Sampling Density Research Articles

3D Printing Conductive Filament for Fuel Cell Bipolar Plates

Fuel cell bipolar plates are commonly manufactured from metals and graphite. Utilizing a polymer material, while still adhering to the standards set by the U.S. Department of Energy for bipolar plate electrical conductivity, could greatly reduce production costs and time. 3D printing bipolar plates could have benefits that include weight reductions as well as ease of testing different flowfield designs. However, very few 3D printing filaments are electrically conductive. In this work, samples were printed with Electrifi conductive filament, a copper-polyester composite material. Samples were printed at various conditions to determine optimal print settings for dimensional accuracy and electrical conductivity. Printing parameters such as nozzle temperature, flow rate, and infill pattern were varied to affect sample density and conductivity. Several combinations of print conditions led to conductivities nearing the US DOE technical target for bipolar plate conductivity. SEM imaging was performed to better understand the structure of the Electrifi filament, and an Energy-dispersive X-ray spectroscopy scan provided details on its elemental composition.

Estimating the compacted dry density of gravelly soil with oversized particles

The compacted dry density of gravelly soils containing particles that are too large for ordinary laboratory compaction tests is usually estimated by measuring the dry density of the base sample obtained by removing over-sized particles then correcting the measured value by the Walker-Holtz Equation (W&H Eq.). It is known that the W&H Eq. overestimates the dry density of gravelly soils and this trend becomes stronger as the mass ratio P of oversized particles increases. It seems that a satisfactory solution is not yet available. A comprehensive series of laboratory compaction tests was performed on a wide variety of gravelly soil samples with different particle sizes, grading uniformities and particle shapes. The followings were found. The ratio, X, of the maximum dry density predicted by the W&H Eq. to the measured value increases linearly from unity as P increases from zero up to approximately 0.75. The slope of the X-P relation, (X − 1.0) / P, increases as the coefficient of uniformity or the fines content of the base sample increases and as the gravel particles become more angular in a synergistic manner. It is proposed to estimate the maximum dry density of compacted gravelly soil containing oversized particles by dividing the value predicted from the W&H Eq. by X obtained from the substitution of P into the relevant X-P relation. Proposed based on the above is an effective and efficient compaction method for gravelly soils containing oversized particles that controls the degree of saturation and the compaction energy.

Grading scalping and sample size effects on critical shear strength of mine waste rock through laboratory and in-situ testing

Geotechnical stability analyses of mine waste rock (WR) piles require the critical friction angle (ϕcr) of the coarse blasted rock. However, due to the presence of oversized rock clasts, shear strength can only be characterized on small samples prepared using grading scaling techniques, such as scalping. Thus, considering a testing device able to handle samples of characteristic size D, the material should be scaled down to a maximum particle size dmax given by the minimum sample aspect ratio α = D/dmax. However, a practical concern about how far the size scale can be reduced while keeping representative results remains a matter of debate in the geotechnical community. International standards do not agree on the minimum recommended α, and its effects on the mechanical behavior remain poorly understood. This paper aims to investigate the grading effects and sample size effects on ϕcr of WR materials using the scalping technique, to provide insights on the minimum recommended α. Triaxial tests were conducted on loose and dense samples of diameters D = 150 and 300 mm. Samples were scalped from field material having dmax = 75 mm, to allow a range of α from 4 to 30. Additionally, one of the world largest in-situ direct shear boxes (120 × 120 × 38 cm3) was developed to test the same WR material. The results show that scalping is an appropriate technique to assess the critical shear strength of WR. The minimum α for ϕcr assessment in triaxial testing is not sensitive to grading nor sample size, but it is affected by sample density. The aspect ratio was found to be α ≥ 12 and α ≥ 16 for loose and dense samples, respectively. This finding advocates that α values recommended by worldwide standards, such as ASTM D7181-20, might be too low and should be revisited after comprehensive testing.

A Circle Center Location Algorithm Based on Sample Density and Adaptive Thresholding

How to acquire the exact center of a circular sample is an essential task in object recognition. Present algorithms suffer from the high time consumption and low precision. To tackle these issues, we propose a novel circle center location algorithm based on sample density and adaptive thresholding. After obtaining circular contours through image pre-processing, these contours were segmented using a grid method to obtain the required coordinates. Based on the principle of three points forming a circle, a data set containing a large number of samples with circle center coordinates was constructed. It was highly probable that these circle center samples would fall within the near neighborhood of the actual circle center coordinates. Subsequently, an adaptive bandwidth fast Gaussian kernel was introduced to address the issue of sample point weighting. The mean shift clustering algorithm was employed to compute the optimal solution for the density of candidate circle center sample data. The final optimal center location was obtained by an iteration algorithm. Experimental results demonstrate that in the presence of interference, the average positioning error of this circle center localization algorithm is 0.051 pixels. Its localization accuracy is 64.1% higher than the Hough transform and 86.4% higher than the circle fitting algorithm.

