What is the moisture content of oil palm fresh fruit bunch?5 answersThe moisture content of oil palm fresh fruit bunches varies depending on the ripeness and maturity stage. Research has shown that the moisture content in oil palm fresh fruit bunches can range from 52.59% to 86.33%. Additionally, studies have focused on determining the moisture content in oil palm fruitlets using electrical impedance spectroscopy, with correlations to moisture content reaching around -0.84 at 100 kHz. Furthermore, an automated detection system utilizing a microstrip ring resonator has been proposed to determine the moisture content in oil palm fruit, enhancing the efficiency of maturity detection processes. These findings highlight the importance of accurately assessing the moisture content in oil palm fruit bunches for various applications in the palm oil industry.
How to calculate the yield?5 answersTo calculate the yield, various methods can be employed based on different contexts. One approach involves utilizing statistical timing data to consider path and stage delay correlation, leading to improved yield calculation accuracy. Another method involves a yield calculation system that integrates position, volume, and moisture measurements to determine the yield of crop material in a baler, excluding moisture content from the final yield calculation. Additionally, a yield distribution calculation device uses position and yield detection values to determine unpassed-through regions in a field, associating them with corresponding yield values to calculate the yield distribution according to position. Furthermore, a method involving binary decision graphs and mesh elements is utilized to calculate yield based on performance item values of sample points, providing a comprehensive yield assessment.
Generic tree biomass estimation formula for tropical agroforestry systems ?4 answersA generic tree biomass estimation formula for tropical agroforestry systems is recommended to encompass diameter at breast height (dbh), height, and wood specific gravity with sufficient calibration taking into account different forest types. The commonly used pantropical models should be evaluated for different ecosystems prior to their application at national or regional scales. Generic equations developed in Mexico and Brazil performed better in estimating tree biomass for multi-species data. Models considering gender, families, successional groups, climatic variables, and wood specific gravity should be adjusted, tested, and the resulting equations should be validated at both local and regional levels as well as on the scales of tropics with dry forest dominance. A simple height-diameter allometry is needed to accurately estimate biomass and carbon stock from plot inventories when biomass allometric models are not available for a given forest site.
How much of food waste is fruit waste?3 answersFruit waste constitutes a significant portion of food waste globally, with estimates ranging from 16% to more than 20%. In India, fruit processing industries generate fruit waste that comprises about 30-40% of fruit weight. Post-harvest losses of fruits and vegetables, including waste, account for 25-50% of the total produce. The rejection of produce based on visual appearance is a major cause of food wastage.
How can a neural network and genetic algorithm algorithm be used to determine the palm fruit ripeness?3 answersA neural network and genetic algorithm can be used to determine the ripeness of palm fruit. In one study, Raman spectroscopy was used to classify the ripeness of oil palm fruits based on molecular assignments extracted from Raman bands. An artificial neural network (ANN) was then deployed with seven significant Raman peak features to develop an automated ripeness classification system with 97.9% accuracy. Another study introduced a complete dataset of palm oil fruit videos and images with different categories based on maturity levels. This dataset was used to detect and classify the maturity level of oil palm fruit using computer vision techniques. Additionally, a deep learning algorithm, specifically a convolutional neural network, was applied to detect the maturity level of oil palm fruit based on digital images, achieving an accuracy of 92% for test data.
How do you calculate the volume of a standing tree?5 answersThe volume of a standing tree can be calculated using various methods. One approach is to use terrestrial LiDAR technology, which records detailed spatial information on the surface of the tree bole. This method, known as the "unwrapping method," combines cylinder fitting, voxelization, and Digital Elevation Models (DEMs) to provide accurate volume estimates of tree stems. Another method involves developing models based on variables such as diameter and height to estimate the volume of standing trees. Additionally, remote sensing techniques can be used to estimate forest stock volume by multiplying the number of trees detected remotely by the mean individual volume of the population. For standing dead trees, an automated volume estimation algorithm using terrestrial lidar, called "TreeVolX," has been developed, which provides accurate volume estimates for trees in dense forests. Another method involves using a digital camera to capture images of the standing tree and calculating the wood volume based on the number of black pixels in the image.