Coffee Branches Research Articles

Mycena citricolor isolates from diverse hosts in Costa Rica: Colony aspect, growth dynamics, reproduction in vitro and aggressiveness on Coffea arabica

AbstractThe basidiomycete fungus Mycena citricolor hosts on about 80 plant families. The asexual morph causes the disease known as American leaf spot of coffee (Coffea arabica). We isolated and characterized 15 isolates of M. citricolor collected from coffee plants, shade trees and weeds. Cultures on potato‐dextrose‐agar + yeast extract (PDAY) medium were kept for a week in complete darkness. The cultures were then exposed to light for 7 weeks and co‐cultivated with coffee foliar discs, to stimulate the production of gemmifers. We evaluated the speed of growth, appearance, colour of the mycelium and gemmifers production capacity. All isolates conformed to the typical cultural characteristics of M. citricolor, with beige/white thin and slightly aerial mycelium. The whitest isolate was from Persea americana, which had the slowest growth rate in vitro (6.4 mm/day), while the isolate from weed Kalanchoe pinnata was the fastest, with a speed of 9 mm/day. The most gemmifer‐producing isolates were those isolated from the coffee cultivar Catimor‐Costa Rica 95, Citharexylum donnell‐smithii and Cissus verticillata, with over 200 gemmifers per Petri dish. Isolates from Erythrina and Ipomoea nil produced <50 gemmifers on average. The Composite Aggressiveness Index (CAI) was determined on 2‐year‐old detached coffee branches of the Caturra variety foliage. The least aggressive isolate was from Erythrina poeppigiana (CAI = 0) and the most aggressive was from Kalanchoe pinnata (CAI = 18.87). The isolate from the coffee cultivar Catimor‐Costa Rica 95 was more aggressive than that from the cultivar Caturra (CAI = 9.94 vs. CAI = 3.66). Moreover, successful infection occurred only when the apex of gemmae made direct contact with the coffee leaf when using the inoculum derived from C. verticillata and Anredera cordifolia. These results show the variability in the population of the pathogen. This is the first study that characterizes the growth, morphology, reproduction and aggressiveness of M. citricolor obtained from hosts other than coffee. In addition, it is the first to report the use of coffee foliar discs to induce gemmifer production in vitro and to assess and quantify the effect of gemma position when inoculating coffee leaves.

Computer Vision-Aided Intelligent Monitoring of Coffee: Towards Sustainable Coffee Production

Earlier, researchers have employed computer vision-based automatic fruit detection to estimate coffee yield at the time of harvest, however, studies on the on-plant quantification of the coffee fruit are scarce. In this study, the latest version of the state-of-the-art algorithm YOLOv7 (You Only Look Once) was used for the first time. YOLOv7 was trained with 324 annotated images of fruit bearing coffee branches followed by its evaluation with 82 annotated images as validation data (supervised method) and then tested through raw images (unannotated) as test data. Meanwhile, the K-means models were trained which led to machine-generated color classes of coffee fruit for semi-supervised image annotation. Consequently, the developed model efficiently analyzed the test data with an mAP@.5 (mean average precision) of 0.89. Strikingly, our innovative semi-supervised method with an mAP@.5 of 0.77 for multi-class mode surpassed the supervised method which had mAP@.5 of only 0.60, leading to faster and more accurate annotation. While testing the yield estimation of the model in two plots, an average error of 3.78% was recorded between the predicted (pre-harvest) and ground truth (harvest) data for binary class mode. The average error for multi-class data was recorded as 3.87% for green, 3.445% for green-yellow, 5.09% for cherry-raisin, and 2.51% for dry fruits. This AI-based technology when integrated with other tools such as UAV would efficiently remotely monitor coffee field for informed decision about irrigation, fertilizer application and other measures of timely field management, hence advancing precision agriculture. Moreover, this machine learning intelligent model can be tailored for various other fruit farming.

