Planting Research Articles

Habitat Associated with Ramps/Wild Leeks (Allium tricoccum Ait.) in Pennsylvania, USA: Guidance for Forest Farming Site Selection

Ramps or wild leeks (Allium tricoccum) are a popular foraged non-timber forest product in North America consumed for their edible bulbs and leaves. The agroforestry practice of forest farming is a possible solution to conservation challenges surrounding the wild exploitation of this species, but it requires proper site selection to be successful. In this study, maximum entropy (Maxent) modeling using 163 occurrence points and field data collected at 30 wild populations were combined to determine the characteristics of the ramp habitat in Pennsylvania. Both Maxent modeling and field measurements highlighted moist, lower slope positions with base-rich bedrock types as suitable for ramps. Sites shared 50% of their floristic associates on average, with 252 species documented in total. Forest communities associated with ramps included many species indicative of base-rich mesic soil conditions, but the relative abundance of some indicator species differed by region. The confirmation of model variables by field measurements and forest community types points to the usefulness of these characteristics in identifying suitable forest farming sites. When used in tandem, these results can help to guide site selection for forest farming and other conservation strategies.

Application of Spectral Imaging and Vegetation Index in Latin American Coffee Production: A Systematic Mapping

ABSTRACTCoffee production is a crucial economic, social, and cultural pillar in Latin America, facing numerous challenges, including integrating technological advancements such as multispectral imaging. This approach offers multiple advantages for coffee production; however, a knowledge gap in the domain is the need to methodologically review the available empirical evidence to delineate the field and the study region. Therefore, this systematic mapping aims to map the scientific corpus of multispectral imagery and vegetation index implemented in coffee production in the Latin American region. The study followed the PRISMA protocol; 42 primary studies were analyzed to identify key trends and research gaps. The main result of this research is that NDVI emerged as the most widely used spectral index, with applications in estimating critical biophysical parameters such as biomass and chlorophyll content. Other indices such as GNDVI, NDRE, and SAVI also proved valuable in assessing coffee plant health and development. There was an emerging trend to integrate multispectral imaging with machine learning techniques, promising greater accuracy in data interpretation. The study also revealed a concentration of research efforts in selected Latin American countries, particularly Brazil, indicating opportunities to expand research in other coffee‐producing regions. The study's main conclusion is that multispectral imaging, mainly through vegetation index, has emerged as a valuable tool for phenological monitoring and management of coffee production, offering several advantages over traditional methods. Finally, this review contributes to the existing knowledge base and identifies future research directions for applying multispectral imagery to sustainable coffee production in Latin America.

Estimating coffee crop parameters through multispectral imaging and machine learning algorithms

Abstract. Brazil plays a crucial role in the global economy due to its significant contribution to the agricultural sector, particularly in coffee production, where it stands out as the largest producer and exporter of processed coffee. Various disturbances can influence coffee plants, causing abnormalities that can hinder their successful growth. Parameters such as plant height and canopy diameter play an essential role in assessing the health and productivity of the plants, reflecting their growth, development, and ability to capture sunlight. Additionally, height is also related to the balanced distribution of nutrients and water, providing valuable information about overall performance and the capacity for healthy production. In this regard, the application of methodologies involving remote sensing and machine learning algorithms has shown promising results in the rapid and safe acquisition of information about agricultural systems. This study evaluates different machine learning algorithms, using radiometric values from multispectral images obtained by remote sensing platforms as input datasets for estimating plant height and canopy diameter in coffee cultivation. The best performance was observed for architectures that showed lower RMSE and RMSE% values. For the plant height parameter (m), the RGB sensor exhibited the best performance using the Random Tree algorithm, with an RMSE (0.27) and RMSE% (8.80). For the canopy diameter (m), the sensor showed the best performance using the Random Forest algorithm, with an RMSE (0.15) and RMSE% (8.16).