Promoting effect of interfacial hole accumulation on photoelectrochemical water oxidation in BiVO4 and Mo-doped BiVO4

Hole transfer at the semiconductor-electrolyte interface is a key elementary process in (photo)electrochemical (PEC) water oxidation. However, up to now, a detailed understanding of the hole transfer and the influence of surface hole density on PEC water oxidation kinetics is lacking. In this work, we propose a model for the first time in which the surface accumulated hole density in BiVO4 and Mo-doped BiVO4 samples during water oxidation can be acquired via employing illumination-dependent Mott-Schottky measurements. Based on this model, some results are demonstrated as below: (1) Although the surface hole density increases when increasing light intensity and applied potential, the hole transfer rate remains linearly proportional to surface hole density on a log-log scale. (2) Both water oxidation on BiVO4 and Mo-doped BiVO4 follow first-order reaction kinetics at low surface hole densities, which is in good agreement with literature. (3) We find that water oxidation active sites in both BiVO4 and Mo-doped BiVO4 are very likely to be Bi5+, which are produced by photoexcited or/and electro-induced surface holes, rather than VOx species or Mo6+ due to their insufficient redox potential for water oxidation. (4) Introduction of Mo doping brings about higher OER activity of BiVO4, as it suppresses the recombination rate of surface holes and increases formation of Bi5+. This surface hole model offers a general approach for the quantification of surface hole density in the field of semiconductor photoelectrocatalysis.

The impact of pressure rate on the physical, structural and gamma-ray shielding capabilities of novel light-weight clay bricks

The present study focuses on investigating the gamma-ray protection features of clay bricks for potential use in radiation shielding fields. The study examined the physical and structural features that affect the performance of these stones in shielding γ-rays. The density (ρ, g/cm3) of the clay bricks samples was measured utilizing the MH-300A density meter. Additionally, the mineral structure within the annealed pressed clay samples was identification the XRD spectrometry. Moreover, the morphology and elemental chemical composition for the annealed bricks were examined using a Thermo Scientific Prisma E, USA field emission Scanning Electron Microscope (SEM) in conjunction with Energy Dispersive X-ray Spectroscopy. Besides, the shielding features of the clay bricks were analyzed using the experimentally measurements (by NaI (Tl) scintillation detector), XCOM software, and Monte Carlo Simulation over the γ-ray energy interval of 0.033–1.332 MeV. The findings of the study indicate that an increase in the pressure rate within the clay bricks samples leads to the rise in their density (from 1.62 to 1.87 g/cm3). This increase in density is accompanied by a decline in both porosity (Φ, %) (from 34.75 to 26.21 %) and water absorption (K, %) (from 26.21 to 14.74 %) factors. Furthermore, the increase in pressure rate from 7.61 to 114.22 MPa also results in an increase in the linear attenuation coefficient (μ, cm−1) of the clay bricks under study. This is achieved by increasing the μ values from 0.39 to 0.43 cm−1, from 0.13 to 0.15 cm−1, and from 0.09 to 0.10 cm−1, at 0.081, 0.511 and 1.173 MeV, respectively. The synthetic bricks offer a lead-free and efficient option for protection, making them ideal for use in nuclear facility start-ups or in areas with radiation exposure.

Influence of gamma radiation on the composition and physicochemical characteristics of olefins: post-radiation effects

The effect of gamma radiation on olefins was studied under static conditions at an absorbed dose of 65 kGy and at a dose rate ofP= 0.076 Gy/s. The effect of radiation on the physicochemical characteristics and structural and group composition of the resulting olefins has been established. Post-irradiation effects were studied immediately after irradiation and during 1, 2, 4, and 7 months later. When fuels are irradiated, polymerization of unsaturated hydrocarbons occurs. After cessation of irradiation, the postpolymerization process occurs The chemical instability of olefins in fuels leads to the formation of carbon deposits in the engine system, tanks, and valves. IR spectra, iodine values, density, and kinematic viscosity of irradiated samples were measured.