Dynamic Behavior of Coffee Branches: an Analysis Using the Finite Element Method

Dynamic Behavior of Coffee Branches: an Analysis Using the Finite Element Method

Infestation of White Waxy Scale on Coffea arabica in Southwestern Ethiopia

Over 49 coffee insect species reported in Ethiopia. However, mealybugs and whitefly are the pests currently recorded in Ethiopia. Ceroplastes brevicauda (Hemiptera: Coccidae) is one of potentially important coffee pest. From assessed coffee trees around 96% and 27% mean infestation of bearing branch and dried branch due to the insect recorded, respectively from coffee hybrids. Coffee berry disease resistant cultivars were exhibit cross-susceptibility against white waxy scale. The white waxy scale although affecting Acacia abyssinica shade tree. Cultural pest management such as pruning infested coffee branches and rubbing the waxy scale by using alcohol is best fits in integrated pest management which usually recommended for coffee producers. Therefore, future research works should be focused on characterizing and identifying the natural enemies and screening insecticides as one management of pest management options.

Life Cycle and Damage Patterns of Tea Mosquito Bug (Helopeltis theivora Waterhouse), a Newly Recorded Pest on Arabica coff ee in Northern Thailand

The symptoms of “shot hole leaves” and “excess bud growth” in Arabica coffee have signifi cantly increased in northern Thailand since 2017, resulting in the death of shoots and reduced fl owering, ultimately leading to yield loss. This study investigates whether the “shot hole leaves” symptom is caused by the tea mosquito bug (Helopeltis theivora Waterhouse) (Hemiptera: Heteroptera: Miridae) by rearing tea mosquito bugs with coffee and reproducing the same symptoms under laboratory conditions. Furthermore, we examine whether the “shot hole leaves” symptom is associated with the “excess bud growth” symptom in the fi eld. Our results show that H. theivora can complete their life cycle on Arabica coffee trees. Female bugs lay an average of 87.60±41.82 eggs underneath the soft tissue near young leaves on coffee branches, with a hatching rate of 73.97±6.69%, and an average incubation period of 8.20±0.97 days. The longevity of the fi rst to fi fth nymphal stages was 4.02±1.58, 3.36±0.93, 3.27±0.74, 3.23±0.96, and 3.83±1.18 days, respectively. The adult bugs had a lifespan ranging from 2 to 24 days, with an average of 11.61±7.89 days. The “shot hole leaves” symptom appear approximately 14 days after H. theivora begin feeding on young coffee shoots. We found that the bud number is signifi cantly higher on twigs with the symptom, indicating that both symptoms are caused by H. theivora. The study concludes by discussing control practices of H. theivora on coffee trees.

Attack Level Of Coffee Fruit Borer Pest (Hypothenemus hampei) And Branch Borer Pest (Xylosandrus compactus) In Central Dempo District Pagaralam City

Pagaralam is a city in South Sumatra Province with five districts: North Dempo, Central Dempo, South Dempo, North Pagaralam and South Pagaralam. The main commodity is coffee. Coffee cultivation has a major problem, namely the attack of fruit and branch borer pests because it can reduce the quality and productivity of coffee. This study was to determine the level of attack by fruit borer and branch borer in the Dempo Tengah sub-district. Coffee farmers in Pagaralam use monoculture and polyculture cultivation systems. This field practice method is observation, observation in this study, and interviews with coffee farmers. The results showed that the attack of young coffee berry borer pests can cause the fruit to wither and fall off, while ripe fruit has holes in its seeds. Branch borer attacks cause branches to wither and dry. The highest percentage of fruit and branch borer attacks on coffee plants was found in young mixed-aged coffee plantations. In conclusion, fruit borer and coffee branch borer are more susceptible to attacking coffee at a young age, because young coffee plants have soft plant organs. Lush shade creates high humidity and low temperatures, which can make it easier for pests to breed.

