Optimum Yield Research Articles

The Influence of Shade on the Growth and Production of Butterfly Pea Plants (Clitoria ternatea)

Butterfly pea (Clitoria ternatea L.) is a medicinal plant known for its anthocyanin pigment content, which imparts a blue color to its flowers. This study aimed to evaluate the influence of shading on butterfly pea flower growth and production. The research design utilized a randomized complete block design (RCBD) for shading treatments. We replicated each treatment level four times, resulting in 20 experimental units, each containing four plants, for a total population of 80 plants. We conducted the experiment at the Experimental Garden of Gunadarma University Campus F7, implementing shade nets at different intensity levels (55%, 65%, 75%, and 85%), along with a control treatment without shading. We made observations on various plant growth parameters such as leaf count, plant length, days to first flower appearance, flower count, fresh weight, and dry weight. The results indicated that shading significantly influenced butterfly pea plants' growth. Plants without shading tended to exhibit better growth in several parameters, such as increased leaf count, higher plant length, and earlier days to first flower appearance. These findings underscore the importance of sunlight in supporting the growth and production of butterfly pea plants. Therefore, careful consideration of shade management is essential in agricultural practices to ensure optimal growth and maximum yield from butterfly pea plants.

Growth and production of cat's whiskers plant biomass (Orthosiphon aristatus Bl. Miq.) In various accessions and harvest intervals

Cat's whiskers plant is an ornamental plant used as a medicinal plant. The part of the cat's whiskers plant used is leaves. Accessions and harvest intervals are essential for increasing optimal yields to plant biomass growth and results. This study aims to determine the effect of differences in accession, intervals, and interactions between accession differences and intervals on the growth and production of a cat's whiskers biomass. The design used in this study is a complete group design of being randomized with two treatment factors. The first factor has two treatment levels: white flowering accessions (A1) and purple flowering accessions (A2). The second factor is a harvest interval with four treatment levels, namely a 1-week harvest interval (P1), two weeks (P2), three weeks (P3), and six weeks (P4). The results showed that accession treatment significantly affected the number of books, number of branches, flowering ages, leaf fresh weight, leaf dry weight, and leaf simplicia yields. Harvest interval treatment significantly affects the height of the shoots, number of shoots, number of branches, number of leaves, flowering ages, leaf fresh weight, stem fresh weight, flower fresh weight, leaf dry weight, stem dry weight, flower dry weight, and leaf simplicia yield. Accession interactions with harvest intervals significantly affect the height of the shoots, number of shoots, number of branches, number of leaves, flower fresh weight, stem dry weight, and leaf simplicia yields.

Optimizing quercetin and kaempferol extraction from Moringa oleifera leaves via ultrasonic assisted extraction: Kinetic modeling and process optimization

Flavonols, such as quercetin and kaempferol, are pigments found in Moringa oleifera leaves (M. oleifera), which show potential medical values that can be extracted using various extraction methods. This study employed direct probe ultrasound-assisted extraction (UAE) to extract quercetin and kaempferol compounds from M. oleifera leaves. We used the one-factor-at-a-time (OFAT) method to investigate five operating parameters: solvent concentration, extraction temperature, extraction time, amplitude, duty of cycle, and solid-to-solvent ratio, in order to identify the most important extraction parameters. The OFAT experiment's results prompted the development of a Box-Behnken Design (BBD) for processing parameter optimization. According to the BBD results, the solvent concentration had little influence on the yields, however the extraction duration had a considerable impact on all of them. After a few runs, the measured yields acquired under predicted processing parameters matched the results that were expected. The findings showed that the highest amounts of quercetin and kaempferol were obtained when 60 % ethanol was used, the extraction process of 14 minutes, the temperature of 48 °C, and the ratio of liquid to solid (L/S) of 45:1 ml/g. The structural surface of M. oleifera leaves changed after exposure to the UAE process and maceration extraction, as revealed by scanning electron microscopy (SEM). These results imply that the UAE has the potential to extract the phenolic compound from M. oleifera leaves at optimal processing parameters with optimal yields.

