjhi) samples harvested during the monsoon, autumn, and winter seasons, the research aims to assist cultivators in selecting optimal harvesting times for tea production. An LC-MS/MS method was developed and validated for phytometabolite quantification. Epigallocatechin gallate (EGCG) emerged as the most abundant catechin, with concentrations ranging from 78.01±13.31–125.21±5.65 µg/mg in buds during the monsoon and decreasing to 17.86±1.22–51.11±1.21 µg/mg in winter. Banjhi leaves exhibited even higher EGCG levels, from 203.86±21.06–312.58±28.23 µg/mg in the monsoon, dropping to 74.43±15.22–97.52±8.47 µg/mg in autumn. Similarly, epicatechin gallate concentrations in buds ranged from 17.04±2.57–24.78±1.15 µg/mg in the monsoon and decreased to 5.36±0.39–11.16±1.74 µg/mg in winter, while banjhi leaves showed a decline from 63.61±1.60–72.72±1.23 µg/mg in the monsoon, dropping to 12.73±2.07–15.35±1.33 µg/mg in autumn. The study also noted seasonal variations in catechin hydrate, caffeine, gallic acid, theanine, and theaflavin. These findings underscore the importance of harvest timing for maintaining tea quality and optimizing cultivation and processing practices for sustainability amid environmental changes.

Metabolomic analysis of umami taste variation in Pyropia haitanensis throughout the harvest cycle

Porphyra sensu lato, a highly valuable edible seaweed renowned for its distinctive umami taste, undergoes significant taste variations during the harvest cycle, affecting product quality and pricing. In this study, umami-related metabolites in Pyropia haitanensis were investigated at different harvesting times using GC–MS metabolomic, targeted LC-MS analysis, and an electronic tongue taste evaluation. High concentrations of compounds, including glutamic acid, aspartic acid, and inosine 5′-monophosphate, were identified as the main contributors to the overall umami profile. The concentrations of the compounds and umami-enhancing substances, such as sugars, were negatively correlated as the harvesting period extended. The early harvested P. haitanensis exhibited a superior umami taste, which gradually decreased with subsequent harvest time. Proline, a known cold-resistance metabolite, accumulated as the seawater temperature decreased and the harvest period progressed. These findings provide insights into the optimal cultivation and harvesting practices for maintaining umami quality in P. haitanensis products.

Conventional and artificial intelligence based maximum power point tracking techniques for efficient solar power generation

AbstractThe increasing global need for renewable energy sources, driven by environmental concerns and the limited availability of traditional energy, highlights the significance of solar energy. However, weather fluctuations challenge the efficiency of solar systems, making maximum power point tracking (MPPT) systems crucial for optimal energy harvesting. This study compares ten MPPT approaches, including both conventional and artificial intelligence (AI)‐based techniques. These controllers were designed and implemented using MATLAB Simulink, and their performance was evaluated under real environmental conditions with fluctuating irradiance and temperature. The results demonstrate that conventional techniques, such as incremental conductance (INC), Perturb and Observe (P&amp;O), Incremental conductance and Particle Swam Optimization (INC‐PSO), Fuzzy Logic Control and Particle Swam Optimization (FLC‐PSO), and Perturb and Observe and Particle Swam Optimization (P&amp;O‐PSO), achieved accuracies of 94%, 97.6%, 98.9%, 98.7%, and 99.3% respectively. In contrast, AI‐based intelligent techniques, including Artificial Neural Network (ANN), Artificial Neural Fuzzy Interference System (ANFIS), Fuzzy Logic Control (FLC), Particle Swam Optimization (PSO), and Artificial Neural Network and Particle Swam Optimization (ANN‐PSO), outperform achieving higher accuracies of 97.8%, 99.9%, 98.9%, 99.2%, and 99%, respectively. Compared to available research, which often reports lower accuracies for conventional techniques, our study highlights the enhanced performance of AI‐based methods. This study provides a comprehensive comparative analysis, delivering critical analysis and practical guidance for engineers and researchers in selecting the most effective MPPT controller optimized to specific environmental conditions. By improving the efficiency and reliability of solar power systems, our research supports the advancement of sustainable energy solutions.