PSLBII-23 Effects of alternative production systems on growth and circulating blood profiles in Berkshire grower pigs

Abstract In this study, we compared the growth performance and circulating blood profiles of Berkshire grower pigs maintained in two different alternative swine production systems, the dry-lot production system, and the hoop structure production system. This study was conducted during a 75-d period spanning from May to July at the North Carolina Agricultural and Technical State University Swine Facility in Greensboro, N.C. Protein expression profiles associated with growth (FGF-19, PDGF-BB, IGF-1), feed intake (CCK), stress (cortisol) and the ability to handle oxidative stress (T-AOC) were analyzed in blood plasma obtained from 24 Berkshire nursery/grower pigs. Berkshire pigs (n = 12) were managed in a 12.19 m x 18.28 m hoop structure with the end walls removed for ventilation and a straw deep bedding system. Twelve additional Berkshire nursery/grower pigs were managed in a 0.08-ha dry-lot. These animals were provided with a canopy for shade and a wallowing area for evaporative cooling. All animals were provided with ad libitum ration and water. Individual body weights (BW) and blood samples were collected at 25-d intervals throughout the 75-d trial, culminating in three different time points. Plasma was isolated from the blood samples and used for ELISA and colorimetric assays. The BioTek 800 TS absorbance reader and Gen5 Microplate Reader and Imager software (Agilent Technologies, Inc., Santa Clara, CA) were used to obtain and calculate the optical densities of the plasma samples, respectively. The data were analyzed using the two-way ANOVA feature of JMP 17.2.0 software (SAS Institute, Inc., Cary, NC) with production system and growth period considered fixed variables, while either growth rate or protein concentration were considered as the response variable. There were four significant treatment effects observed (P < 0.05). Significantly greater concentrations of IGF-1, CCK, and T-AOC were detected in the plasma collected from Berkshire pigs managed in the dry-lot. Whereas those managed in the hoop structure production system had heavier BW. The results show that exposing pigs to higher temperatures can reduce feed intake and growth rates. However, this same stress elicits the release of hormones that promote growth, while enhancing the total antioxidant capacity in these animals. The results support the adoption of the hoop structure production system over the dry-lot production system when managing swine in regions that experience higher temperatures.

Empirical Bayesian Kriging, a Robust Method for Spatial Data Interpolation of a Large Groundwater Quality Dataset from the Western Netherlands

No single spatial interpolation method reigns supreme for modelling the precise spatial distribution of groundwater quality data. This study addresses this challenge by evaluating and comparing several commonly used geostatistical methods: Local Polynomial Interpolation (LPI), Ordinary Kriging (OK), Simple Kriging (SK), Universal Kriging (UK), and Empirical Bayesian Kriging (EBK). We applied these methods to a vast dataset of 3033 groundwater records encompassing a substantial area (11,100 km2) in the coastal lowlands of the western Netherlands. To our knowledge, no prior research has investigated these interpolation methods in this specific hydrogeological setting, exhibiting a range of groundwater qualities, from fresh to saline, often anoxic, with high natural concentrations of PO4 and NH4. The prediction performance of the interpolation methods was assessed through statistical indicators such as root means square error. The findings indicated that EBK outperforms the other geostatistical methods in forecasting groundwater quality for the five variables considered: Cl, SO4, Fe, PO4, and NH4. In contrast, SK performed worst for the species except for SO4. We recommend not using SK to interpolate groundwater quality species unless the data exhibit low spatial variation, high sample density, or evenly distributed sampling.

The utilization of pulverized waste tire rubber in a soil–cement composite for sustainable compressed earth brick production

This study examined the suitability of blending waste tires with cement in indigenous soil for producing compressed earth bricks (CEB) to achieve a sustainable environment. CEB was produced with clay soil and a combination of cement at 5 and 10% levels with varying dosages of pulverized waste tire at 0, 2.5, 5, 7.5, and 10% mixture. Classification tests were conducted to determine engineering properties such as the particle size distribution, Atterberg limit, specific gravity, optimum moisture and unit weight of the soil. The physical properties of the pulverized tire were evaluated. Moreover, density, water absorption, and compressive strength were determined for hardened CEB samples produced from mixtures of soil and various proportions of blended cement and pulverized waste tire materials. The classification results showed that the soil was silty clay of low plasticity. The density of the CEB samples was observed to increase slightly with the addition of blended cement-tire residue. Furthermore, a considerable improvement in the compressive strength development of the CEB was observed; however, compared with those of the control, the peak compressive strength of the CEB samples was greater when the soil was stabilized with 7.5% pulverized waste tire material and 10% cement. A decrease in the water absorption capacity of CEB was observed with an increase in the amount of pulverized waste tire and cement in the soil mixture. The response models corroborate the experimental findings indicating that amount of waste tire rubber residue and cement had significant effects on the CEB performance. This study ensure the beneficial recycling of waste tires blended with cement in soil for making medium-strength CEB to achieve sustainable, resilient masonry construction applications.Graphical

