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Wang, Zhenglin, Anand Koirala, Kerry Walsh, Nicholas Anderson, and Brijesh Verma. "In Field Fruit Sizing Using A Smart Phone Application." Sensors 18, no. 10 (October 5, 2018): 3331. http://dx.doi.org/10.3390/s18103331.
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In field (on tree) fruit sizing has value in assessing crop health and for yield estimation. As the mobile phone is a sensor and communication rich device carried by almost all farm staff, an Android application (“FruitSize”) was developed for measurement of fruit size in field using the phone camera, with a typical assessment rate of 240 fruit per hour achieved. The application was based on imaging of fruit against a backboard with a scale using a mobile phone, with operational limits set on camera to object plane angle and camera to object distance. Image processing and object segmentation techniques available in the OpenCV library were used to segment the fruit from background in images to obtain fruit sizes. Phone camera parameters were accessed to allow calculation of fruit size, with camera to fruit perimeter distance obtained from fruit allometric relationships between fruit thickness and width. Phone geolocation data was also accessed, allowing for mapping fruits of data. Under controlled lighting, RMSEs of 3.4, 3.8, 2.4, and 2.0 mm were achieved in estimation of avocado, mandarin, navel orange, and apple fruit diameter, respectively. For mango fruit, RMSEs of 5.3 and 3.7 mm were achieved on length and width, benchmarked to manual caliper measurements, under controlled lighting, and RMSEs of 5.5 and 4.6 mm were obtained in-field under ambient lighting.
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Neupane, Chiranjivi, Maisa Pereira, Anand Koirala, and Kerry B. Walsh. "Fruit Sizing in Orchard: A Review from Caliper to Machine Vision with Deep Learning." Sensors 23, no. 8 (April 10, 2023): 3868. http://dx.doi.org/10.3390/s23083868.
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Forward estimates of harvest load require information on fruit size as well as number. The task of sizing fruit and vegetables has been automated in the packhouse, progressing from mechanical methods to machine vision over the last three decades. This shift is now occurring for size assessment of fruit on trees, i.e., in the orchard. This review focuses on: (i) allometric relationships between fruit weight and lineal dimensions; (ii) measurement of fruit lineal dimensions with traditional tools; (iii) measurement of fruit lineal dimensions with machine vision, with attention to the issues of depth measurement and recognition of occluded fruit; (iv) sampling strategies; and (v) forward prediction of fruit size (at harvest). Commercially available capability for in-orchard fruit sizing is summarized, and further developments of in-orchard fruit sizing by machine vision are anticipated.
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Buchner, Richard, Seeley Mudd, Bruce Carroll, and Mark Gilles. "Harvest Field Sizing as a Technique to Remove Undersize French Prunes." HortScience 33, no. 3 (June 1998): 452a—452. http://dx.doi.org/10.21273/hortsci.33.3.452a.
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Overall profitability is a major goal in successful prune production and a major component in any prune management system. Large prune crops in 1996 and 1997 have stimulated considerable interest in undersize fruit. Undersize prunes currently have marginal value and may represent a net loss because of costs to haul, dry, and to market order payments on low value prunes. One technique to control delivery size is to field size at harvest. Field sizing involves installing size-sorting devices on harvesters, which allow small prunes to fall out while valuable fruit is collected. Field sizing is considered a “risky” strategy because of the potential to remove prunes with economic value. During the 1997 harvest, 21 infield harvest sizing evaluations were made in prune orchards throughout Tehama county. The first evaluation occurred on 12 Aug. 1997, at the start of prune harvest. The final evaluation was done on 5 Sept. 1997, at the tail end of harvest. The objective was to sample throughout the harvest period to test field sizing under various sugar, size, and fruit pressure scenarios. The test machine was 1-inch bar sizer. Of the 21 sample dates, undersize fruit was clearly not marketable in 20 of the 21 samples. Discarded fruit averaged 133 dry count per pound. Only one sample out of 21 may have had market value at 86 dry count per pound. Although small in size, these prunes had very high sugar content contributing to their dry weight. In this evaluation, a 1-inch bar sizer did a good job of separating fruit with and without market value under the 1997 price schedule. As harvest date becomes later and soluble solids increase, the chances of sorting out marketable prunes also increases.
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Koirala, A., Z. Wang, K. B. Walsh, and C. McCarthy. "Fruit sizing in-field using a mobile app." Acta Horticulturae, no. 1244 (July 2019): 129–36. http://dx.doi.org/10.17660/actahortic.2019.1244.20.
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Amaral, Marcelo H., and Kerry B. Walsh. "In-Orchard Sizing of Mango Fruit: 2. Forward Estimation of Size at Harvest." Horticulturae 9, no. 1 (January 3, 2023): 54. http://dx.doi.org/10.3390/horticulturae9010054.
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Forecast of tree fruit yield requires prediction of harvest time fruit size as well as fruit number. Mango (Mangifera indica L.) fruit mass can be estimated from correlation to measurements of fruit length (L), width (W) and thickness (T). On-tree measurements of individually tagged fruit were undertaken using callipers at weekly intervals until the fruit were past commercial maturity, as judged using growing degree days (GDD), for mango cultivars ‘Honey Gold’, ‘Calypso’ and ‘Keitt’ at four locations in Australia and Brazil during the 2020/21 and 21/22 production seasons. Across all cultivars, the linear correlation of fruit mass to LWT was characterized by a R2 of 0.99, RMSE of 29.9 g and slope of 0.5472 g/cm3, while the linear correlation of fruit mass to )2, mimicking what can be measured by machine vision of fruit on tree, was characterized by a R2 of 0.97, RMSE of 25.0 g and slope of 0.5439 g/cm3. A procedure was established for the prediction of fruit size at harvest based on measurements made five and four or four and three weeks prior to harvest (approx. 514 and 422 GDD, before harvest, respectively). Linear regression models on weekly increase in fruit mass estimated from lineal measurements were characterized by an R2 > 0.88 for all populations, with an average slope (rate of increase) of 19.6 ± 7.1 g/week, depending on cultivar, season and site. The mean absolute percentage error for predicted mass compared to harvested fruit weight for estimates based on measurements of the earlier and later intervals was 16.3 ± 1.3% and 4.5 ± 2.4%, respectively. Measurement at the later interval allowed better accuracy on prediction of fruit tray size distribution. A recommendation was made for forecast of fruit mass at harvest based on in-field measurements at approximately 400 to 450 GDD units before harvest GDD and one week later.
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Peterson, D. L. "Harvest Mechanization Progress and Prospects for Fresh Market Quality Deciduous Tree Fruits." HortTechnology 15, no. 1 (January 2005): 72–75. http://dx.doi.org/10.21273/horttech.15.1.0072.
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Deciduous tree fruit crops such as apple (Malus domestica), peach (Prunus persica), and sweet cherry (Prunus avium) are not mechanically harvested for the fresh market. Attempts to mechanically harvest these fruits by mass removal techniques have not been successful due to excessive fruit damage caused during detachment, fall through the canopy, and collection. Robotic harvesters have not been commercially accepted due to insufficient fruit recovery. A U.S. Department of Agriculture-Agricultural Research Service (USDA-ARS) harvesting concept shows promise for harvesting both fresh market quality apples and sweet cherries. Successful mechanical harvesting of fresh market quality deciduous tree fruit will only occur when plant characteristics and machine designs are integrated into a compatible system. Cultivar characteristics that would facilitate machine harvesting are uniform fruit maturity at harvest, firm fruit that are resistant to mechanical damage, and compact growth habit that produces fruit in narrow canopies and on short/stiff limbs. Engineers must develop new detachment principles that minimize the energy input to effect fruit detachment, and develop durable energy-absorbing catching surfaces/conveyors to eliminate damage during collection of the fruit. As technology advances, sorting and sizing systems might be developed that can be operating on the harvester to eliminate culls in the field and deliver only fresh market quality fruit to the packers.