Changes in the population and diversity of plant parasitic nematodes and their effects on sugarcane growth at Wonji‐Shoa Sugar Estate, Ethiopia

AbstractIn Wonji‐Shoa Sugar Estate (WSSE), sugarcane (Saccharum spp. hybrid) yields have declined by about 48% over the last 70 years. One of the causes for the decline is assumed to be the long‐term monoculture production system that results in the buildup of plant parasitic nematodes (PPNs). Therefore, the population and diversity of PPNs were investigated by conducting soil sampling using a biosequential method (simultaneous sampling of the soils of adjacent cultivated land [CL] and uncultivated land [UL]) and a chronosequential method (taking soil samples at different times from the same site). The samples were subjected to analysis using standard procedures to determine the change in the population, and identify the genera of PPNs. Additionally, a pot experiment that involved fumigation was conducted on top soils sampled from the CL and UL of the plantation. The results revealed that about 10 genera of PPNs (Meloidogyne, Helicotylenchus, Hoplolaimus, Rotylenchulus, Hemicycliophora, Discriconemella, Xhiphinema, Pratylenchus, Tylenchorhynchus, and Scutellonema) were detected, of which the first four were newly identified. The population density and the number of genera of PPNs found in the CL were 36‐fold and 4.5‐fold higher than those found in the UL, respectively. Furthermore, fumigation reduced the population of the PPNs by 61% and increased production of cane biomass by 63%. It is concluded that the soils of the WSSE are infested by PPNs, which consequently have detrimental effects on sugarcane growth. While amending soil fertility is crucial, reversing the decline in sugarcane yields also necessitates implementing an integrated soil management system that includes PPNs.

Economic Viability of Coffee Plants Cultivated in Agroforestry Systems in Southwest Goiás

Brazil is the world's leading coffee producer. Increased productivity has been observed in recent harvests due to new management and automation technologies. Even with the expectation of a reduction in national production, the state of Goiás has shown an increasing share in coffee production. The municipality of Rio Verde, in Goiás, is among the eight largest coffee producers in the state and is where the Fazenda da Mata enterprise, the main object of this research, is located. The objective of the research is to evaluate the performance of the production of Arabica coffee grown in an agroforestry system through studies on economic feasibility comparing the implementation costs plus the estimated costs and revenues of AFS with the conventional cultivation system. Coffee growing in AFS is a production system that requires research that presents results on economic analysis, thus the aim was to research the economic feasibility of growing coffee in AFS as a sustainable alternative for agribusiness, whose information can contribute to the decision-making of rural managers when comparing a conventional cultivation enterprise to AFS cultivation. Furthermore, AFS can contribute to increased agricultural productivity with less impact on the environment, revealing several possibilities of subsystems that can be applied to large, medium and small rural properties, considering the financial advantages and also the motivating values ​​that direct the farmer towards this agricultural activity. The economic analysis showed that the conventional cultivation system is more advantageous financially, however AFS also presented excellent results. Therefore, it is important to highlight other relevant factors that can be considered when deciding which cultivation system to use in coffee production. Although AFS presented lower financial results than the conventional system, it is a cultivation system that can provide a second source of income for the producer, such as the use of tree species.

Kawasan Konservasi Mangrove sebagai Penggerak Ekonomi Masyarakat Desa Budeng Kabupaten Jembrana Bali