Ultrasonic-Assisted Extraction of Phenolic Compounds from Lonicera similis Flowers at Three Harvest Periods: Comparison of Composition, Characterization, and Antioxidant Activity.

Lonicera similis Hemsl. (L. similis) is a promising industrial crop with flowers rich in phenolic compounds. In this study, an ultrasound-assisted extraction (UAE) was designed to extract phenolic compounds from L. similis flowers (LSFs). A contrastive analysis on the phenolic compounds' yield and characterization and the antioxidant activity of the extracts at three harvest stages (PGS I, PGS II, and PGS III) are reported. The results indicate that the optimal conditions are a sonication intensity of 205.9 W, ethanol concentration of 46.4%, SLR of 1 g: 31.7 mL, and sonication time of 20.1 min. Under these optimized conditions, the TPC values at PGS I, PGS II, and PGS III were 117.22 ± 0.55, 112.73 ± 1.68, and 107.33 ± 1.39 mg GAE/g, respectively, whereas the extract of PGS I had the highest TFC (68.48 ± 2.01 mg RE/g). The HPLC analysis showed that chlorogenic acid, rutin, quercetin, isoquercitrin, and ferulic acid are the main components in the phenolic compounds from LSFs, and their contents are closely corrected with the harvest periods. LSF extracts exhibited a better antioxidant activity, and the activity at PGS I was significantly higher than those at PGS II and PGS III. The correlation analysis showed that kaempferol and ferulic acid, among the eight phenolic compounds, have a significant positive correlation with the antioxidant activity, while the remaining compounds have a negative correlation. Minor differences in extracts at the three harvest stages were found through SEM and FTIR. These findings may provide useful references for the optimal extraction method of phenolic compounds from LSFs at three different harvest periods, which will help to achieve a higher phytochemical yield at the optimal harvest stage (PGS I).

Physicochemical Characterization and Nutrient Composition Decide Harvest Maturity of Cucumis melo Varieties

Cucumis melo is a polymorphic taxon belonging to the family Cucurbitaceae, with several varieties based on ovary pubescence. Cucumis melo var. momordica and Cucumis melo var. acidulus are popularized and highly cultivated forms in South India. The characteristic of C.melo var.momordica is its fruit-cracking nature, which distinguishes the variety from others when it is ready to harvest. So, it would be a herculean task for the farmers to harvest ripened fruits before it gets cracked. Analysis of the ripening process's physicochemical attributes and nutritional composition is inevitable to understand and establish proper harvest management for the varieties. The current study was conducted in the experimental field of the Department of Botany, University of Kerala using two different melon varieties, Cucumis melo var. momordica (Roxb.) Duthie &amp; Fuller (Snap melon) and Cucumis melo var. acidulus L. Naudin (culinary melon), from January to October 2021. Fruits were harvested at five developmental stages (S1: 5 days after pollination (DAP), S2: 10 DAP, S3:15 DAP, S4: 20 DAP, S5: 25 DAP) and analysed for physical and biochemical characters. Results were analyzed statistically by using one way ANOVA (P≤0.05). Pomological characteristics such as fruit weight and length at different developmental stages showed a tremendous peak from S3 to S5 in both varieties. However, the firmness of the fruits decreased from the S4 to S5 stage in varieties, reducing sugar accumulated sharply from the S2 to S3 stage. Titratable acidity content in Cucumis melo fruits continuously increased from the S1 to S5 stage. On the other hand, the total carbohydrate, cellulose, protein, and amino acid content increased from S1 to S2 but decreased sharply in S3 and S5. Ascorbic acid, total phenolics, lipid peroxidation, and electrolyte leakage levels declined with fruit ripening in Cucumis melo varieties. As a result of all the quality parameters mentioned above, Cucumis melo fruit harvested at the S4 maturity stage was the ideal harvest maturity for long-distance transportation and had higher consumer acceptability before fruit cracking. Our findings showed that the physical-biochemical properties and nutritional composition of Cucumis melo varieties change dynamically during ripening. The study highlighted the significance of maturity stages for fruit quality and provided critical information for optimal harvest management of the fruits of Cucumis melo varieties.