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Russo, J. M., and E. J. Holcomb. "Gauges for Discrete Plant Measurement." HortScience 21, no. 1 (February 1986): 149. http://dx.doi.org/10.21273/hortsci.21.1.149.
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Abstract Simple, specialized instruments, such as tree calipers, tree diameter tapes, and fruit sizing templates, have been used to quantify dimensions of specific plant parts and provide a standard set of plant measurements. Forshey (3) used a band-type fruit caliper to measure the diameter of McIntosh apples to predict their size at time of harvest.
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Jarimopas, B., S. Toomsaengtong, and C. Inprasit. "Design and testing of a mangosteen fruit sizing machine." Journal of Food Engineering 79, no. 3 (April 2007): 745–51. http://dx.doi.org/10.1016/j.jfoodeng.2006.01.083.
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Hong, Suk-Ju, Sungjay Kim, ChangHyup Lee, Seongmin Park, Kyoung-Chul Kim, Ahyeong Lee, and Ghiseok Kim. "On-Plant Size and Weight Estimation of Tomato Fruits Using Deep Neural Networks and RGB-D Imaging." Journal of the ASABE 67, no. 2 (2024): 439–50. http://dx.doi.org/10.13031/ja.15746.
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Highlights Deep learning-based instance segmentation models were applied and evaluated for tomato fruit detection. Mask R-CNN with vision transformer backbone showed the highest accuracy for tomato instance detection. Size and weight estimation indexes were calculated using tomato region depth data from instance segmentation models. Area-based index has higher accuracy for weight estimation than indexes based on weight and height information. Abstract. The size and weight of fruits are crucial factors in yield prediction and determining harvesting time. Machine vision, including fruit detection, is a key technology in the automated monitoring and harvesting of fruits. In particular, deep learning-based fruit-detection methods have been actively applied. Estimation of fruit size after fruit detection requires depth information, which can be acquired using depth imaging. RGB-D cameras include color and depth information required for fruit detection and size estimation. In this study, the RGB-D imaging technique was used to estimate the size and weight of tomatoes. Furthermore, deep learning-based instance segmentation models, including Mask R-CNN, YOLACT, and RTMDet for tomato fruit detection, were trained and evaluated. The proposed method estimated the fruit width with a root mean square error (RMSE) of 4 mm, a mean absolute percentage error (MAPE) of 4.28%, and a fruit height with an RMSE of 5.12 mm and a MAPE of 6.42%. Furthermore, the weight-prediction model based on the area index estimated the tomato fruit weight with an RMSE of 19.69 g and MAPE of 9.44%. Thus, the method can be used for accurate size and weight estimation and can be applied in growth monitoring and automated tomatoes harvesting. Keywords: Deep learning, Fruit sizing, Instance segmentation, RGB-D, Tomato.
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Miranda, Juan C., Jordi Gené-Mola, Manuela Zude-Sasse, Nikos Tsoulias, Alexandre Escolà, Jaume Arnó, Joan R. Rosell-Polo, Ricardo Sanz-Cortiella, José A. Martínez-Casasnovas, and Eduard Gregorio. "Fruit sizing using AI: A review of methods and challenges." Postharvest Biology and Technology 206 (December 2023): 112587. http://dx.doi.org/10.1016/j.postharvbio.2023.112587.
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Farzand Ahmadi, Vahid, Peyman Ziyaee, Pourya Bazyar, and Eugenio Cavallo. "Development and Testing of a Low-Cost Belt-and-Roller Machine for Spheroid Fruit Sorting." AgriEngineering 2, no. 4 (December 4, 2020): 596–606. http://dx.doi.org/10.3390/agriengineering2040040.
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Sorting is one of the most critical factors in the marketing development of fruit and vegetable and should be performed without any damage to the product. This article reports results of the development and testing of a prototype of a low-cost mechanical spherical fruit sorter based on a belt-and-roller device built at the State University of Tabriz, Iran. The efficiency and damage effect of the prototype of the machine was tested at different sorting rates on apples (Red Delicious and Golden Delicious) and oranges. Performance tests indicated that the speed of the feeding belt and transporting belt as well as the spherical coefficient significantly affect the machine’s sizing performance and damages. The results of the test showed a 95.28% and 92.48% accuracy in sorting for Red Delicious and Golden Delicious, respectively, and 94.28% for orange. Furthermore, the machine sorts fruits without any significant damage.
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Wright, Glenn C. "Girdling Lemons to Improve Fruit Size and Set in Southern Arizona." HortScience 33, no. 3 (June 1998): 499a—499. http://dx.doi.org/10.21273/hortsci.33.3.499a.
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Arizona lemon producers are often concerned with poor flowering, fruit set and fruit sizing, especially following excessively warm winter or spring weather. `Limoneira 8A Lisbon' (Citrus limon Burm.) lemons were girdled over a 3-year period to determine if girdling would improve yield or fruit size. Eight trees were girdled each month, from November through August, using a double spiral girdle and a 4.8-mm wide girdling knife. Fruit size measurements were taken throughout the growing season. Trees were harvested individually, and yield; fruit packout and fruit quality measurements were collected. For the 1995/96 harvest, trees girdled in March and May had greater early size and greater yields. Fruit quality was improved as well. For 1996/97 harvest year, trees girdled the previous November and December had significantly greater yield and fruit size. For trees harvested in 1997/98, no treatment was significantly better than the non-girdled trees. The effects of girdling on the orchard profitability will also be discussed.
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Krueger, William H., and Ricardo Fernandez Escobar. "THE RELATIONSHIP BETWEEN LIGHT INTENSITY, LEAF SPECIFIC WEIGHT, LEAF NITROGEN LEVELS, AND FRUIT SIZE AT HARVEST FOR MANZANILLO OLIVE." HortScience 27, no. 6 (June 1992): 604b—604. http://dx.doi.org/10.21273/hortsci.27.6.604b.
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The relationship between changes in Photosynthetically Active Radiation (PAR), specific leaf weight, nitrogen per leaf area and fruit size at harvest were investigated within the canopy of Manzanillo olive. Increasing PAR in the tree canopy related linearly to increasing: specific leaf weight, nitrogen per leaf area and fruit size at harvest for samples collected adjacent to where the light measurements were made. From these results it appears as though specific leaf weight, and nitrogen per leaf area may be useful indicators for determining if light intensity is a limiting factor on fruit sizing within the canopy of Manzanillo olive. These and additional data will be discussed.
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Delwiche, Michael J., and Reginald A. Baumgardner. "Conversion Between Southeastern and California Peach Sizes." HortScience 21, no. 5 (October 1986): 1238–39. http://dx.doi.org/10.21273/hortsci.21.5.1238.
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Abstract The 2 largest production regions of fresh-market peaches in the United States—California and Southeast—collectively account for two-thirds of the total U.S. crop (3), yet use completely different sizing and labeling systems. Confusion occurs among producers and in marketing channels when comparing packed fruit from the 2 regions.