Budeng Village, located in Jembrana Regency, is home to a significant mangrove conservation area featuring 32 species of mangroves with substantial potential for utilization. Conservation activities in this region are led by the Wana Merta Group, which aims to engage the local community of Budeng Village in these deeds. However, the residents have yet to show much interest due to the lack of perceived economic benefits from conservation activities. The purpose of the community service activities conducted in Budeng Village is to enhance the knowledge and skills of the community in transforming mangroves into economically valuable enterprises. These activities comprised three stages: technical guidance, training sessions, and questionnaire distribution. The activities were attended by 15 participants from the Wana Mertha Forest Farmer Group (KTH), which manages the mangrove conservation area in Budeng Village. The technical guidance included institutional strengthening materials for the group. The training sessions covered topics such as mangrove product diversification, processing Brugueira sp. into mangrove chips, processing Xylocarpus granatum into scrubs, processing shrimp and fish into siomay, as well as packaging and digital marketing to support the group's business endeavors. Throughout the technical guidance and training, participants actively engaged in discussions and followed the sessions diligently. The questionnaire results indicated a significant increase in participants' knowledge, from 40% to 73.76%, reflecting an improvement of 34.67% after the activities.

Rekayasa Teknik Guludan sebagai Upaya Rehabilitasi Ekosistem Mangrove di Ekowisata Pantai Alam Serdang Bahari, Pantai Labu, Sumatera Utara

Abrasion at Alam Serdang Bahari Beach (ASB) is increasingly worrying, causing the reduction of mangrove forests on the coast. ASB Beach is located in Regemuk Village, Labu Beach. The ASB Mangrove Forest Farmers Group (KTHM) has made many efforts to continue to exist morally and materially to survive in the ecotourism industry and is trying to re-green the beaches to minimize the impact of abrasion. The results of a field assessment involving lecturers, village officials, and KTHM ASB obtained a roadmap for a sustainable development village with a solution to prevent prolonged abrasion using the simplest and most economical way through engineered bund techniques to protect mangrove plants and also act as a wave breaker. Implementing this PKM aims to make new efforts to plant mangrove trees as coastal abrasion protection. Implementing activities uses a participatory action research (PAR) approach. KTHM, as the partner, carried out the construction of the bund enclosure, and the PKM team was the drafter and supervisor. The results of the PKM implementation are three plots of bunds in the shape of a ship's bow as an effort to break the beach waves using the Rhizopora sp. propagules collected from mangrove seeds by KTHM ASB. This innovation is still early to assess because it requires ongoing monitoring. It is hoped that this effort will better protect newly planted mangrove plants from fierce waves and abrasion as a joint effort to prevent abrasion on ASB Beach.

Development and Evaluation of a Variable-Rate Fertilizer Distribution System for Coffee Plants

Currently, Brazilian coffee farming seeks the rational use of resources through sustainable practices. As a result, the development of machinery with more efficient input application systems and the adoption of precision agriculture techniques have been yielding excellent results. This study was divided into two stages, with the first involving the adaptation of a solid fertilizer application machine with fixed doses, allowing dose variation using an electronic controller. The second stage consisted of conducting trials and their applications under operational conditions. The results confirmed that the developed system remained stable in terms of variable-rate fertilizer distribution for coffee cultivation. The machine’s lateral fertilizer distribution range met the demands of coffee farming satisfactorily. In field conditions, the developed system exhibited an average error of −2.9%, compared to the programmed doses, validating the accuracy of the machine and its suitability for use in coffee plantations.

Migration of Maharashtrians to Mauritius (1834-1968)

The present study is confined only to Marathi people, who migrated to Mauritius for the sake of employment economy in the sugar plantations. In this study, the mobility of the Marathi people to Sugar industries in Mauritius recruitment of Marathi workers their standard of wages and their relationship with the local people and authorities will be examined during the period. Nevertheless, their role in the socio-economic development and cultural transformation of the local society was quite significant. Therefore, their study highlights the specific nature and pattern of evolution of an immigrant community overseas. Their involvement and contribution to the socio- economic development and cultural assimilation of the host country need to be studied in detail.