Production of biodiesel from non-edible waste palm oil and sterculia foetida using microwave irradiation

Abstract The environmental damage stemming from traditional diesel begins during crude oil extraction and persists throughout its usage. The burning of fossil fuels has further deteriorate the environmental effect and added to global warming by emitting harmful substances. Moreover, the reduction of finite fossil fuel reserves due to widespread extraction has made the adoption of renewable resources essential. Given these considerations, biodiesel emerges as a highly promising alternative to conventional diesel due to its environmentally beneficial nature, renewable source, and economic feasibility. In this study, biodiesel was prepared by a microwave reactor in the presence of potassium methoxide using blended waste palm oil and sterculia foetida. The effects of raw materials characteristics on transesterification products were studied. The studied process parameters were methanol/oil ratio, microwave temperature, catalyst concentration, reaction time, and stirring speed. The optimal yield with 98.5% FAME content was obtained at a methanol/oil ratio of 60 vol. %, microwave temperature of 120 °C, catalyst concentration of 0.3 wt.%, and 3 min reaction time, and stirring speed of 500 rpm. The potassium methoxide was used to catalyse the transesterification process. The physicochemical properties and the fatty acid methyl ester composition were discussed thoroughly. The flash point of biodiesel, at 157.5°C, exceeds that of diesel fuel by more than two times. The cetane index is 59.5 which is higher than diesel (49.6). The biodiesel’s fuel properties conformed to the requirements of both ASTM D6751 and EN 14214. High biodiesel conversion and low sulphur content show that waste palm oil and sterculia foetida are sustainable and economical feedstocks that produce clean fuel to aid the feasibility of the energy transition of the global energy sector. In addition, the selection of synthesis approaches can be further explored for potential catalysts to ensure eco-green biodiesel’s sustainability with minimised.

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.

Real-Time Precision Irrigation System for Optimal Crop Yield and Water Conservation

Real-Time Precision Irrigation System for Optimal Crop Yield and Water Conservation

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.

Optimization of bio-oil production from macroalgae, caulerpa lentillifera via hydrothermal liquefaction

Abstract An environmentally friendly method of producing bio-oil through the hydrothermal liquefaction (HTL) of algae has emerged, providing a path toward renewable energy and reducing greenhouse gas emissions. Algae is currently received a lot of interest as biomass feedstock due to its long growing season in warm climate area, does not require arable land, and relatively rapid growing rate. This study aims to optimize the HTL process of macroalgae (Caulerpa lentillifera) for bio-oil production, focusing on optimizing the bio-oil yield based on three parameters (operating temperature, the loading size of catalyst sodium hydroxide (NaOH), and algae-to-water ratio) using Box Behnken Design (also generally known as Response Surface Methodology). The results showed that an ideal reaction temperature of 277 °C, a 1:10 algae-to-water ratio, and 0.88 wt% catalyst loading led to an optimal experimental bio-oil yield of 11.65 wt%. Sensitivity study also revealed that the temperature is the second most important component, after the algae-to-water ratio. The difference in the catalyst loading showed low impact on the HTL of algae. Slight improvement to the bio-oil yield under the presence of NaOH is mainly due to the alkali environment provided by NaOH. The FTIR spectrum revealed the existence of various functional groups in the bio-oil. In summary, HTL has been effective in turning Caulerpa lentillifera into useful bio-oil. Overall, this study contributes to the growing body of research on algae-based bio-oil production. The results highlighted the potential of HTL as a promising technology for sustainable biofuel production, offering a pathway towards a greener and more energy-efficient future.

Enhancing Photocatalytic Activity for Solar‐to‐Fuel Conversion: A Study on S‐Scheme AgInS2/CeVO4@Biocharx Heterojunctions