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Anastasya Bernike Br Ginting, Asima Manurung, Sutarman Sutarman, and Enita Dewi Br Tarigan. "Metode Material Requirement Planning (MRP) dalam Perencanaan Produksi Sirup Markisa Dewi." Jurnal Arjuna : Publikasi Ilmu Pendidikan, Bahasa dan Matematika 2, no. 4 (July 16, 2024): 246–69. http://dx.doi.org/10.61132/arjuna.v2i4.1102.
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This study examines the Material Requirement Planning (MRP) method in planning the production of Dewi Passion Fruit syrup. Through a literature study approach, collecting articles or journals related to production planning, determining order size and MRP. The results showed that the results of forecasting the demand for passion fruit syrup were 87,751 liters with passion fruit raw materials of 175,502 kg and sugar of 87,751kg. As well as based on the Material Requirement Planning (MRP) method and lot sizing techniques which include Silver Meal Algorithm and Wagner Within Algorithm, the one used in this study is Silver Meal Algorithm because it has a smaller total order cost and storage cost than Wagner Within Algorithm.
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Rehal, Jagbir, Gagan Jyot Kaur, and Harsimrat K. Bons. "Studies on physico-mechanical properties of W. Murcott mandarin." Journal of Applied and Natural Science 9, no. 1 (March 1, 2017): 80–84. http://dx.doi.org/10.31018/jans.v9i1.1154.
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The post-harvest physico-mechanical properties of fruits is important in adoption and design of varioushandling, packaging, storage and transportation systems. These are important for sizing and grading the fruit beforemarketing as well as demarcate their end use. Geometric, gravimetric and textural properties were determined forthe fresh samples of W. Murcottmandarin. The results show that W. Murcottfruit diameter varies from 81.82-68.97mm, equatorial length varies from 86.51-68.43 mm, and length varies from 61.33-52.08 mm. The specific mean areais 57.591 with the sphericity of 0.90. The L, a, b values were 53.37, 42.9 and 49.68 respectively. The firmness variedfrom 1.351-1.650 kgf. These physical attributes can be taken into consideration while designing the grading andprocessing equipment.
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Shellie, K. C., and R. L. Mangan. "Cooling Method and Fruit Weight: Efficacy of Hot Water Quarantine Treatment for Control of Mexican Fruit Fly in Mango." HortScience 37, no. 6 (October 2002): 910–13. http://dx.doi.org/10.21273/hortsci.37.6.910.
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The objective of this research was to determine whether immediate cooling of mangoes (Mangifera indica L.) in water or air affected survival of Mexican fruit fly (Anastrepha ludens Loew) larvae. Two tests were conducted with mortality of late third instar Mexican fruit fly larvae evaluated after infested mangoes were immersed in 46.1 °C water for 65, 75, or 90 minutes depending on fruit weight and immediately cooled in water or air at 22 to 26.5 °C. Results suggest a need to amend the current hot water quarantine dip treatment schedule to require cooling of fruit for 30 minutes in air. We suggest a 25-g allowance in maximum permitted fruit weight be established for the 65-, 75-, and 90-minute dips and a monitoring system used to ensure compliance. Synchronization between maximum permitted fruit weight for each hot water dip duration and commercial sizing practices would facilitate monitoring of fruit weight. We also recommend confirmation of efficacy for the 75-minute treatment of flat-elongated mangoes that weigh 375-570 g.
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Neupane, Chiranjivi, Anand Koirala, and Kerry B. Walsh. "In-Orchard Sizing of Mango Fruit: 1. Comparison of Machine Vision Based Methods for On-The-Go Estimation." Horticulturae 8, no. 12 (December 19, 2022): 1223. http://dx.doi.org/10.3390/horticulturae8121223.
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Estimation of fruit size on-tree is useful for yield estimation, harvest timing and market planning. Automation of measurement of fruit size on-tree is possible using RGB-depth (RGB-D) cameras, if partly occluded fruit can be removed from consideration. An RGB-D Time of Flight camera was used in an imaging system that can be driven through an orchard. Three approaches were compared, being: (i) refined bounding box dimensions of a YOLO object detector; (ii) bounding box dimensions of an instance segmentation model (Mask R-CNN) applied to canopy images, and (iii) instance segmentation applied to extracted bounding boxes from a YOLO detection model. YOLO versions 3, 4 and 7 and their tiny variants were compared to an in-house variant, MangoYOLO, for this application, with YOLO v4-tiny adopted. Criteria developed to exclude occluded fruit by filtering based on depth, mask size, ellipse to mask area ratio and difference between refined bounding box height and ellipse major axis. The lowest root mean square error (RMSE) of 4.7 mm and 5.1 mm on the lineal length dimensions of a population (n = 104) of Honey Gold and Keitt varieties of mango fruit, respectively, and the lowest fruit exclusion rate was achieved using method (ii), while the RMSE on estimated fruit weight was 113 g on a population weight range between 180 and 1130 g. An example use is provided, with the method applied to video of an orchard row to produce a weight frequency distribution related to packing tray size.
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Markovic, Dragan, Nikola Mladenovic, Vojislav Simonovic, and Ivana Markovic. "Modeling the motion and mass quantity of fruit by rotating sizing machines." FME Transaction 42, no. 1 (2014): 34–39. http://dx.doi.org/10.5937/fmet1401034m.
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K. Y. Liu, L. H. Chen, and C. K. Yang. "Development of a Sizing System for Tree Fruit on Slopeland in Taiwan." Applied Engineering in Agriculture 7, no. 6 (1991): 661–66. http://dx.doi.org/10.13031/2013.26305.
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Wilcox, M. A., C. A. Sanchez, G. Wright, and P. Brown. "Response of `Lisbon' Lemons to Irrigation Frequency in the Arizona Desert." HortScience 30, no. 4 (July 1995): 839B—839. http://dx.doi.org/10.21273/hortsci.30.4.839b.
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The majority of citrus planted in southwestern Arizona are lemons. Lemons are generally more vigorous and usually produce higher yields than other citrus cultivars. However, under water stress, fruit size will be compromised and excessive fruit drop will occur. Limited information is available that addresses the issue of irrigation frequencies and the impact on fruit sizing of lemons. A field study was initiated in 1993 evaluate the response of `'Lisbon' lemons to various flood irrigation intervals. Irrigation intervals were based on soil moisture depletion (SMD), as calculated from frequent neutron probe soil moisture measurements. Individual treatments were irrigated when total SMD was 25%, 40%, 55%, and 70%, respectively. The experiment is a completely random design with four replications. Results indicate that both the most-frequent (25% SMD) and least-frequent (70% SMD) irrigation regimes produced negative results. Overall, the first year's results indicate optimal fruit growth and yield is achieved at 40% SMD.
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Anderson, Nicholas Todd, Kerry Brian Walsh, and Dvoralai Wulfsohn. "Technologies for Forecasting Tree Fruit Load and Harvest Timing—From Ground, Sky and Time." Agronomy 11, no. 7 (July 14, 2021): 1409. http://dx.doi.org/10.3390/agronomy11071409.
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The management and marketing of fruit requires data on expected numbers, size, quality and timing. Current practice estimates orchard fruit load based on the qualitative assessment of fruit number per tree and historical orchard yield, or manually counting a subsample of trees. This review considers technological aids assisting these estimates, in terms of: (i) improving sampling strategies by the number of units to be counted and their selection; (ii) machine vision for the direct measurement of fruit number and size on the canopy; (iii) aerial or satellite imagery for the acquisition of information on tree structural parameters and spectral indices, with the indirect assessment of fruit load; (iv) models extrapolating historical yield data with knowledge of tree management and climate parameters, and (v) technologies relevant to the estimation of harvest timing such as heat units and the proximal sensing of fruit maturity attributes. Machine vision is currently dominating research outputs on fruit load estimation, while the improvement of sampling strategies has potential for a widespread impact. Techniques based on tree parameters and modeling offer scalability, but tree crops are complicated (perennialism). The use of machine vision for flowering estimates, fruit sizing, external quality evaluation is also considered. The potential synergies between technologies are highlighted.