ANALISIS RANTAI PASOK DAN RANCANG BANGUN SISTEM KETERTELUSURAN KOPI ROBUSTA BERBASIS ANDROID

Robusta coffee is the most widely cultivated coffee commodity in Indonesia. In the East Bolaang Mongondow Regency, the problem at the supplier level is limited market information, which makes the coffee beans' quality inconsistent, impacting the price and product quality image. This research aims to identify supply chain structure models and members, added value, and design a traceability system to support product quality validation. Robusta coffee supply chain participants and their interactions were identified at the Modayag coffee plantation in East Bolaang Mongondow. The data were collected through observations, interviews, and field studies. Supply chain analysis was performed using the Vorst method and the added value was calculated using the Hayami method. The traceability system design follows the system development lifecycle method. The findings indicate that the Robusta coffee supply chain in East Bolaang Mongondow Regency includes farmers, collector traders, processing plants, the retail industry, coffee roasteries, and consumers. Farmers profit from selling perfectly ripe wet coffee beans 42-43%, wet mixed coffee beans (8%), and dry mixed coffee beans 63-71%. A traceability system named Kinton was successfully developed and integrated with the Firebase database to store all information.

Sources and splitting of special fertilizers application in coffee crop

This study assesses special and mineral fertilizers and the splitting of fertilizer application in coffee - a crop with high nutritional requirements for full yield potential. A 4 × 3 factorial scheme was implemented with four fertilizers [mineral, mineral with polymer, organomineral with cellulosic residue (OM-CR), or sugarcane filter cake (OM-FC)] and three application times, or splits (100% at once, 50%+50%, 33.3%+33.3%+33.3%). Coffee plant height, canopy diameter, plagiotropic branch growth, leaf chlorophyll, nutrient contents in the soil and leaves, and harvest yield after fruit maturation were evaluated in two consecutive crop cycles. The results indicated that organomineral fertilizers performed similarly to other fertilizers regarding coffee leaf chlorophyll and plant height. Only one fertilizer application effectively increased canopy diameter in both crop cycles. In the first crop cycle, OM-FC and conventional mineral fertilizers were significantly better for coffee foliar N content. In contrast, in the second crop cycle, mineral-P, OM-CR, and OM-FC achieved satisfactory results with one fertilizer application, whereas conventional mineral fertilizer required three applications for superior results. There are no differences in leaf P content among different sources and frequencies of application. Still, mineral-P and OM-CR had better soil P content than the conventional mineral fertilizer. OM-CR required two applications to reach high levels of leaf K content, while other fertilizers achieved it with one application. Organomineral and protected mineral fertilizers performed similarly in both crop cycles, with two applications resulting in greater coffee yield in the second cycle, regardless of the fertilizer used.

Research on the Influencing Factors and Development Strategies of the Under-forest Economy in Heilongjiang Province

Abstract: To address issues such as the small scale of operations, low technological content, and opaque market information in the under-forest economy of Heilongjiang Province, this study employs descriptive statistics and multiple linear regression analysis methods based on 124 questionnaire responses from forest farmers in various cities and counties of Heilongjiang Province. The study explores the influencing factors of developing the under-forest economy in Heilongjiang Province. The results show that the number of family laborers, family wage income, forest product planting area, attention to forestry technology, and forestry bureau subsidies significantly impact the development of the under-forest economy. Factors such as forest product prices, product quality, the risk of unsold products, supply of production materials, and forest product cooperatives have a weaker influence on the development of the under-forest economy. Based on these influencing factors, relevant suggestions are proposed to promote the development of the under-forest economy, providing a more scientific theoretical basis for the development of the under-forest economy in Heilongjiang Province.

Soil- and Foliar-Applied Silicon and Nitrogen Supply Affect Nutrient Uptake, Allocation, and Stoichiometry in Arabica Coffee Plants