AbstractRare earth vanadates are promising for solar‐to‐fuel conversions, yet their photocatalytic efficiency is limited by the substantial recombination of photo‐generated carriers. Constructing heterojunctions is recognized as an effective approach to improving charge carrier separation in vanadates. Nonetheless, inefficient charge transfer often results from the poor quality of interfaces and non‐directional charge transfer within these heterojunctions. Herein, an S‐scheme AgInS2/CeVO4@Biocharx (AIS/CV@Cx) heterojunction photocatalyst is designed and synthesized through a straightforward freeze‐drying and calcination three‐step process, aimed at photocatalytic co‐production of xylonic acid and carbon monoxide (CO) from xylose. The AIS/CV@C2 heterojunction achieves an optimal yield of 67.74% for xylonic acid and a CO release of 29.76 µmol from xylose. The enhanced photocatalytic performance of the AIS/CV@C2 heterojunction is attributed to three key factors: I) the high‐quality interface and intimate contact within the AIS/CV@C2 heterojunction significantly reduce undesirable carriers recombination, II) the staggered band structures and directed carriers transfer in the AIS/CV@C2 heterojunction notably improve spatial carriers separation/migration, and III) the incorporation of biochar boosts the conductivity of the AIS/CV@C2 heterojunction. This work presents a straightforward yet effective method for fabricating vanadate heterojunctions, highlighting the importance of quality interfacial contact and directed charge transfer in amplifying photocatalytic performance.

Influence of higher levels of NPK fertilizers on growth, yield, and profitability of three potato varieties in Surma, Bajhang, Nepal

Potato is a crucial food and cash crop with high yield potential in many parts of the Bajhang district. However, achieving optimal yields can be hindered by inconsistent NPK fertilizer application rates and suboptimal potato variety selection, including instances where no fertilizers are used at all by the farmers. To address these challenges and determine the most effective NPK fertilizer rates and potato varieties, a field experiment was conducted in Surma rural municipality of Bajhang district. The experiment utilized a randomized complete block design (RCBD) with three replications, to evaluate the effects of four NPK fertilizer rates (0:0:0, 50:50:50, 100:100:60, and 150:150:90 kg NPK/ha) and three potato varieties (Khumal Seto, Cardinal, and Bajhang Local), on growth, yield, and economic profitability. Statistical analysis, including analysis of variance and Duncan's multiple range test (DMRT), indicated that the highest values for plant height, canopy diameter, number of leaves, number of main stems, tuber weight, fresh weight of leaves and stems, average tuber diameter and number of marketable tubers per hill were consistently observed higher in either the Khumal Seto or Bajhang Local potato varieties. Similarly, these results were particularly prominent with the application of 150:150:90 kg NPK/ha. Economic analysis demonstrated that the Khumal Seto variety showed superior performance in terms of gross benefit, net benefit, and benefit-to-cost ratio (NPR 1,805,714.29, NPR 1,306,168.83, and 3.61, respectively) when compared to other varieties. Similarly, the application of 150:150:90 kg NPK/ha resulted in higher economic returns (NPR 1,645,714.29, NPR 1,129,908.83, and 3.19). In conclusion, using higher levels of mineral fertilizers (150:150:90 kg NPK/ha) with high yielding and well adapted potato varieties such as Khumal Seto and Bajhang Local significantly enhances growth, yield, and profitability in potato cultivation, as demonstrated by the findings of this study.

STATISTICAL OPTIMIZATION OF ANTIOXIDANT AND EXTRACTION YIELD FROM CENTELLA ASIATICA LEAVES

This study focuses on the statistical optimization of antioxidant and extraction yield from Centella asiatica leaves using Central Composite Designs (CCD) and response surface methodology. The primary objective was to identify influential variables affecting the extraction process, such as extraction time and temperature, using ultrasonic-assisted extraction. The optimized extraction conditions yielded an antioxidant activity of 52.4420%, Total Phenolic Content (TPC) of 0.5000 mg/g, and Total Flavonoid Content (TFC) of 15.3125 mg/g. Statistical analysis revealed significant model terms with an R² value of 0.930, indicating that 93% of the variability in antioxidant yield could be explained by the model. The 'Adeq Precision' ratio of 15.479 confirmed an adequate signal, and the Model F-value of 15.16 (p = 0.0043) highlighted the significance of the model. The findings demonstrate a viable and efficient technique for maximizing the extraction yield of bioactive components from C. asiatica, providing a robust framework for enhancing the efficiency of extracting valuable antioxidants from medicinal plants, which is crucial for natural product research and herbal medicine.