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Neupane, Chiranjivi, Anand Koirala, Zhenglin Wang, and Kerry Brian Walsh. "Evaluation of Depth Cameras for Use in Fruit Localization and Sizing: Finding a Successor to Kinect v2." Agronomy 11, no. 9 (September 5, 2021): 1780. http://dx.doi.org/10.3390/agronomy11091780.
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Eight depth cameras varying in operational principle (stereoscopy: ZED, ZED2, OAK-D; IR active stereoscopy: Real Sense D435; time of flight (ToF): Real Sense L515, Kinect v2, Blaze 101, Azure Kinect) were compared in context of use for in-orchard fruit localization and sizing. For this application, a specification on bias-corrected root mean square error of 20 mm for a camera-to-fruit distance of 2 m and operation under sunlit field conditions was set. The ToF cameras achieved the measurement specification, with a recommendation for use of Blaze 101 or Azure Kinect made in terms of operation in sunlight and in orchard conditions. For a camera-to-fruit distance of 1.5 m in sunlight, the Azure Kinect measurement achieved an RMSE of 6 mm, a bias of 17 mm, an SD of 2 mm and a fill rate of 100% for depth values of a central 50 × 50 pixels group. To enable inter-study comparisons, it is recommended that future assessments of depth cameras for this application should include estimation of a bias-corrected RMSE and estimation of bias on estimated camera-to-fruit distances at 50 cm intervals to 3 m, under both artificial light and sunlight, with characterization of image distortion and estimation of fill rate.
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Mirwansyah, Dedy, and Arief Wibowo. "FRUIT IMAGE CLASSIFICATION USING DEEP LEARNING ALGORITHM: SYSTEMATIC LITERATURE REVIEW (SLR)." MULTICA SCIENCE AND TECHNOLOGY (MST) JOURNAL 2, no. 2 (October 31, 2022): 120–23. http://dx.doi.org/10.47002/mst.v2i2.356.
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Systematic literature review (SLR) research studies various classification models with deep learning algorithms on fruit with digital images. In recent years, computer vision and processing techniques are increasingly useful in the fruit industry, especially for quality and color inspection, sizing, and shape sorting applications. Research in this area demonstrates the feasibility of using a machine computer vision system to improve product quality. Utilizing deep learning in the field of image processing or digital image processing, Image Processing is used to assist humans in recognizing and/or classifying objects quickly, and precisely, and can process large amounts of data simultaneously. Classifying fruit through a computerized system using deep learning algorithms with CNN, MASK-RCNN, FASTER-RCNN, and SSD models. Developed on the multilayer perceptron (MLP) layer, the algorithm is processed into two-dimensional data, to the image and is capable of classifying images with larger classes.
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Neupane, Chiranjivi, Kerry B. Walsh, Rafael Goulart, and Anand Koirala. "Developing Machine Vision in Tree-Fruit Applications—Fruit Count, Fruit Size and Branch Avoidance in Automated Harvesting." Sensors 24, no. 17 (August 29, 2024): 5593. http://dx.doi.org/10.3390/s24175593.
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Recent developments in affordable depth imaging hardware and the use of 2D Convolutional Neural Networks (CNN) in object detection and segmentation have accelerated the adoption of machine vision in a range of applications, with mainstream models often out-performing previous application-specific architectures. The need for the release of training and test datasets with any work reporting model development is emphasized to enable the re-evaluation of published work. An additional reporting need is the documentation of the performance of the re-training of a given model, quantifying the impact of stochastic processes in training. Three mango orchard applications were considered: the (i) fruit count, (ii) fruit size and (iii) branch avoidance in automated harvesting. All training and test datasets used in this work are available publicly. The mAP ‘coefficient of variation’ (Standard Deviation, SD, divided by mean of predictions using models of repeated trainings × 100) was approximately 0.2% for the fruit detection model and 1 and 2% for the fruit and branch segmentation models, respectively. A YOLOv8m model achieved a mAP50 of 99.3%, outperforming the previous benchmark, the purpose-designed ‘MangoYOLO’, for the application of the real-time detection of mango fruit on images of tree canopies using an edge computing device as a viable use case. YOLOv8 and v9 models outperformed the benchmark MaskR-CNN model in terms of their accuracy and inference time, achieving up to a 98.8% mAP50 on fruit predictions and 66.2% on branches in a leafy canopy. For fruit sizing, the accuracy of YOLOv8m-seg was like that achieved using Mask R-CNN, but the inference time was much shorter, again an enabler for the field adoption of this technology. A branch avoidance algorithm was proposed, where the implementation of this algorithm in real-time on an edge computing device was enabled by the short inference time of a YOLOv8-seg model for branches and fruit. This capability contributes to the development of automated fruit harvesting.
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Zeeshan, Sadaf, and Tauseef Aized. "Design and Analysis of a Solar Energy System for a Fruit Harvesting Robot in Pakistan." Acta Technologica Agriculturae 26, no. 4 (November 14, 2023): 185–93. http://dx.doi.org/10.2478/ata-2023-0025.
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Abstract In order to meet the growing agricultural demands, modern machinery needs to be deployed and cheaper energy supply needs to be ensured. With advancements in artificial intelligence, fruit harvesting robots can improve both the quality and productivity of fruit picking and increase orange fruit exports. However, to ensure effective working of the fruit harvesting robot, an energy source that is both efficient and cost-effective is necessary. This paper aims at designing of a solar energy system for a lightweight fruit harvesting robot for orange orchards in Pakistan and conducting a feasibility study for the deployment of the robot for remote agricultural land. The site for fruit harvesting robot employment is decided by irradiance using random forest regression. Solar system sizing is done based on the design and energy requirements of the fruit harvesting robot. The Homer Pro software is used for simulation of the system to analyse the potential of using solar system for fruit harvesting robot in Sargodha, Pakistan. The results show that compared to hybrid system, a stand-alone system is a more cost effective, reliable, and efficient option with a payback time of 3.36 years and levelized cost of energy being $0.085 per unit kWh. This study proves that solar energy is a viable and cheaper solution for using modern agricultural machineries, like fruit harvesting robot, in remote areas in developing countries, like Pakistan, to enhance productivity and improving quality of the produce.
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Piñeros, Juan, Alyne Toscano, Deisemara Ferreira, and Reinaldo Morabito. "Datasets for lot sizing and scheduling problems in the fruit-based beverage production process." Data in Brief 35 (April 2021): 106810. http://dx.doi.org/10.1016/j.dib.2021.106810.
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Neupane, C., K. B. Walsh, and A. Koirala. "Machine vision with deep learning for in-orchard mango fruit sizing and size distribution." Acta Horticulturae, no. 1395 (May 2024): 317–24. http://dx.doi.org/10.17660/actahortic.2024.1395.42.
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Margulies, Rebecca, and Leslie Miller. "Fruit Size as a Model for Teaching First Trimester Uterine Sizing in Bimanual Examination." Obstetrics & Gynecology 98, no. 2 (August 2001): 341–44. http://dx.doi.org/10.1097/00006250-200108000-00027.