Evaluation of the Amount of Endophytic Bacteria Associated with Roots of Brachiaria Humidicola Cv. Humidicola (Rendle) Schweick in Relation to Ph Values, Organic Matter and Phosphorus Contents of Cattle Farm Soil

The objective of this study was to isolate endophytic bacteria from roots of Brachiaria humidicola cv. humidicola (Rendle) Schweick and to relate their presence to pH, organic matter and phosphorus contents of the soil of cattle farms located in the municipality of San Benito Abad. Soil sampling was carried out with roots of B. humicola for the isolation and counting of the population density of endophytic bacteria and soil samples were also collected for the determination of pH, organic matter and phosphorus parameters. The results found indicate that there is an amount of endophytic bacteria in roots of B. humidicola when the soil contains optimum pH values of (6.1 ± 6.98); low to moderate phosphorus content (10.8 ± 16.28 mg/kg) and low to moderate organic matter content (1.7 ± 2.31%). The presence of endophytic bacteria was observed in a range of 3.0 ± 8.0 X 106 CFU/g of roots. There is a worldwide need to establish a relationship between endophytic bacteria and soil physical-chemical quality indicator parameters to predict a change in functional diversity under physical, chemical and biological conditions of the soil ecosystem.

Fuzzy support vector machine using local outlier factor and intuitionistic fuzzy sets for imbalanced datasets

Traditional classifiers are commonly used for solving class balance problems. However, many datasets exhibit class imbalance along with outliers and noise, which affect the classification accuracy, this paper proposes a fuzzy support vector machine algorithm based on local outlier factor and intuitionistic fuzzy sets. First, to highlight the importance of the minority class, the membership degree is set to the maximum value. Meanwhile, local outlier factor is calculated to measure the abnormality and further obtain the membership degree in the majority class. Then, a kernel density estimation method is designed to estimate the sample density accurately. Furthermore, based on the density distribution, intuitionistic fuzzy sets are used to assign membership and non-membership degrees to samples, effectively distinguishing between noise and outliers. Finally, different penalty coefficients for two classes are built to offset the impact of class imbalance on classification accuracy. Experimental results show the advantages of the proposed algorithm.

Maximum Local Density-Driven Non-overlapping Radial Basis Function Support Kernel Neural Network

The learning and optimization of kernels in the radial basis function neural network (RBFNN) are crucial. However, in existing methods, there are issues of overfitting when learning kernel parameters. The learned kernels are also sensitive to outliers. This paper proposes a general kernel learning strategy for RBFNN called non-overlapping maximum local density support kernel learning (MLD-SKL), which contains two modules, the non-overlapping maximum local density (MLD) kernel learning module and support kernel learning (SKL) module. In the MLD kernel learning stage, the candidate set of kernels is incrementally determined based on the local density of samples. Meanwhile, it is required that the coverage ranges of kernels from different classes do not overlap with each other. This module is effective in reducing the impact of outliers. In the SKL stage, kernel importance indicator is defined to measure the importance of kernels. The learned support kernels are utilized to construct a maximum local density-driven non-overlapping radial basis function support kernel neural network (MLD-RBFSKNN). The RBFNN constructed through MLD-SKL exhibits a more compact structure. The experiments demonstrate that the proposed MLD-RBFSKNN improves accuracy in recognition task. Furthermore, while achieving superior recognition performance, the final constructed network also has the minimum number of kernels.

Uranium Mine Proposed Experimental Design for Natural Background Gross Gamma Exposure Rates, Post Remediation Final Status Survey Sampling Density, and Radiological Water Quality Modeling for a Worst-case Catastrophic Failure, Coles Hill, Virginia.