Detection of coffee fruits on tree branches using computer vision

Coffee farmers do not have efficient tools to have sufficient and reliable information on the maturation stage of coffee fruits before harvest. In this study, we propose a computer vision system to detect and classify the Coffea arabica (L.) on tree branches in three classes: unripe (green), ripe (cherry), and overripe (dry). Based on deep learning algorithms, the computer vision model YOLO (You Only Look Once), was trained on 387 images taken from coffee branches using a smartphone. The YOLOv3 and YOLOv4, and their smaller versions (tiny), were assessed for fruit detection. The YOLOv4 and YOLOv4-tiny showed better performance when compared to YOLOv3, especially when smaller network sizes are considered. The mean average precision (mAP) for a network size of 800 × 800 pixels was equal to 81 %, 79 %, 78 %, and 77 % for YOLOv4, YOLOv4-tiny, YOLOv3, and YOLOv3-tiny, respectively. Despite the similar performance, the YOLOv4 feature extractor was more robust when images had greater object densities and for the detection of unripe fruits, which are generally more difficult to detect due to the color similarity to leaves in the background, partial occlusion by leaves and fruits, and lighting effects. This study shows the potential of computer vision systems based on deep learning to guide the decision-making of coffee farmers in more objective ways.

The Effect of Omni-Channel Integration Quality and Omni-Channel Perceived Value on Customer Loyalty Through Customer Satisfaction on Kenangan Coffee Branch OCBC Ringroad Medan

This study aims to analyze omni-channel integration quality and omni-channel perceived value on customer loyalty through customer satisfaction at Kopi Kenangan OCBC Ringroad. The type of research used in this research is associative research. The population in this study were consumers who had bought online and offline Kopi Kenangan OCBC Ringroad with 135 respondents as samples taken in this study. Withdrawal of the number of sample sizes is done by non-probability sampling using purposive sampling method. The data used are primary data and secondary data obtained through a list of statements and documentation studies. The data analysis technique uses structural equation modeling (SEM) with the Smart PLS version 3.0 analysis tool. The results directly show that omni-channel integration quality has a negative and significant effect on customer loyalty, omni-channel perceived value has a positive and significant effect on customer loyalty, omni-channel integration quality has a positive and significant effect on customer satisfaction, omni-channel perceived value positive and significant effect on customer satisfaction, and customer satisfaction has a positive and significant effect on customer loyalty. Then the results of the tests carried out indirectly indicate that customer satisfaction is able to mediate the relationship between omni-channel integration quality and customer loyalty, but customer satisfaction is able to mediate the relationship between omni-channel perceived value and customer loyalty. Keywords: Omni-channel integration quality, omni-channel perceived value, customer satisfaction, customer loyalty

The Impact of Green Human Resource Management on Employee Performance

Green Human Resource Management refers to a set of HRM practices that organizations adopt to improve employee green performance. Whilte the negative impact on the process of business production and human carbon footprint require company to adopt strategic movement and practice of sustainable business through Green HRM. The research focuses upon the various Green HR practices pursued by the coffee shop largest company in the world. It explains the simplified meaning of Green HRM. The research approach is using quantitative approach, extracted four mains of Green HRM practices used in company from literature, review, and journals provided. The identified practices were green recruitment, green development, green performance appraisal, and green reward. However, the study sample is all the employee of Starbucks Coffee in Manado city. The questionnaire was distributed to four Starbucks Coffee branches in Manado City within August to July 2020. Using ten-point Likert-type scale, these extracted practices were evaluated to find out which Green HRM indicators impact the employee performance best. The study found that the implementation of the Green HRM indicators such as green recruitment, green development, and green reward impact the employee performance in Starbucks Coffee in Manado city. This study recommends other researchers to examine other Green HRM indicators that might affect employee performance with a variety of other variables related to the application of green HRM concepts

Determination of physical and mechanical properties of the coffee branch: An experimental approach