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Margulies, R. "Fruit size as a model for teaching first trimester uterine sizing in bimanual examination." Obstetrics & Gynecology 98, no. 2 (August 2001): 341–44. http://dx.doi.org/10.1016/s0029-7844(01)01406-5.
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NeSmith, D. Scott. "REGIONALIZATION AND FRUIT CROPS IN THE SOUTHERN REGION: INTRODUCTION." HortScience 40, no. 3 (June 2005): 890b—890. http://dx.doi.org/10.21273/hortsci.40.3.890b.
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Regionalization is a contemporary issue facing those of us involved in research, teaching and extension in the area of agricultural and environmental sciences. Primarily, regionalization involves sharing of intellectual resources (i.e., scientists, specialists) across institutional boundaries to accomplish common objectives. While at times it seems that regionalization is simply a euphemism for down-sizing, the issue can actually be broader reaching than that. Given our increased ability for virtual technology transfer, the global market our clientele face, and the ever decreasing budgets for agriculture, regionalization may well be a key to meeting the needs of those we serve in the most cost efficient way. Hopefully, as we regionalize, the efforts will be synergistic. There also has to be awareness that personal contact with our constituents is still highly desirable for many. The purpose of this forum is to gain perspectives, both pros and cons, from those involved in regional efforts. These perspectives will include an administrator, a regional faculty, and an extension specialist/agent. Also, there will be two examples of regional efforts that are underway: the USDA–ARS Southern Horticultural Laboratory and the Southern Region Small Fruit Consortium.
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Barrueto Guzmán, Aldo, Rodrigo Barraza Vicencio, Jorge Ardila-Rey, Eduardo Núñez Ahumada, Arturo González Araya, and Gerardo Arancibia Moreno. "A Cost-Effective Methodology for Sizing Solar PV Systems for Existing Irrigation Facilities in Chile." Energies 11, no. 7 (July 16, 2018): 1853. http://dx.doi.org/10.3390/en11071853.
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In the last five years, the Chilean Ministries of Agriculture and Energy developed a national strategy to incorporate renewable energies into various economic sectors. Since 2013, more than 1500 off-grid solar photovoltaic (PV) systems, with power ranging from 1 kW to 3 kW, were installed to drive existing irrigation systems in small and medium-sized farms for the exportation of fresh fruit. A net billing regulation was also implemented in 2014. This study shows a cost-effective methodology for the sizing of solar PV systems for existing irrigation facilities in Chile, in an effort to improve the competitiveness of the fresh-fruit industry. The same methodology may also be implemented in other Latin American countries. The article presents the analysis of four projects (two in the Atacama Region, and two in the Maule Region). The baseline situation of the four units was studied, as well as the energy-efficient actions that may be applied, in addition to the recommended characteristics of the selected PV system to drive the irrigation systems of small fresh-fruit farms. Off-grid and on-grid solar PV systems were analyzed, including some particularities of the Chilean regulations. The required water demand of the irrigation systems and their corresponding pressure heads were also determined. The electricity demand of the system was calculated, and the PV system was designed for an optimal irrigation system. Additionally, an economical assessment was made for two years. In the first year, the cost effectiveness of energy-efficient actions was evaluated for the irrigation system, and it was found that they had paybacks of approximately two years. In the second year, the implementation of a PV system in each demonstrative unit was evaluated. The on-grid solar PV system performed better than the off-grid system, with evaluated paybacks of approximately 12 years. Finally, some recommendations for a well-designed on-grid solar PV system were made on the basis of it lasting over 25 years, with an adequate operation and maintenance plan.
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Kim, Y. K., and C. L. Xiao. "Distribution and Incidence of Sphaeropsis Rot in Apple in Washington State." Plant Disease 92, no. 6 (June 2008): 940–46. http://dx.doi.org/10.1094/pdis-92-6-0940.
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Sphaeropsis rot, caused by Sphaeropsis pyriputrescens, is a recently recognized postharvest disease of apple in Washington State. To determine the distribution and incidence of this disease as well as other postharvest diseases, decayed fruit were sampled during packing or pre-sizing operations in commercial fruit packinghouses from 26, 72, and 81 grower lots in 2003, 2004, and 2005, respectively. Fungi associated with decayed fruit were isolated and identified. The most common postharvest diseases of apple in the region were blue mold caused by Penicillium spp., primarily P. expansum, gray mold caused by Botrytis cinerea, and Sphaeropsis rot, accounting for 32, 28, and 17% of the decayed fruit, respectively. Percentages of these diseases in the total decayed fruit varied from lot to lot. Bull's eye rot caused by Neofabraea spp. was responsible for 13.4% of the total decay and was most prevalent on Golden Delicious. Other minor diseases included speck rot caused by Phacidiopycnis washingtonensis, Alternaria rot caused by Alternaria spp., Mucor rot caused by Mucor piriformis, and core rot caused by a group of fungi, primarily Alternaria spp. Sphaeropsis stem-end rot was more common than calyx-end rot on Golden Delicious, whereas Sphaeropsis calyx-end rot was more common than stem-end rot on Fuji. On Red Delicious, both stem-end rot and calyx-end rot were common. Sphaeropsis rot resulting from infections through the fruit peel was more commonly seen on Golden Delicious and Fuji than on Red Delicious. The percentage of gray mold was higher on nondrenched fruit than on fruit drenched with thiabendazole (TBZ), whereas blue mold was more prevalent on TBZ-drenched fruit. Our results indicate that Sphaeropsis rot is an important component of storage rots of apples in Washington State.
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Dhonju, Hari Krishna, Thakur Bhattarai, Marcelo H. Amaral, Martina Matzner, and Kerry B. Walsh. "Management Information Systems for Tree Fruit–2: Design of a Mango Harvest Forecast Engine." Horticulturae 10, no. 3 (March 20, 2024): 301. http://dx.doi.org/10.3390/horticulturae10030301.
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Spatially enabled yield forecasting is a key component of farm Management Information Systems (MISs) for broadacre grain production, enabling management decisions such as variable rate fertilization. However, such a capability has been lacking for soft (fleshy)-tree-fruit harvest load, with relevant tools for automated assessment having been developed only recently. Such tools include improved estimates of the heat units required for fruit maturation and in-field machine vision for flower and fruit count and fruit sizing. Feedback on the need for and issues in forecasting were documented. A mango ‘harvest forecast engine’ was designed for the forecasting of harvest timing and fruit load, to aid harvest management. Inputs include 15 min interval temperature data per orchard block, weekly manual or machine-vision-derived estimates of flowering, and preharvest manual or machine-vision-derived estimates of fruit load on an orchard block level across the farm. Outputs include predicted optimal harvest time and fruit load, on a per block and per week basis, to inform harvest scheduling. Use cases are provided, including forecast of the order of harvest of blocks within the orchard, management of harvest windows to match harvesting resources such as staff availability, and within block spatial allocation of resources, such as adequate placement of harvest field bin and frost fans. Design requirements for an effective harvest MIS software artefact incorporating the forecast engine are documented, including an integrated database supporting spatial query, data analysis, processing and mapping, an integrated geospatial database for managing of large spatial–temporal datasets, and use of dynamic web map services to enable rapid visualization of large datasets.
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Gilreath, James P., Carlene A. Chase, and Salvadore J. Locascio. "Crop Injury from Sublethal Rates of Herbicide. I. Tomato." HortScience 36, no. 4 (July 2001): 669–73. http://dx.doi.org/10.21273/hortsci.36.4.669.