Completely randomized experimental design statistical modeling techniques were employed to analyze exposure rate measurements for evaluating hypothetical natural background post uranium mill operations at Coles Hill, Virginia uranium milling processes. The proposed Coles Hill Uranium Mine is situated upstream of the Banister River. This River is nearly homogenous throughout the reach length used in analysis and feeds into the mouth of Kerr Reservoir, Lake Gaston, which serves as the main drinking water source for cities in the Hampton Roads area including Norfolk, Virginia Beach, and Chesapeake. A critical scan value (=DCGLscan) was developed to flag anomalies of surface contamination during simulated post remediation final status surveys. The natural background was critical for meeting the Multi-Agency Radiation Survey and Site Investigation Manual guidance for post remediation final status surveys. The overarching null hypothesis suggested that the selected mean natural background is equal to the survey unit's mean natural background. Using SAS Procedures Shapiro-Wilk Test, ANOVA, and CR, it was decided the exposure rate data was normal, had no extreme outliers, and no collinearity between the number of samples (=treatment) and the areas (=block). Using the q-hyper (hypergeometric) distribution, the soil sampling density was decided for a final status survey unit. The most likely worst-case catastrophic failure analysis, 500-year event, such as the1969 Hurricane Camille of 69 centimeters of rain in Nelson County, Virginia was included in the model. The model showed impact was minimal at most to the Banister River's drinking water and likely less than the Virginia's Drinking Water Standards for gross alpha, 226Ra and 228Ra, and total uranium.

Effect of sintering temperature and holding time on structure and properties of Li1.5Ga0.5Ti1.5(PO4)3 electrolyte with fast ionic conductivity

Li1.5Ga0.5Ti1.5(PO4)3 (LGTP) is recognized as a promising solid electrolyte material for lithium ions. In this work, LGTP solid electrolyte materials were prepared under different process conditions to explore the effects of sintering temperature and holding time on relative density, phase composition, microstructure, bulk conductivity, and total conductivity. In the impedance test under frequency of 1−106 Hz, the bulk conductivity of the samples increased with increasing sintering temperature, and the total conductivity first increased and then decreased. SEM results showed that the average grain size in the ceramics was controlled by the sintering temperature, which increased from (0.54±0.01) μm to (1.21±0.01) μm when the temperature changed from 750 to 950 °C. The relative density of the ceramics increased and then decreased with increasing temperature as the porosity increased. The holding time had little effect on the grain size growth or sample density, but an extended holding time resulted in crack generation that served to reduce the conductivity of the solid electrolyte.

Characterization of wood plastic composites made with recycled waste tire rubber

Abstract Green materials are currently demanded for construction as well as other products since the 26th UN Climate Change Conference of the Parties (COP26) in 2021. Using renewable and sustainable resources to innovate new materials such as composites is encouraged. This study aimed to investigate the physical and mechanical characteristics of wood plastic composites (WPCs) when adding waste tire rubber as filler for 10% or 20% by weight. The results showed that the density of the WPC samples (50 wt% wood − 50 wt% high density polyethylene) increased with the addition of the waste tire rubber (WTR) while the dimensional stability of samples was reduced. The mechanical properties of the WPC samples were determined, including flexural strength, flexural modulus, elongation at break, tensile strength, tensile modulus, and impact strength. The WTR as filler in the WPC tended to decrease the tensile strength and flexural strength whereas it improved the impact strength of materials. The results indicated that the WTR as recycled material in WPC affected the physical and mechanical properties of the WPCs. Although the use of the WTR in the production of the WPC adversely affects the mechanical properties, the use of 10 wt% WTR was acceptable. The results of the study showed that the addition of the WTR to the WPC production process can be useful for its recycling and for reducing the cost of the WPC.

Synthetic oversampling with Mahalanobis distance and local information for highly imbalanced class-overlapped data

Minority oversampling is currently one of the most popular and effective methods for handling imbalanced data. However, oversampling that relies on the observations of the minority class to generate new samples is not applicable in the scenario of imbalanced data with extremely scarce minority samples, because the strongly underrepresented minority class does not contain enough information to support the oversampling process. Since some recent studies have exhibited the effectiveness of using majority information to bootstrap oversampling, the neglect of class overlap in the sampling process would increase the overlapping degree and complicate the decision boundary. To this end, this paper proposes a Mahalanobis distance and Local information based OverSampling (MLOS) for highly imbalanced class-overlapped data. MLOS first employs the majority density to guide the sample synthesis, with Mahalanobis distance to extract the majority probability contour. Then for each minority seed sample, to avoid the generation of overlapping samples, MLOS constrain the synthetic process by finding the auxiliary sample (in its 5 nearest neighbors) with similar probability density value to the seed. Finally, MLOS uses a pair-wise data cleaning process to improve the visibility of the decision boundary according to the probability density of synthetic samples. Comparative experiments conducted on 16 highly imbalanced class-overlapped datasets, using 17 different methods, demonstrates the superiority of our proposed method in terms of three popular evaluation metrics AUC, G-mean and Recall for imbalance classification. The source code of MLOS is available at https://github.com/ytyancp/MLOS.