Variation in Soluble Sugars in Arabica Coffee Cherry Fruits.

The maturation of Arabica coffee fruits is influenced by both endogenous and external factors. The stage of fruit maturation affects the chemical composition of the beans, which in turn impacts the quality of the coffee beverage. During maturation, the fruit peel changes colour from green to red (cherry), signalling the optimal harvest time and suggesting high fruit quality. However, the degree of redness can vary, indicating different levels of maturity. This study aimed to explore the variation in soluble sugar accumulation in relation to the redness of coffee fruit tissues. We classified ripe fruits into six ripeness categories based on the intensity of the red colour of the epicarp, measured using a colourimeter. We analysed total soluble sugar, sucrose, and starch in three parts: coat (exocarp + mesocarp), coat juice (obtained by squeezing the coat), and beans. Our findings reveal that the variation in sugar in the endosperm does not correspond to changes in the coat, suggesting separate regulation of sugar accumulation, particularly sucrose, which is crucial for coffee quality. Our data indicate that there is no transfer of sucrose and reducing sugars from the red coat to the bean.

Optimal harvest period and quality control markers of cultivated Flos Chrysanthemi Indici using untargeted/targeted metabolomics, chemometric analysis and in vivo study

Ethnopharmacological relevanceFlos Chrysanthemi Indici (FCI), the flower of Chrysanthemum Indicum L., is a popular traditional Chinese medicine (TCM) for treatment of inflammatory diseases in China. FCI is also a functional food, and is widely used as herbal tea for clearing heat and detoxicating. Aim of the studyTo explore quality control markers of FCI based on the optimal harvest period. Materials and methodsFirst, UPLC-Q-TOF/MS based untargeted metabolomics was applied to explore the chemical profiles of FCIs collected at bud stages (BS), initial stages (IS), full bloom stages (FS) and eventual stages (ES) from eight cultivated regions in China. Subsequently, lipopolysaccharide (LPS)-induced RAW264.7 cell inflammatory model and carrageenan-induced rat paw edema model were used to confirm the anti-inflammatory effect of FCIs collected at IS/FS. Then, UPLC-PDA targeted metabolomics was used to quantitatively analyze 9 constituents with anti-inflammatory activity (7 flavonoids and 2 phenolic acids) changed significantly (VIP > 4) during flowering stages. Finally, ROC curves combined with PCA analysis based on the variation of 9 active constituents in FCIs from different flowering stages were applied to screen the quality markers of FCI. ResultsFCIs at IS/FS had almost same chemical characteristics, but quite different from those at BS and ES. A total of 32 constituents in FCIs including flavonoids and phenolic acids were changed during flowering development. Most of the varied constituents had the highest or higher contents at IS/FS compared with those at ES, indicating that the optimal harvest period of FCI should be at IS/FS. FCI extract could effectively suppress nitric oxide (NO) production in LPS-induced RAW264.7 cells and regulate the abnormal levels of cytokines and PGE2 in carrageenan-induced paw edema model rat. The results of quantitatively analysis revealed that the variation trends of phenolic acids and flavonoids in FCIs were different during flowering development, but most of them had higher contents at IS/FS than those at ES in all FCIs collected from eight cultivated regions, except one sample from Anhui. Finally, linarin, luteolin, apigenin and 3,5-dicaffeoylquinic acid were selected as the Q-markers based on the contribution of their AUC values in ROC and clustering of PCA analysis. ConclusionsOur study demonstrates the optimal harvest period of FCI and specifies the multi-constituents Q-markers of FCI based on the influence of growth progression on the active constituents using untargeted/targeted metabolomics. The findings not only greatly increase the utilization rate of FCI resources and improve quality control of FCI products, but also offer new strategy to identify the Q-markers of FCI.