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Drift from pesticides can kill or damage nontarget organisms. In these studies, the effects of sublethal rates of the herbicide glyphosate applied prebloom, at bloom, and postbloom of the first flower cluster were evaluated in tomato (Lycopersicon esculentum Mill.). As rates increased from 1 to 100 g·ha-1, foliar injury and flower and fruit number per plant varied with the stage of development at the time of exposure and the time of evaluation after treatment. Plants treated with 60 and 100 g·ha-1 glyphosate prebloom and at bloom had developed moderate to severe foliar injury by 14 days after treatment, but phytotoxicity to plants treated postbloom was only mild to moderate. Blooms abscised from plants treated with 60 and 100 g·ha-1 glyphosate for several weeks after application and fruit set was reduced. Greatest yield losses occurred following treatment prebloom (just prior to bloom) and at bloom. Plants treated before emergence of flower buds, and more mature plants exposed when first cluster fruit were sizing, yielded better than did those treated just prior to bloom and at bloom. Chemical name used: N-(phosphonomethyl)glycine (glyphosate).
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Hidayatulloh, Irwan, Emmanuela Maria Widyanti, Endang Kusumawati, and Lidya Elizabeth. "Nanocellulose Production from Empty Palm Oil Fruit Bunches (EPOFB) Using Hydrolysis Followed by Freeze Drying." ASEAN Journal of Chemical Engineering 21, no. 1 (June 30, 2021): 52. http://dx.doi.org/10.22146/ajche.61093.
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Empty palm oil fruit bunches (EPOFB) are lignocellulose which is abundantly available in Indonesia. EPOFB has big potential as raw materials to substitute wood in nanocellulose manufacture. The production of nanocellulose from EOPFB consists of various stages, such as preparation by grinding and sizing, α-cellulose isolation, acid hydrolysis, and freeze-drying. α-cellulose isolate from POEFB through delignification using 17.5% NaOH (w / v) at 80oC for 30 minutes and bleaching using 10% H2O2 (v / v) at 70oC for 15 minutes. The bleached cellulose was then hydrolyzed by acid hydrolysis process using 64% H2SO4 for 45 minutes with temperature variations to determine the effect of temperature on the size of nanocellulose. Obtained nanocellulose then dried with the freeze-drying method at a temperature of 50oC for 6 hours. The nanocellulose morphology was characterized using SEM analysis, and FTIR analysis was done to determine the presence of cellulose and lignin. The smallest average diameter obtained at 50oC temperature is 86.8 nm with a 51.5 – 66.5 nm distribution range.
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Lopez, G., and T. DeJong. "USING GROWING DEGREE HOURS ACCUMULATED THIRTY DAYS AFTER BLOOM TO HELP GROWERS PREDICT DIFFICULT FRUIT SIZING YEARS." Acta Horticulturae, no. 803 (November 2008): 175–80. http://dx.doi.org/10.17660/actahortic.2008.803.22.
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Barakat, Shimaa. "Optimal Sizing and Techno-Economic Analysis of an Off-Grid PV/Battery System for Fruit Farm Electrification." Journal of Engineering Science and Sustainable Industrial Technology 2, no. 1 (January 1, 2024): 26–32. http://dx.doi.org/10.21608/jessit.2023.218793.1000.
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Galletta, G. J., J. M. Enns, and J. L. Maas. "Strawberry Cultivar Responses to Variations in Planting Time, Stock, and Mulches." HortScience 31, no. 4 (August 1996): 610c—610. http://dx.doi.org/10.21273/hortsci.31.4.610c.
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The cultivars Allstar, Honeoye, Kent, and Jewel yielded the most successful summer and subsequent spring crops when planted in mid-July from dormant, cold-stored, multiple-crowned, nursery mother plants. Summer fruit sizing during very high temperatures was a problem; fruit number and quality was not. In a second hot year, the same cultivars did not give satisfactory summer crops when planted after late July. The return spring crop was most successful following planting in July rather than August or September, though there was a significant cultivar × planting date interaction for a number of characters. Nursery mother plants were more productive than first daughter plants. `Tristar' outyielded `Seascape' on black poly-mulched beds but not on killed vetch sod beds. `Allstar' runnered freely and produced good crops on three types of raised bed killed sod mulches and on red, blue, and silver-painted black poly raised bed mulches. Compared to the summer-planted, black, poly-mulched standard, `Mohawk' had increased but later yields, when the poly was painted blue, red, or silver, and much later yields, when mulched with recycled paper or wood fiber. The silver and paper treatments depressed fruit size. The wood fiber mulch seems promising for deliberately delaying ripening by lowering soil temperatures under the mulch. Seedling and selection plantings have generally responded favorably to summer planting from potted or “plug” plant stocks on unfumigated soil, thus, shortening the selection and evaluation cycles, with accompanying savings in land, water, fertilizer, and pesticide use.
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Paull, Robert E., Benjamin Wiseman, and Gail Uruu. "Pineapple Field Establishment Using Slips." HortScience 57, no. 12 (December 2022): 1540–44. http://dx.doi.org/10.21273/hortsci16877-22.
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Slips are side-shoots or fruit with large crowns that grow from buds on the pineapple (Ananas comosus L.) peduncle. The slips are widely used for pineapple vegetative propagation when crowns are left attached to the fruit that is marketed. There is a difference between the two most popular low-acid pineapple hybrids grown worldwide. The ‘Pineapple Research Institute 73-50’ (CO-2, MD-1) slips develop few roots when planted compared with ‘Pineapple Research Institute 73-114’ (MD2). The slow rooting of 73-50 leads to slow field establishment and can extend the crop cycle. Our objective was to determine the cause of this reduced rooting and evaluate treatments to increase the rooting rate. Rooting trials in moist, coarse vermiculite showed that larger slips and green slips with red hues also had a greater number of roots compared with smaller slips and green or yellow slips. Delaying harvesting of the slips after the fruit were harvested also resulted in a greater number of roots. Treatments including components frequently used for rooting cuttings did not significantly increase root numbers. An exception was a tendency for slips treated with potassium nitrate to have greater rooting during some tests. We present data that support the conclusion that the poor root development is associated with the mechanical impedance of the root from the tightly affixed basal leaf bracts. Removal of the lower ten bracts can lead to greater root numbers. When the slip with the bracts removed was tightly wrapped in plastic wrap and masking tape, rooting was reduced. The sizing and selection of slips that are green with a red hue and collected as late as possible after fruit harvest had the best rooting response.
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Ndruru, Indah Fiyar, Saleha Hannum, and Suci Rahayu. "Genetic Diversity of Durian (Durio zibethinus Murr.) from North and South Nias using Simple Sequence Repeat (SSR)." International Journal of Ecophysiology 5, no. 2 (November 8, 2023): 69–75. http://dx.doi.org/10.32734/ijoep.v5i2.14314.
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Durian is a tropical fruit that has economic value for Nias Island especially in North and South Nias. Anthropogenic activity already occured in Nias and caused disturbance resulting in destruction and extinction of various durian. The aim of the research was to analyzed the genetic diversity of Durian from North and South Nias using SSR primers namely: Dz844, DzGCCG01, DzGCAG01, and DzMTb021. Total DNA was successfully isolated from 20 accessions. The DNA was successfully amplified resulting in DNA alleles sizing from 170-1100 bp. All primers showed 33 alleles with 28 polymorphic bands. The DNA profile were further analyzed with Ntsys which showed that 20 accession has coefficient of similarity 0.66-0.94 and clustered into nine groups at the similarity coefficient of 0.80. The research showed that the ninth accession of durian from North and South Nias has a high genetic diversity.