Examine the Effects of Inter Row Spacing, Weeding Frequency and Weed Infestation on Agro Morphological Traits and Yield of Durum Wheat (Triticuma Durum Desf.) Variety in Bedesa, Oromia, Ethiopia

According to study, durum wheat (Triticum durum Desf.), is an important food crop in the world, with an estimated annual production of 36 million tons. Randomized complete block design was employed. With a relative density 74.6%, broadleaved weed species were the most dominant followed by grasses with relative density of 24.3%. Number of tillers per plant, plant height, Grains per spike, aboveground biomass yield, and grain yield were affected by the interaction of weeding frequency and spacing. Spacing and Weeding frequency were significantly affected days to heading, spike length, thousand grain weight and harvest index. Wider spacing, four wedding and control weeding frequencies had significantly yield components of durum wheat. Highest dry biomass weight was achieved by treatments with 10 cm row spacing for both grass and wide weed species. As study sowing durum wheat with 30 cm row spacing and keeping it completely weed free resulted in optimum growth and grain yield.

Influence of Mn on dry yield and nutrient uptake by new jute variety BJRI Tossa-7

A field experiment was conducted during the year 2018-2019 at the vital place of Bangladesh Jute Research Institute (BJRI), Dhaka. The aim of the study was to evaluate the influence of Mn fertilizer on the dry matter yield and potential nutrient uptake of the newly developed jute variety BJRI Tossa jute-7. The treatments used in the experiments were T1: Control, T2: RDF sole (N90P10 K30 S20kg/ha), T3: RDF + 1 kg Mn/ha, T4: RDF + 2 kg Mn/ha, T5: RDF + 3 kg Mn/ha and T6: RDF + 4 kg Mn/ha. Mn application had a favorable effect on the dry matter yield of jute. Among the fertilizers of Mn with RDF, interaction promoted the dry yield biomass compared to sole RDF and control. Maximum dry matter yield (leaves + shoots + roots) achieved (20000 kg/ha) with T5 (RDF + 3 kg Mn/ha) and minimum (6421 kg/ha) in T1 (control). Study indicated that it needs to apply Mn to obtain optimum yield production. The interaction effect of Mn, NPK and S fertilizer significantly influenced nutrient uptake by the jute plant. The uptake of nutrient found highest N (218.9 kg/ha) in T5, P (92.75 kg/ha) in T3, K (239.73 kg/ha) with T6, S (19.59 kg/ha) in T4, Fe (0.64 kg/ha) in T5, Zn (0.38 kg/ha) in T5 and Mn (0.63 kg/ha) recorded in T6. The amount of micro nutrient uptake may be arranged in the order of Mn >Zn> Fe. Considering the highest uptake of major element, it can be kept as in the order of K > N>P>S. Study indicated that a higher rate of nutrient uptake was promoted dry matter accumulation in jute. Research revealed that the rate of nutrient uptake maximized with the addition of Mn in the RDF treatment. Hence, it could be concluded that applying RDF + 3 kg Mn/ha may be a suitable dose for optimum yield production of jute. Yet, in order to draw a sound conclusion, repeating the experiment is needed. In the future, the study will be a guideline for further investigation. Int. J. Agril. Res. Innov. Tech. 14(1): 87-95, June 2024

Process-constrained batch Bayesian approaches for yield optimization in multi-reactor systems

The optimization of yields in multi-reactor systems, which are advanced tools in heterogeneous catalysis research, presents a significant challenge due to hierarchical technical constraints. To this respect, this work introduces a novel approach called process-constrained batch Bayesian optimization via Thompson sampling (pc-BO-TS) and its generalized hierarchical extension (hpc-BO-TS). This method, tailored for the efficiency demands in multi-reactor systems, integrates experimental constraints and balances between exploration and exploitation in a sequential batch optimization strategy. It offers an improvement over other Bayesian optimization methods. The performance of pc-BO-TS and hpc-BO-TS is validated in synthetic cases as well as in a realistic scenario based on data obtained from high-throughput experiments done on a multi-reactor system available in the REALCAT platform. The proposed methods often outperform other sequential Bayesian optimizations and existing process-constrained batch Bayesian optimization methods. This work proposes a novel approach to optimize the yield of a reaction in a multi-reactor system, marking a significant step forward in digital catalysis and generally in optimization methods for chemical engineering.