ABSTRACT Silicon (Si) application may affect the plant response to nitrogen (N), possibly by changing the uptake, concentration, and partitioning of nutrients in plant tissues; however, this has not yet been proven in Arabica coffee plants. The effects of Si application methods [no Si, soil-applied soluble Si (168 mg Si L−1), and foliar-applied soluble Si (two application of 2 mg Si plant−1)] and N levels (0 and 80 mg N L−1) on biomass production and partitioning and uptake, partitioning, and stoichiometry of nutrients and Si in young Arabica coffee plants grown under greenhouse conditions were evaluated. Nitrogen fertilization increased the biomass production and uptake of all nutrients; however, reduced the concentrations of K, Ca, Mg, S, Mn, and Si in the leaves, Si in the stems, and K, Mg, and S in the roots of coffee plants as a dilution effect. In the presence of N, soil-applied Si increased the concentrations of Zn in the leaves and Ca and Si in the stems, the uptake of K, S, and Si, and the Si:N ratio. Foliar-applied Si increased the concentrations of N, P, K, and Zn in the leaves and Ca and Si in the stems, as well as the total uptake of K and Si and the Si:N ratio in coffee plants, being more evident in the N fertilization presence. This study unraveled that, especially when it was soil-applied, Si altered the nutrient uptake, allocation, and stoichiometric ratios with N, with a consequent increase in biomass production of young coffee plants fertilized with N.

A Spatial Analysis of Coffee Plant Temperature and Its Relationship with Water Potential and Stomatal Conductance Using a Thermal Camera Embedded in a Remotely Piloted Aircraft

Coffee is a key agricultural product in national and international markets. Physiological parameters, such as plant growth indicators, can signal interruptions in these processes. This study aimed to characterize the temperature obtained by a thermal camera embedded in a remotely piloted aircraft (RPA) and evaluate its relationship with the water potential (WP) and stomatal conductance (gs) of an experimental coffee plantation using geostatistical techniques. The experiment was conducted at the Federal University of Lavras, Minas Gerais, Brazil. A rotary-wing RPA with an embedded thermal camera flew autonomously at a height of 10 m and speed of 10 m/s. Images were collected on 26 November 2019 (rainy season), and 11 August 2020 (dry season), between 9:30 am and 11:30 am. Data on gs and WP were collected in the field. The thermal images were processed using FLIR Tools 5.13, and temperature analysis and spatialization were undertaken using geostatistical tools and isocolor maps by Kriging interpolation in R 4.3.2 software. Field data were superimposed on final crop temperature maps using QuantumGIS version 3.10 software. The study found that with decreasing WP, stomatal closure and reduction in gs occurred, increasing the temperature due to water deficit. The temperature distribution maps identified areas of climatic variations indicating water deficit.

PENINGKATAN DAYA SAING KELOMPOK TANI MELALUI PEMANFAATAN TEKNOLOGI PERTANIAN

Indonesia is known as an agricultural region with a wide variety of agricultural and plantation commodities. Plantation commodities such as coffee plants are one of the superior products produced by farmers in Indonesia. Coffee plants grow in mountainous areas with relatively cold weather temperatures. Geographically, natural conditions support coffee plants to grow well even with limited technology. Community service activities aim to increase the competitiveness of coffee farmer groups through the application of technology. The community service activities were carried out in Mekarmanik Village, Cimenyan District, Bandung Regency, West Java Province. Service partner Tiwikrama Mukti Farmer Group is engaged in coffee plantations around Mekarmanik village. Coffee trees in this area are planted intercropped with rubber trees that grow on land owned by the PERHUTANI State-Owned Company. The method of implementing the service activities provides assistance with a set of grass cutting equipment and garden support equipment. This equipment can help farmers clean grass and weeds that often grow around the garden so that the growth of coffee plants can be better. In addition to providing agricultural equipment instruments, the service team provided simulations on the use of tools and counselling to farmer group partners regarding the market potential of coffee commodities. The results of community service activities in farmer groups after carrying out garden maintenance can increase coffee productivity. Coffee farmer groups also have a better understanding of coffee marketing circulation so that farmers obtain more optimal economic returns.