In order to reduce the human efforts during the manual harvesting and increase the operational capacity and quality, the mechanization of the harvesting operation has been significantly increasingly in the last few years in the coffee crops. Therefore, for the design of coffee harvesting machines, the physical and mechanical properties of coffee branch are of utmost importance for harvesting machines project. In this way, using an experimental approach, the present paper analyzes the variability of physical and mechanical properties in the coffee branches. The branches were collected in different positions, along the orthotropic branch: upper, middle and lower parts of the plant. The mass, volume, specific mass and modulus of elasticity of the collected specimens were determined considering their position in the plant and position along the branches. ​​According to the position in the plant, no significant differences were found between the specific mass averages for the upper, middle and lower parts of the plant. The research had obtained an average of 1.24 GPa with a standard deviation of 0.13 GPa for the elasticity modulus. A significant increase in the elasticity modulus could be noted in the branches from the top to the bottom of the plant in the present research. Key words: Mechanized harvest; tensile test; elasticity modulus variation; coffee plant analysis; coffee branch analysis.

Water, energy and carbon dynamics over an intercropped sun-grown coffee and corn system

The energy dissipation and the evapotranspiration processes, are factors involved in the ecosystem net carbon exchange and are determinants in the ability of a self-regulating system to balance high carbon emissions. To discover these relationships, a corn production system intercropped with coffee was monitored during the first 19 months after the system establishment, to determine the flux of energy, water, gases, and carbon by implementing the eddy covariance technique. From the net carbon exchange ecosystem balance, during the first cycle of corn intercropped with coffee, 63 g C m-2 was fixed. For the next phase of coffee culture, maintaining the corn stalks and coffee branches, 5.4 g C m-2 was emitted. In the second cycle with intercropped corn, thefixation was 291 g of C m-2; and in the last period of the first reproductive stage of the coffee trees, 172 g C m-2 was fixed. Throughout the analysis period, the system behaved as a carbon sink with a potential fixation between 4.7 and 5.6 ton C ha-1. The energy, measured as net radiation, was estimated at 274.53 ± 5.2 W m-2 day-1, and it was dissipated mainly as sensible heat (26.5% - 53.6%), latent heat (45.7% - 71, 9%) and soil heat (0.5% - 1.6%). The crop coefficient (Kc) in the coffee vegetative stage in the monoculture, fluctuated between 0.79 ± 0.05 and 0.99 ± 0.04. For the intercropping system with corn, the Kc was calculated at 0.84 ± 0.05, 1.05 ± 0.06, 1.60 ± 0.09, and 1.22 ± 0.05 for the vegetative, pre-flowering, maximum foliar development and harvest maturity stages of corn, respectively. Key words: Eddy covariance; Net ecosystem exchange; Evapotranspiration; Water fluxes; Carbon dioxide fluxes.

Bionomics, Abundance and Management of Coffee White Stem Borer (Xylotrechus quadripes Chervolet) in Nepal

An experiment was conducted to study the life cycle, seasonal abundance and management practices of coffee white stem borer (Xylotrechus quadripes) at Horticulture Research Station, Kaski, Pokhara, Nepal from April, 2016 to October, 2019. The life cycle of coffee white stem borer was studied in laboratory by inoculation of first instar larvae into coffee branches up to adult emergence. The first instar larvae took 94±3 days to become adult. The monthly observation on the emergence of this borer showed that it was highly weather dependent and has two peak periods of emergence: April - June and September - November. Coffee white stem borer infestation was reduced to 11.11% with the application of treatments like scrubbing of stem and application of red soil mixed with fresh cow dung (1:1) or by stem scrubbing and application of Bordeaux paste on it followed by root zone application of Metarrhizium anisopliae (22.22%) or Beauveria bassiana (22.22%), or spraying of 10% lime (22.22%). Proper and timely management practices during cultivation and selection of borer resistant genotype seem beneficial for the coffee growers. Further, application of borer management practices based on abundance models are recommended to minimize the pest infestation.