Using machine learning algorithms to cluster and classify stone pine (Pinus pinea L.) populations based on seed and seedling characteristics

AbstractThe phenotype of a woody plant represents its unique morphological properties. Population discrimination and individual classification are crucial for breeding populations and conserving genetic diversity. Machine Learning (ML) algorithms are gaining traction as powerful tools for predicting phenotypes. The present study is focused on classifying and clustering the seeds and seedlings in terms of morphological characteristics using ML algorithms. In addition, the k-means algorithm is used to determine the ideal number of clusters. The results obtained from the k-means algorithm were then compared with reality. The best classification performance achieved by the Random Forest algorithm was an accuracy of 0.648 and an F1-Score of 0.658 for the seed traits. Also, the best classification performance for stone pine seedlings was observed for the k-Nearest Neighbors algorithm (k = 18), for which the accuracy and F1-Score were 0.571 and 0.582, respectively. The best clustering performance was achieved with k = 2 for the seed (average Silhouette index = 0.48) and seedling (average Silhouette Index = 0.51) traits. According to the principal component analysis, two dimensions accounted for 97% and 63% of the traits of seeds and seedlings, respectively. The most important features between the seed and seedling traits were cone weight and bud set, respectively. This study will provide a foundation and motivation for future efforts in forest management practices, particularly regarding reforestation, yield optimization, and breeding programs.

Rancang Bangun Mesin Digesting Tandan Kosong Kelapa Sawit Sebagai Bahan Baku Brown Paper

Indonesia's pulp and paper production capacity was 5.5% of global production capacity in 2021. As an effort to support the development of the pulp and paper industry in Indonesia, pulp from empty oil palm fruit bunches (EFB) waste which are currently abundant is being tried to develope as raw material for brown paper. To simplify the process of developing pulp quality from EFB, the authors tried to design a rotary digester on a laboratory scale as a EFB digesting machine. The steps used in this research are assembling digester, making pulp, and finally analyzing the data. The digester machine was successfully designed to carry out the pulping process with operating conditions at a pressure of 7 bar, a temperature of 160°C, and a stirrer speed of 80 rpm with a maximum capacity of 1.3 L. The designed rotary digester is capable of producing pulp with an optimal yield level (43%) under reaction conditions, a temperature of 100°C and a NaOH concentration of 5%.

Adjacent Reaction Sites of Atomic Mn2O3 and Oxygen Vacancies Facilitate CO2 Activation for Enhanced CH4 Production on TiO2-Supported Nickel-Hydroxide Nanoparticles

The catalytic conversion of carbon dioxide (CO2) to methane (CH4) through the “Sabatier reaction”, also known as CO2 methanation, presents a promising avenue for establishing a closed carbon loop. However, the competitive reverse water gas shift (RWGS) reaction severely limits CH4 production at lower temperatures; therefore, developing highly efficient and selective catalysts for CO2 methanation is imperative. In this regard, we have developed a novel nanocatalyst comprising atomic scale Mn2O3 species decorated in the defect sites of TiO2-supported Ni-hydroxide nanoparticles with abundant oxygen vacancies (hereafter denoted as NiMn-1). The as-prepared NiMn-1 catalyst initiates the CO2 methanation at a temperature of 523 K and delivers an optimal CH4 production yield of 21,312 mmol g−1 h−1 with a CH4 selectivity as high as ~92% at 573 K, which is 45% higher as compared to its monometallic counterpart Ni-TiO2 (14,741 mmol g−1 h−1). Physical investigations combined with gas chromatography analysis corroborate that the exceptional activity and selectivity of the NiMn-1 catalyst stem from the synergistic cooperation between adjacent active sites on its surface. Specifically, the high density of oxygen vacancies in Ni-hydroxide and adjacent Mn2O3 domains facilitate CO2 activation, while the metallic Ni domains trigger H2 splitting. We envision that the obtained results pave the way for the design of highly active and selective catalysts for CO2 methanation.