A comparative study of acoustic and ultrasonic nondestructive testing for evaluating melon quality

Abstract Melon (Cucumis melo L.) is a high-value agricultural commodity known worldwide for its sweet taste and crisp flesh texture, which are important factors for quality and consumer acceptance. Unfortunately, quality testing and determining the optimal harvest time for achieving desired melon characteristics are traditionally performed through destructive methods. The aim of this study was to explore the potential of acoustic and ultrasonic tests for predicting the physicochemical properties of Honey Globe melons (Cucumis melo L. var. inodorus). A total of 100 melon samples were used in this study. For the nondestructive ultrasonic testing, attenuation values served as its variable, whereas in acoustic testing, variables included frequency, magnitude, short-term energy, and zero-moment. Fruit’s flesh firmness and total soluble solids (TSS) as physicochemical quality properties were determined using destructive tests. The calibration phase involved 80 melon samples, employing a K-Fold Cross Validation approach with ten folds, done on Partial Least Square Regression (PLS) modeling. Another 20 melon samples were used for blind testing. Reliability evaluation was done on key metrics, consisting of R2 values, RMSEC (Root Mean Square Error of Calibration), RMSECV (Root Mean Square Error of Cross-Validation), RMSEP (Root Mean Square Error of Prediction), and RPD (Ratio of Performance to Deviation). Analysis results on these metrics collectively support the conclusion that both ultrasonic and acoustic methods exhibit their potential to predict the firmness properties of melon fruits. The best evaluation result that has been conducted for the ultrasonic test uses attenuation, age, and density as predictors to predict fruit firmness, with R2 = 0.763 and RPD = 2.945, while the acoustic test achieved the best result with magnitude used as a predictor to predict fruit firmness with R2 = 0.718 and RPD = 2.230. However, evaluation metrics on the prediction of total soluble solids for both nondestructive tests were still not good enough for application with low R2 and RPD value.

Smart irrigation system using node microcontroller unit ESP8266 and Ubidots cloud platform

The agricultural irrigation system is extremely important. For optimal harvest yields, farmers must manage rice plant quality by monitoring water, soil, and temperature on agricultural fields. If market demand rises, traditional rice field irrigation in Indonesia will make things harder for farmers. This modern era requires a system that lets farmers monitor and regulate agricultural fields anywhere, anytime. We need a solution that can control the irrigation system remotely using an internet of things (IoT) device and a smartphone. This study employed the Ubidots IoT cloud platform. In addition, the study uses soil moisture and temperature sensors to monitor conditions in agricultural regions, while pumps function as irrigation systems. The test results indicate the proper design of the system. Each trial collected data. The pump will turn on and off automatically based on soil moisture criteria, with the pump active while the soil moisture is less than 20% and deactivated when the soil moisture exceeds 20%. In simulation mode, the pump operates for an average of 0–5 seconds of watering. The monitoring system shows the current soil temperature and moisture levels. Temperature sensors respond in 1-3 seconds, whereas soil moisture sensors respond in 0–4 seconds.

Smart irrigation system using node microcontroller unit ESP8266 and Ubidots cloud platform

The agricultural irrigation system is extremely important. For optimal harvest yields, farmers must manage rice plant quality by monitoring water, soil, and temperature on agricultural fields. If market demand rises, traditional rice field irrigation in Indonesia will make things harder for farmers. This modern era requires a system that lets farmers monitor and regulate agricultural fields anywhere, anytime. We need a solution that can control the irrigation system remotely using an internet of things (IoT) device and a smartphone. This study employed the Ubidots IoT cloud platform. In addition, the study uses soil moisture and temperature sensors to monitor conditions in agricultural regions, while pumps function as irrigation systems. The test results indicate the proper design of the system. Each trial collected data. The pump will turn on and off automatically based on soil moisture criteria, with the pump active while the soil moisture is less than 20% and deactivated when the soil moisture exceeds 20%. In simulation mode, the pump operates for an average of 0–5 seconds of watering. The monitoring system shows the current soil temperature and moisture levels. Temperature sensors respond in 1-3 seconds, whereas soil moisture sensors respond in 0–4 seconds.