Reconciling coffee productivity and natural vegetation conservation in an agroecosystem landscape in Brazil

Politicians have approved significant changes to the Brazilian Forest Code (Brazilian Law n. 12.651/2012), providing partial pardons for illegal deforestation in 2012. Nonetheless, the New Forest Code (NFC) may cause economic harm, since ecosystem services may be affected, and the productivity of several crops may end up decreasing. Here, we explored two sets of factors, one at a narrow-scale – the loss of close natural vegetation cover – and another at a wide-scale considering implications at a landscape level to measure the effects of the presence/absence of forest remnants, and consequently, of pollinators, on coffee productivity. The narrow-scale perspective used manipulative experiments in ten coffee plantations, and the wide-scale perspective considered secondary data on coffee productivity in planted and native forests of 61 municipalities to test the hypotheses: i) coffee branches with pollinator access are more productive; ii) coffee crops in contact with native forest remnants are more productive; iii) coffee plants located near to native forest remnants are more productive; iv) coffee productivity increases with the municipality area occupied by native forest remnants, and, v) coffee productivity decreases with the municipality area occupied by Eucalyptus spp. At the narrow-scale, we detected 32 % higher coffee productivity when pollinators were present (hypothesis i) and 15 % higher productivity when forest remnants were in contact with the plantation (hypothesis ii), but no differences related to forest remnants in the broader area (hypothesis iii). At the wide-scale, we observed that a higher amount of native forest cover increased coffee productivity (hypothesis iv), while increased Eucalyptus spp. plantations reduced coffee productivity (hypothesis v). The corroboration of hypotheses i, ii, and iv illustrates the importance of animal pollination and native vegetation remnants fr coffee productivity. The findings for hypothesis v reinforce that Eucalyptus spp. plantations are not good surrogates for native vegetation as part of management recovery action for deforested areas. Following the New Forest Code’s recommendations in Article 22 (Chapter IV, Section II), the preservation of native vegetation, species diversity, and native species regeneration should be attended to in legally instituted natural reserves. Our findings improve discernment that natural areas' devastation or its coverage using planted forest may reduce productivity levels of coffee plantations, representing a disruption of natural complexity, of organisms' connectivity, and consequently of ecosystem services as the pollination and pollinator-dependent crops' productivity, as the coffee.

The Effect of Shade Trees in the Coffee Ecosystem to the Population and Diurnal Activity of Insect Pollinators

Insect pollinators is one of the important factors in the cross-pollination of coffee flowers, which affects the coffee fruit set. However, there is still a limited understanding of how shade trees in the coffee ecosystem affect insect pollinators. The purpose of this study was to obtain information on the effect of climate variations at different shading levels in the coffee ecosystem to the population and diurnal activity of insect pollinators. The shade levels are categorized in three ways, namely high shade, low shade, and open shade. The observation was conducted at the time when the flower blooms with sample units a flower in two coffee branches. Insect pollinators that show feeding behavior in coffee flowers were recorded in the morning, while the diurnal activity of each species pollinator was observed in the morning, midday, and afternoon. The study showed five species of insects belonging to three families and two orders, Hymenoptera and Lepidoptera that showed feeding behavior on coffee flowers. Apis cerana and Apis mellifera were the dominant pollinators of coffee flowers. The difference in shade levels did not affect pollinator species to visit coffee flowers, but their population tends to decrease in the open shade, except Apis cerana. The peak of diurnal activity of insect pollinator recorded in the morning decreased at midday and showed an increase slightly in the afternoon until the end of the diurnal activity. An increase of temperature may significantly decrease the number of pollinators that visit coffee flowers, while humidity and light intensity showed no significant effect.