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Apazhev, A. K., Ar M. Egozhev, and A. A. Egozhev. "Substantiation of the design and technological parameters of the working body of the cutter for tillage around the tree stem in a terrace." Izvestiya of Kabardino-Balkarian State Agrarian University named after V.M. Kokov, no. 2(36) (2022): 68–76. http://dx.doi.org/10.55196/2411-3492-2022-2-36-68-76.
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Gardening in the conditions of mountainous and foothill zones with the use of new technologies is a promising direction of agriculture. Terra-sizing in mountainous and foothill zones contributes to the development of new areas for fruit crops, which are not suitable for gardening without this event, which is a priority in conditions of limited land use areas. The main direction of improving soil care technologies in gardens, in the conditions of the foothill zone, is the introduction of mechanization tools for processing the trunk strips of terraces, ensuring the effective use of the root system of fruit plantations. The problem faced by farmers in these conditions is the lack of modern equipment for the care of the trunk strips of fruit plantations. The introduction of new machines and units for the mechanical processing of the barrel circle in one pass of the unit, contributing to the increase of soil fertility in the conditions of terraces, is relevant. A constructive and technological scheme of the working body of a garden cutter is proposed, the technical result of which is to perform a highquality processing process in the area of the trunk circle by ensuring the bypass of the rotors around the tree stem, in one pass of the unit along the row line, for which a utility model patent was obtained. Analytical dependences have been obtained that allow us to determine the influence of the main design parameters, as well as the operating modes of the new milling cutter design, on the quality of the technological process.
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Parekh, Niyati, Gabrielle Khalife, Natalie Hellmers, and Gail D’Eramo Melkus. "The Healthy Eating and Living Against Noncommunicable Diseases Study: An Innovative Family-Based Intervention." Diabetes Educator 46, no. 6 (October 30, 2020): 569–79. http://dx.doi.org/10.1177/0145721720965491.
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Objective Inadequate nutrition literacy within families is a barrier for healthy dietary choices and influences chronic disease risk. This pilot study examined the feasibility of providing an in-person nutrition intervention for families at high risk of developing prediabetes or type 2 diabetes and cardiovascular risk-factors. Methods Eligible families had at least one member with a non-communicable disease (NCD) or metabolic risk factor, fluency in English, willingness to attend all three educational sessions and complete questionnaires as a family unit. Sessions included didactic and experiential activities on food label reading, portion sizing, physical activity and modifiable lifestyle factors to reduce NCD risk. Demographics and fruit and vegetable screeners were collected from all participants at baseline and after completion of sessions. Families participated in focus groups to evaluate the program. Results Twelve families (n=35;17 adults;18 children) were recruited from New York City. Participants self-identified as Asian, Hispanic or Black. Adults had a mean age of 40y, BMI of 32.29kg/m2, household income of $35,000-$49,000y, and 13 of 17 adult participants had college degrees. Children ranged from 1-17y. Based on focus group feedback, three sessions were acceptable, families reported enjoying interactive activities and group learning and requested child-friendly activities. They reported improved knowledge of food labels, strategies for grocery shopping, portion-sizing, and increased awareness of the links between diet quality and NCDs. Conclusions and Implications The study met recruitment goals within 4 months. The educational intervention was acceptable and may be scaled-up for future studies on NCD prevention, particularly prediabetes and type 2 diabetes.
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Lee, Jaesu, Haseeb Nazki, Jeonghyun Baek, Youngsin Hong, and Meonghun Lee. "Artificial Intelligence Approach for Tomato Detection and Mass Estimation in Precision Agriculture." Sustainability 12, no. 21 (November 3, 2020): 9138. http://dx.doi.org/10.3390/su12219138.
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Application of computer vision and robotics in agriculture requires sufficient knowledge and understanding of the physical properties of the object of interest. Yield monitoring is an example where these properties affect the quantified estimation of yield mass. In this study, we propose an image-processing and artificial intelligence-based system using multi-class detection with instance-wise segmentation of fruits in an image that can further estimate dimensions and mass. We analyze a tomato image dataset with mass and dimension values collected using a calibrated vision system and accurate measuring devices. After successful detection and instance-wise segmentation, we extract the real-world dimensions of the fruit. Our characterization results exhibited a significantly high correlation between dimensions and mass, indicating that artificial intelligence algorithms can effectively capture this complex physical relation to estimate the final mass. We also compare different artificial intelligence algorithms to show that the computed mass agrees well with the actual mass. Detection and segmentation results show an average mask intersection over union of 96.05%, mean average precision of 92.28%, detection accuracy of 99.02%, and precision of 99.7%. The mean absolute percentage error for mass estimation was 7.09 for 77 test samples using a bagged ensemble tree regressor. This approach could be applied to other computer vision and robotic applications such as sizing and packaging systems and automated harvesting or to other measuring instruments.
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Popović, Dražen, Nenad Bjelić, Milorad Vidović, and Branislava Ratković. "Solving a Production Lot-Sizing and Scheduling Problem from an Enhanced Inventory Management Perspective." Mathematics 11, no. 9 (April 28, 2023): 2099. http://dx.doi.org/10.3390/math11092099.
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In this study, we consider a production lot-sizing and scheduling problem found in the fruit juice production industry from an enhanced inventory management perspective. The problem can be classified as a P2SMM (two-stage multi-machine lot-scheduling) problem. We extended the classical P2SMM problem by incorporating an additional inventory management aspect of finished products to reflect a possible real-life case problem, specifically regarding the shelf-life concept and limited warehouse capacity, with a possibility of outsourcing the warehousing demand to a third-party logistics company. We developed the mixed integer linear programming (MILP) model to fully represent the considered problem (due to the NP-hard nature of the problem, only small-scale instances could be solved to optimality), and the hybrid variable neighborhood search with linear programming (VNS/LP) model to solve both small and real-life large-scale problem instances. The goal of the developed models is to minimize total costs that consist of the cost of backordering, the cost of planned minimum and maximum stock level violation, the cost of warehouse capacity overflow, the costs of production setup time and unused available production time. The main idea of the VNS/LP model is to solve the scheduling segment of P2SMM (the production sequence) via a VNS heuristic, and the lot-sizing segment of P2SMM via the linear programming (LP) model. Based on the results from five variants of the problem setup, a potential decision maker can have an overview of the impact of different important input parameters (production time costs, warehouse capacity and costs, inventory related costs and production demand) on the total cost of a production process and improve its efficiency in changing conditions.
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SAYINCI, Bahadir, Sezai ERCISLI, Ismail OZTURK, Zeynep ERYILMAZ, and Bunyamin DEMIR. "Determination of Size and Shape in the ‘Moro’ Blood Orange and ‘Valencia’ Sweet Orange Cultivar and its Mutants Using Image Processing." Notulae Botanicae Horti Agrobotanici Cluj-Napoca 40, no. 1 (May 14, 2012): 234. http://dx.doi.org/10.15835/nbha4016645.