Probiotic Growth Pattern and Physicochemical Evaluation of Water Kefir Fermentation

Probiotics are live-friendly microorganisms that can confer a health benefit on the host if it is consumed in sufficient amounts. Water kefir is a probiotic-rich fermented beverage that contains multi-species of live cultures. Brown sugar and palm sugar were used for water kefir fermentation due to their high sucrose and mineral contents. The objective of this study was to determine the probiotic growth pattern of water kefir and to evaluate the physicochemical parameters, including the pH changes, lactic acid content, reducing sugar content, and total soluble solids. The fermented water kefir was collected at every 6-hour interval, until the end of 72 hours of fermentation. The growth curve was determined by enumerated probiotics on De Man, Rogosa, and Sharpe (MRS) agar, Yeast Extract-Peptone-Dextrose (YPD) agar, and Gluconobacter (GM) agar plates, respectively. MRS, YPD, and GM agar plates were used to enumerate lactic acid bacteria, yeast, and acetic acid bacteria, respectively. The result showed increased probiotic growth as fermentation time increased with different phases observed from the growth curve. The stationary phase of probiotics was recorded at 30-42 h and was recommended as the optimal harvesting point. Besides, longer fermentation time produced lower pH values and lower total soluble solids while higher lactic acid and higher reducing sugars. At the end of fermentation, the concentration of lactic acid and reducing sugars were 2.16 ± 0.09 g/L and 13.66 ± 0.14 mg/mL, respectively. In conclusion, probiotics from water kefir fermentation are suggested to be best harvested between 30-42 hours and can be used for self-consume or downstream processing.

Optimal Harvesting Strategies for Timber and Non-Timber Forest Products with Nonlinear Harvesting Terms

Optimal Harvesting Strategies for Timber and Non-Timber Forest Products with Nonlinear Harvesting Terms

Exogenous regulation of macronutrients promotes the accumulation of alkaloid yield in anisodus tanguticus (Maxim.) pascher

BackgroundAnisodus tanguticus (Maxim.) Pascher (A. tanguticus) is a valuable botanical for extracting tropane alkaloids, which are widely used in the pharmaceutical industry. Implementing appropriate cultivation methods can improve both the quality and yield of A. tanguticus. A two-year field experiment was conducted from 2021 to 2023 using a single-factor randomized complete block design replicated three times. The study examined the effects of different nutrient levels (nitrogen: 0, 75, 150, 225, 300, 375 kg/ha; phosphorus: 0, 600, 750, 900, 1050, 1200 kg/ha; potassium: 0, 75, 112.5, 150, 187.5, 225 kg/ha) on the growth, primary alkaloid contents, and alkaloid yield of A. tanguticus at different growth stages (S-Greening, S-Growing, S-Wilting; T-Greening, T-Growing, and T-Wilting) in both the roots and aboveground portions.ResultsOur results demonstrate that nutrient levels significantly affect the growth and alkaloid accumulation in A. tanguticus. High nitrogen levels (375 kg/ha) notably increased both root and aboveground biomass, while phosphorus had a minimal effect, especially on aboveground biomass. For alkaloid content (scopolamine, anisodamine, anisodine, atropine), a moderate nitrogen level (225 kg/ha) was most effective, followed by low potassium (75 kg/ha), with phosphorus showing a limited impact. Increased phosphorus levels led to a decrease in scopolamine content. During the T-Growing period, moderate nitrogen addition (225 kg/ha) yielded the highest alkaloid levels per unit area (205.79 kg/ha). In the T-Wilting period, low potassium (75 kg/ha) and low phosphorus (750 kg/ha) resulted in alkaloid levels of 146.91 kg/ha and 142.18 kg/ha, respectively. This indicates nitrogen has the most substantial effect on alkaloid accumulation, followed by potassium and phosphorus. The Douglas production function analysis suggests focusing on root biomass and the accumulation of scopolamine and atropine in roots to maximize alkaloid yield in A. tanguticus cultivation.ConclusionsOur findings show that the optimum harvesting period for A. tanguticus is the T-Wilting period, and that the optimal nitrogen addition is 225 kg/ha, the optimal potassium addition is 75 kg/ha, and the optimal phosphorus addition is 600 kg/ha or less.

Dynamics and Optimal Harvesting for Fishery Models with Reserved Areas

Dynamics and Optimal Harvesting for Fishery Models with Reserved Areas

The impact of pollution reduction on the optimal harvesting strategy in a seasonally changing and polluted environment

The impact of pollution reduction on the optimal harvesting strategy in a seasonally changing and polluted environment