Effect of the impact of rigid rods on coffee fruit detachment efficiency by mechanical vibrations

The mechanization of field activities has been the response of coffee producers to the labor shortage, especially for fruit harvesting. The use of mechanical harvesters allows greater harvesting efficiency and ensures the economic viability of coffee plantations, which currently depend mainly on the reduction in production costs. The principle used for mechanized coffee harvesting is based on the principle of mechanical vibration. The objective of this studywas to analyze the dynamic behavior of the coffee fruit-peduncle-branch system under mechanical vibration and the impact of the vibrating rods on the fruit detachment process in association with this behavior. Fragments of coffee branches containing fruits in the unripe and ripe stages were used in this experiment. These samples were subjected to different frequencies (20, 30, 40, and 50 Hz) and amplitudes (0.002, 0.003, and 0.004 m). Another variableanalyzed was the form of vibration transmission to the fruits, with the vibrations being transmitted to the samples with or without the impact of the fiberglass rods. The fruit detachment efficiency increased as the ripening stage progressed from unripe to ripe. A higher detachment efficiency occurred with the increase in vibration frequency and amplitude because of the higher vibrational energy imposed on the fruit. The detachment efficiency was low when the vibration was transmitted without the impact of the rods. Conversely, the vibration in combination with impact achieved a mean detachment efficiency of approximately 90%.Key words: Coffee crop; dynamic behavior; harvester machine; mechanical harvesting.

Starch accumulation does not lead to feedback photosynthetic downregulation in girdled coffee branches under varying source-to-sink ratios

Leaves were forced to accumulate starch as much as possible but maintained relatively low soluble sugar levels with no evidence of photosynthetic feedback downregulation. Here, we examined whether the regulation of photosynthesis in coffee depends on sink activity or carbohydrate build-up in source leaves and how the coffee tree adjusts its photosynthetic performance and primary metabolism to varying source-to-sink ratios. We designed a field experiment by girdling coffee branches that were further manipulated by controlled defoliation and/or defruiting such that three highly varying source-to-sink ratios were created. Under markedly high source-to-sink ratios, photosynthesis rates were primarily limited by diffusional factors, and feedback downregulation contributed a maximum of 7% of the photosynthetic reduction. Such responses were accompanied by a relatively enormous capacity for starch accumulation coupled with the maintenance of low levels of soluble sugars. Chronic photoinhibition and photodamage could be avoided by increases in nonphotochemical energy dissipation, photorespiration and respiration rates, thus diminishing the excitation pressure on photosystems. Overall, the activities of key enzymes (and their transcript abundance) associated with carbon metabolism varied only marginally across treatments. Leaf metabolic adjustments were more evident under high sink demand conditions, and nitrogen metabolism was more affected than carbon metabolism. In conclusion, our results offer novel insights into the high coordination between the source supply and sink demand in coffee, with a minor role of photosynthetic downregulation even under dramatically low sink conditions.

Comparative bioassay methods to determine diamide susceptibility for two coffee pests

Hypothenemus hampei Ferrari (Coleoptera: Curculionidae: Scolytinae) and Leucoptera coffeella Guérin-Méneville (Lepidoptera: Lyonetiidae) are major pests of coffee. Diamides, are a new group of insecticides that activate ryanodine receptors causing muscle contraction, and have been used to control H. hampei and L. coffeella. Bioassay methods need to be standardized for insecticide susceptibility studies on H. hampei with cyantraniliprole and L. coffeella with chlorantraniliprole. Four bioassay methods for H. hampei (topical application with a microsyringe, artificial diet, immersion of green coffee fruits in insecticide solution, and coffee branch bagging) and five for L. coffeella (spraying coffee seedlings, immersion of coffee leaves, immersion of filter paper and topical application with microsyringe were evaluated. The best performing method was selected based on the greater slope (β) of the probit curve, lower LC50, lower natural mortality in the control, and lower variance. The results showed that the best methods for bioassays were the artificial diet for H. hampei and spraying of coffee seedlings for L. coffeella.