Subspace projection attention network: Deep weak signal recovery from complicated downhole distributed acoustic sensing data

Distributed acoustic sensing (DAS) is a new, rapidly developing acquisition technology. It has many advantages, such as full well coverage, high sampling density, and strong tolerance compared with conventional geophones in harsh environments. However, DAS data contain various new types of noise with different characteristics, which brings great difficulties to weak signal recovery. It is also not conducive to subsequent inversion, imaging, and interpretation. Several traditional methods and their developments can only remove particular types of DAS noise with serious energy loss. At the same time, the denoising performance is strongly dependent on the threshold function or manual setting parameters. In recent years, deep learning has attracted much attention in DAS data processing. However, convolutional neural networks can only capture local information. The commonly used channel attention assigns weights to each channel to reflect the importance and neglects the features within the channels. The popular self-attention mechanism (SAM) can efficiently obtain the dependencies between different locations or different patches that are a long distance from the input. Thus, a novel subspace projection attention network (SPANet) is designed from a new projection perspective. In the novel network, some feature basis vectors are generated to guide the decoupled projection of the noise components from the signal components. Low-level surface features are projected under the guidance of high-level abstract features through SAM before feature fusion. The projection operation helps to find the optimal subspace that preserves the fine structure of the input as much as possible, better capturing the potential relevance in DAS data. Finally, experimental results of synthetic and field data illustrate that SPANet recovers the effective reflection signals well, whether in a shallow layer with strong noise or a deep layer with weak energy. Its superior performance compared with some traditional and network methods is fully verified and analyzed.

Experimental and theoretical analysis of strain hardening behavior of friction-stir-welded Al-4.2Zn-3.1Mg aluminium alloy

The strain hardening behavior of friction stir welded AA7039 (Al-4.2Zn-3.1 Mg) alloy was explored in terms of dislocation density, crystallite size, hardening capacity, hardening exponent, and strain hardening rate. Strain hardening behavior was analyzed for base metal and friction stir welded specimens. Four different models were used to calculate the dislocation density viz., Scherrer model, uniform strain model (USM), uniform stress distribution model (USDM), and uniform strain energy distribution model (USDEM). Maximum dislocation density was obtained in base metal for all models (maximum for USM, 3.9 × 10 15 m − 2 ) with a minimum crystallite size of 15.81 nm. The low dislocation density in FSW samples is due to the higher heat input in the FSW process. Strain hardening stages were shown by Kocks–Mecking type plots. Lower strain hardening capacity was obtained for BM, i.e. 0.427 as compared to FSW samples, due to the higher dislocation density of BM. It was determined that there is an inverse relationship between the strain hardening capacity and the strain hardening exponent. Strain hardening rate was higher for BM than FSW specimens, and similar results were obtained from mathematical relations that indicate the adequacy of the results. The ultimate tensile strength was 2.5% higher than the BM at a rotational speed of 1325 rpm, 35 mm/min of welding speed and 1.65° tilt angle. The maximum strength friction stir-welded specimen showed a more ductile fracture surface than the BM because the grain boundary phase disappeared or broke up in the thermomechanical affected zone.

Sampling Method to Estimate Fresh Fruit Bunch Production in Oil Palm Using Geostatistical Techniques

In oil palm cultivation, harvesting is a task that demands the most attention, resources, and accuracy. The logistics of harvesting activities, from bunch cutting through delivery to processing, are organized as a function of yield per hectare, and this planning depends on production samples collected from plantations to estimate the number of fresh fruit bunches that will be harvested per crop management unit. Conventionally, production is estimated through sampling grids, most commonly every five rows and every five palms (5 × 5), 7 × 7, or 10 × 10. Sampling density, however, does not typically result from a statistically rigorous method. Therefore, the objective of the present study was to define, using geostatistics, adequate sampling grids for estimating production. Specifically, seven lots in different Colombian oil palm-growing regions with planting ages between 5 and 9 years were analyzed, and the number of reproductive structures of all oil palms was recorded. From the semivariogram of each lot, different models were proposed, fitted, and cross-validated. For each sampling grid, all possible samples were simulated in the respective lots to determine the degree of accuracy in estimating oil palm production. The optimal sampling grids differed between lots, ranging from 3 × 3 to 15 × 15.