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Fruit size and shape are important physical characteristics in designing relevant equipment, sorting, sizing and packaging systems. Therefore, the properties of size and shape of the sweet orange cultivar, ‘Valencia’, and its three mutants, ‘A70’, ‘A77’, and ‘A88’ were determined by image processing. The blood orange cultivar, ‘Moro’, was also included in this analysis. The volume of each cultivar and mutant was measured by the liquid displacement method. Linear equations with high R2 values were developed in order to estimate the surface area and geometric mean diameter, which were dependent upon the mass and volume of the orange samples. The results of this study showed that the ‘A70’ mutant differed from the other mutants and the ‘Valencia’ cultivar in regard to most physical properties. The ‘A70’ and ‘A88’ mutants and the ‘Valencia’ cultivar had the highest sphericity values, which varied from 96.41% to 97.18%. The lowest shape factor was found in the ‘Valencia’ cultivar, with a mean of 0.73. The elongation of the ‘A88’ mutant and ‘Valencia’ (1.07 each) was smaller than that of the other cultivars. The highest coefficient of variance was observed within the ‘Valencia’ and ‘Moro’ cultivars in most physical properties, suggesting that the ‘Valencia’ mutants produce more homogeneous fruits than the ‘Valencia’ cultivar itself.
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De Caluwé, Emmy, Kateřina Halamouá, and Patrick Van Damme. "Tamarindus indica L. – A review of traditional uses, phytochemistry and pharmacology." Afrika Focus 23, no. 1 (February 25, 2010): 53–83. http://dx.doi.org/10.1163/2031356x-02301006.
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Tamarind (Tamarindus indica, Fabaceae), a tropical fruit found in Africa and Asia is highly valued for its pulp. Tamarind fruit pulp has a sweet acidic taste due to a combination of high contents of tartaric acid and reducing sugars. The pulp is used for seasoning, in prepared foods, to flavour confections, curries and sauces, and as a major ingredient in juices and other beverages. Commercial tamarind-based drinks are available from many countries. Vitamin B content is quite high; carotene and vitamin C contents are low. Presence of tannins and other dyeing matters in the seed testa make the whole seed unsuitable for consumption, but they become edible after soaking and boiling in water. Tamarind kernel powder is an important sizing material in textile, paper and jute industries. Seeds are gaining importance as an alternative source of proteins, and are besides rich in some essential minerals. Seed pectin can form gels over a wide pH range. Leaves and flowers can be eaten as vegetables, and are prepared in a variety of dishes. They are used to make curries, salads, stews and soups. Tamarind leaves are a fair source of vitamin C and α-carotene; mineral content is high, particularly P, K, Ca and Mg. Anti-oxidant, anti-inflammatory, anti-microbial and anti-fungal activity has been documented from several plant parts. Tamarind is also extensively used in traditional medicine. The traditional uses, its phytochemistry and pharmacognosy is reviewed to provided with a particular orientation to its value in sub-Sahara Africa.
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Kabas, Onder, Mehmet Kayakus, and Georgiana Moiceanu. "Nondestructive Estimation of Hazelnut (Corylus avellana L.) Terminal Velocity and Drag Coefficient Based on Some Fruit Physical Properties Using Machine Learning Algorithms." Foods 12, no. 15 (July 28, 2023): 2879. http://dx.doi.org/10.3390/foods12152879.
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Hazelnut culture originated in Turkey, which has the highest volume and area of hazelnut production in the world. For the design and sizing of equipment and structures in agricultural operations for the hazelnut industry, especially harvesting operations and post-harvest operations, it is essential that an understanding of hazelnuts’ aerodynamic properties, i.e., terminal velocity and drag coefficient, is acquired. In this study, the moisture, mass, density, projected area, surface area, and geometric diameter were used as independent variables in the data set, and the dependent variables terminal velocity and drag coefficient estimation were determined. In this study, logistic regression (LR), support vector regression (SVR), and artificial neural networks (ANNs) were used based on machine learning methods. When the results were evaluated according to R2 (determination coefficient), MSE (mean squared error), and MAE (mean absolute error) metrics, it was seen that the most successful models were the ANN, SVR, and LR, respectively. According to the R2 metric, the ANN method achieved 91.5% for the terminal velocity of hazelnuts and 85.9% for the drag coefficient of hazelnuts. Using the independent variables in the study, it was seen that the terminal velocity and drag coefficient value of hazelnuts could be successfully estimated.
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Haryono, Ika Avrilina, and Noval Noval. "Formulasi dan Evaluasi Tablet Effervescent dari Ekstrak Buah Tampoi (Baccaurea macrocarpa)." Jurnal Surya Medika 7, no. 2 (February 1, 2022): 34–44. http://dx.doi.org/10.33084/jsm.v7i2.3201.
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Tampoi is one of the many plants found in East Kalimantan, has secondary metabolic content in the form of saponins, flavonoids, and alkaloids, and has antioxidant activity. The antioxidants produced by the human body are not sufficient to fight free radicals, therefore the body requires the intake of antioxidants from the outside, so to help increase public interest in consumption, researchers are interested in making preparations in the form of extracts and formulated as effervescent tablets from tampoi fruit extract which are useful as antioxidants and increase immunity. The purpose of this study was to determine a good formula for making effervescent tablets from tampoi fruit extract with variations of PVP K30 as a binder. Making tablets using direct compression method with an evaluation of effervescent powder including the angle of repose test, flow rate, setting, compressibility, and moisture of the powder. Evaluation of effervescent tablets included organoleptic test, weight uniformity test, tablet friability test, tablet hardness test, and tablet dissolving time test. The results obtained in the evaluation of the effervescent powder, the angle of repose test has met the requirements, while the test for flow velocity, sizing, compressibility, and moisture of the powder has not met the requirements. The results of the physical evaluation of the tablet weight uniformity test on F1 and F2 were in accordance with the requirements, the tablet friability test on F3 and F4 had met the requirements, the F3 tablet hardness test had met the requirements, and the tablet dissolving time test resulted that all formulas met the requirements with the best formula namely F1 which has the fastest tablet dissolution time. The conclusion of the study from the evaluation of the dissolving time which is the main parameter of the effervescent tablet preparation of tampoi fruit extract, the best formula was obtained, namely F1 with a PVP K30 concentration of 0.5 mg resulting in a tablet dissolving time of 01.99 minutes.
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Zhang, Stephanie, Miles Markey, Caroline D. Pena, Tadmiri Venkatesh, and Maribel Vazquez. "A Micro-Optic Stalk (μOS) System to Model the Collective Migration of Retinal Neuroblasts." Micromachines 11, no. 4 (March 31, 2020): 363. http://dx.doi.org/10.3390/mi11040363.
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Contemporary regenerative therapies have introduced stem-like cells to replace damaged neurons in the visual system by recapitulating critical processes of eye development. The collective migration of neural stem cells is fundamental to retinogenesis and has been exceptionally well-studied using the fruit fly model of Drosophila Melanogaster. However, the migratory behavior of its retinal neuroblasts (RNBs) has been surprisingly understudied, despite being critical to retinal development in this invertebrate model. The current project developed a new microfluidic system to examine the collective migration of RNBs extracted from the developing visual system of Drosophila as a model for the collective motile processes of replacement neural stem cells. The system scales with the microstructure of the Drosophila optic stalk, which is a pre-cursor to the optic nerve, to produce signaling fields spatially comparable to in vivo RNB stimuli. Experiments used the micro-optic stalk system, or μOS, to demonstrate the preferred sizing and directional migration of collective, motile RNB groups in response to changes in exogenous concentrations of fibroblast growth factor (FGF), which is a key factor in development. Our data highlight the importance of cell-to-cell contacts in enabling cell cohesion during collective RNB migration and point to the unexplored synergy of invertebrate cell study and microfluidic platforms to advance regenerative strategies.