Field sampling strategies for coffee berry borer (Coleoptera: Curculionidae: Scolytinae) infesting berries in coffee farms in Hawaii

AbstractThe coffee berry borer (CBB),Hypothenemus hampeiFerrari, a recent invader to Hawaii, is impacting coffee growers by reducing yields and quality and increasing production costs. Monitoring strategies are needed to assess infestations and where control operations are warranted, and evaluate their effectiveness. To develop and validate a fixed-precision sequential sampling plan, an intensive CBB sampling programme was conducted in 17 small farms in Kona and Kau districts in the Big Island in 2016/17. At each location, 30 trees/ha were monitored at 2–4 week intervals. Results show that the CBB has an aggregated spatial distribution based on Taylor's power law parameters. According to Green's stop line formula, between 6 and 50 coffee branches per ha (sample unit) are required to estimate infestation rates of 1.5–2.5% infested green berries (suggested economic threshold) with a precision fixed at 10 to 25%. Concurrently, a modified strategy was tested on 14 farms, in which only infested green berries (not total) was counted. The standard and modified sampling methods were highly correlated (R2≥ 0.98), while the modified approach required on average only 35 min (27% less time) to complete, with an additional 24 min taken to observe the position of the CBB inside the berry. Our data also show that berry infestation rates of CBB prior to harvest were a good predictor of the total defects resulting in processed green coffee from these farms (Pearson'srcoefficient of 0.82). Our findings support improved sampling for the CBB under Hawaiian conditions using a simpler and faster monitoring strategy based on counting green infested berries.

Evaluation of the interaction between a harvester rod and a coffee branch based on finite element analysis

The validation of agricultural mechanization issues often involves experimental tests. However, with the increase of computers processing capacity, numerical analysis became common in agricultural applications, which reduces costs for prototyping. The use of Finite Element Analysis (FEA) in new applications, the improvement of the existing models, together with a constant computers development can contribute significantly for the cost reduction in the agricultural industry. This work aimed to evaluate the interaction between a harvester rod and a coffee branch by using computational modeling via FEA. In order to perform dynamic simulations, three-dimensional models from a plagiotropic branch of a coffee tree and a harvester rod were obtained. In addition, samples from plagiotropic coffee branches were tested. The tests were supported by an accelerometer installed in the coffee branches in order to provide acceleration signals for FEA model validation. Results indicated that accelerations obtained from simulations were 3.14% higher than experiments, simulated displacements were 23.2% lower than experiments and simulated Von Mises stresses were close to values from the literature. This showed FEA potentiality for agricultural applications taking in consideration the interaction between machines and plants.

Measurement of the ripening rate on coffee branches by using 3D images in outdoor environments

In this article, a method for determination of the ripening rate of coffee branches is presented. This is achieved through analysis of 3D information obtained with a monocular camera in outdoor environments and under uncontrolled lighting, contrast, and occlusion conditions. This study was performed on 30 coffee branches, monitored throughout the entire harvest season, at each of nine collection times, directly in the countryside. On each branch checked, the fruit was counted in three maturation stages: unripe, semi-ripe and ripe. Subsequently, the real ripeness percentage was computed for each stage of development. Images were acquired from the same manually checked branches, and the developed algorithm was run. This algorithm performs a reconstruction producing a point cloud, employing Structure from Motion (SfM). In all, 17 features were selected to describe the three maturation stages, leaves, and stem. These features were calculated in a region proportional to the size of the point cloud. The 3D structures of the coffee fruits on the branch were obtained and classified, with between 42% and 92% of correct classification percentage for the unripe, semi-ripe, and ripe developmental stages, and the best classification model was selected, with a neighborhood that was 6.5% of the total size of the point cloud. A statistical estimation model was constructed for each stage of development, and it was found that the model overestimates the percentage of ripe fruit, underestimates that of semi-ripe fruit, and the unripe fruit estimate is one to one. The errors in estimation were between 3.7% and 8.7%. Correlation was between 0.64 and 0.98. Finally, temporary monitoring was performed for the ripening of coffee branches during the harvest season, with nine collection times. A maturation index was determined, with which the state of a branch as ready or not for harvest was correctly determined with 83% efficiency.