Effects of Spacing and Varieties on the Growth and Yield of Cowpea (Vignauguiculata L.). Grown in Makurdi, Benue State. Nigeria

A field experiment was carried out at the Agronomy Teaching and Research Farm of Joseph Sarwun, Tarka, University Makurdi, Benue State Nigeria at 70 41N and Longitude 80 37E, 400m above sea level in Southern Guinea Savannah Agro-ecological zone of Nigeria to investigate the Effects of Spacing and Variety on the Growth and Yield of Cowpea (Vignauguiculata L.). Two spacing were used 25 and 30cm intra row spacing and three medium maturing varieties of IT07K-274-2-9, IAR-07-1050 and UAM-1051-1 were used for study. The treatment were combined and laid in a randomized complete block design with three replications. During the research, growth characters such as plant height, number of leaves, days of maturity, 50% flowering were measured. Other yield and yield related characters like number of pod, number of seed, 1000 seed weight and seed yield were also recorded. The use of 30cm intra row spacing produced significantly (P=0.05) in both growth and yield related parameters except in plant height where 25cm spacing had taller plants (61.21), days to maturity (79.45) and 50% flowering (60.21) while spacing 30cm had higher number of leaves (50.11) higher number of pod per plants (46.01), number of seeds per pod (10.99), weightier pod (900.11), weightier 100 seeds (120.56) and over all yield (681.16) The use of medium maturing varieties was also observed to produce significantly (P=0.05) with 1T07K-274-2-9 recorded early days of maturity (79.11), 50% days of flowering (61.21) and number of pod (47.21) while UAM-1050-1 produced taller plant (62.01), higher number of leaves (51.21) higher number of seeds per pod(11.50) pod weight(1084.01),100 seed weight (22.68) and overall yield (698.82).Form the result cowpea farmers in Makurdi are advice to grow UAM-105-1 at 30cm intra row spacing for optimum yield.

Extraction of Bioactive Compounds from Wine Lees: A Systematic and Bibliometric Review.

The extraction of bioactive compounds from wine lees involves a variety of methods, the selection of which is crucial to ensure optimal yields. This systematic review, following PRISMA guidelines and utilizing the Web of Science database, aimed to examine the current state of this field, providing insights for future investigations. The search employed strategies with truncation techniques and Boolean operators, followed by a three-step screening using well-defined eligibility criteria. A bibliometric analysis was conducted to identify authors, affiliations, countries/regions, and research trends. Thirty references were selected for analysis, with Spain standing out as the main source of research on the topic. The majority of studies (66%) focused on the extraction of bioactive compounds from alcoholic fermentation lees, while 33% were directed towards malolactic fermentation lees. Binary mixtures (ethanol-water) were the predominant solvents, with ultrasound being the most used extraction method (31.3%), providing the highest average yields (288.6%) for the various evaluated compounds, especially flavonoids. The potential of wine lees as a source of bioactive compounds is highlighted, along with the need for further research exploring alternative extraction technologies and the combination of methods. Additionally, the importance of "in vitro" and "in vivo" tests to assess the bioactive potential of lees, as well as the use of computational tools to optimize extraction and identify the molecules responsible for bioactive activity, is emphasized.

Estimating Global Wheat Yields at 4 km Resolution during 1982–2020 by a Spatiotemporal Transferable Method

Reliable and spatially explicit information on global crop yield has paramount implications for food security and agricultural sustainability. However, most previous yield estimates are either coarse-resolution in both space and time or are based on limited studied areas. Here, we developed a transferable approach to estimate 4 km global wheat yields and provide the related product from 1982 to 2020 (GlobalWheatYield4km). A spectra–phenology integration method was firstly proposed to identify spatial distributions of spring and winter wheat, followed by choosing the optimal yield prediction model at 4 km grid scale, with openly accessible data, including subnational-level census data covering ~11,000 political units. Finally, the optimal models were transferred at both spatial and temporal scales to obtain a consistent yield dataset product. The results showed that GlobalWheatYield4km captured 82% of yield variations with an RMSE of 619.8 kg/ha, indicating good temporal consistency (r and nRMSE ranging from 0.4 to 0.8 and 13.7% to 37.9%) with the observed yields across all subnational regions covering 40 years. In addition, our dataset generally had a higher accuracy (R2 = 0.71) as compared with the Spatial Production Allocation Model (SPAM) (R2 = 0.49). The method proposed for the global yield estimate would be applicable to other crops and other areas during other years, and our GlobalWheatYield4km dataset will play important roles in agro-ecosystem modeling and climate impact and adaptation assessment over larger spatial extents.