Analysis of the Biennial Productivity of Arabica Coffee with Google Earth Engine in the Northeast Region of São Paulo, Brazil

Numerous challenges are associated with the classification of satellite images of coffee plantations. The spectral similarity with other types of land use, variations in altitude, topography, production system (shaded and sun), and the change in spectral signature throughout the phenological cycle are examples that affect the process. This research investigates the influence of biennial Arabica coffee productivity on the accuracy of Landsat-8 image classification. The Google Earth Engine (GEE) platform and the Random Forest algorithm were used to process the annual and biennial mosaics of the Média Mogiana Region, São Paulo (Brazil), from 2017 to 2023. The parameters evaluated were the general hits of the seven classes of land use and coffee errors of commission and omission. It was found that the seasonality of the plant and its development phases were fundamental in the quality of coffee classification. The use of biennial mosaics, with Landsat-8 images, Brightness, Greenness, Wetness, SRTM data (elevation, aspect, slope), and LST data (Land Surface Temperature) also contributed to improving the process, generating a classification accuracy of 88.8% and reducing coffee omission errors to 22%.

A Coffee Plant Counting Method Based on Dual-Channel NMS and YOLOv9 Leveraging UAV Multispectral Imaging

Accurate coffee plant counting is a crucial metric for yield estimation and a key component of precision agriculture. While multispectral UAV technology provides more accurate crop growth data, the varying spectral characteristics of coffee plants across different phenological stages complicate automatic plant counting. This study compared the performance of mainstream YOLO models for coffee detection and segmentation, identifying YOLOv9 as the best-performing model, with it achieving high precision in both detection (P = 89.3%, mAP50 = 94.6%) and segmentation performance (P = 88.9%, mAP50 = 94.8%). Furthermore, we studied various spectral combinations from UAV data and found that RGB was most effective during the flowering stage, while RGN (Red, Green, Near-infrared) was more suitable for non-flowering periods. Based on these findings, we proposed an innovative dual-channel non-maximum suppression method (dual-channel NMS), which merges YOLOv9 detection results from both RGB and RGN data, leveraging the strengths of each spectral combination to enhance detection accuracy and achieving a final counting accuracy of 98.4%. This study highlights the importance of integrating UAV multispectral technology with deep learning for coffee detection and offers new insights for the implementation of precision agriculture.

Joint modeling of longitudinal and survival data for the evaluation of the impact of irrigation systems on the time until the occurrence of phoma leaf spot in Arabica coffee plants.

The coffee crop is prominent in Brazilian agriculture, making the country a global power in this area. One of the main concerns in the coffee sector is disease, which can affect coffee productivity and quality. Thus, it is important to evaluate the factors that may affect coffee quality and thus enhance the development of strategies to reduce coffee losses and costs and optimize production. This study evaluated the influence of the type of irrigation (self-propelled, drip, and center pivot) on the time until the occurrence of phoma leaf spot on Arabica coffee plants, considering the intensity of the disease. Additionally, the association between longitudinal incidence and the time until an event of interest was assessed based on the joint modeling of longitudinal and survival data. The results of this study identify the effectiveness of drip irrigation system compared with other systems; the use of such systems was associated with an ~46.5% reduction in the risk of leaf spot disease compared with the use of a self-propelled irrigation system. The use of a center pivot system increased the risk of disease progression compared with a self-propelled system. An association between the longitudinal and survival processes was also observed. The findings demonstrate the superior performance of the drip irrigation system in controlling phoma leaf spot disease in Arabica coffee plants compared with self-propelled and center pivot systems. This research highlights the potential of using drip irrigation to establish more effective agricultural practices in coffee cultivation, contributing to better disease management and improved crop quality. © 2024 Society of Chemical Industry.

A comparison of CNN and SVM algorithms for the prediction of growth defects in coffee plants for stable yield and fungal diseases

A comparison of CNN and SVM algorithms for the prediction of growth defects in coffee plants for stable yield and fungal diseases

DAYA SAING KOPI ARABIKA DI MASA PANDEMI

During the COVID-19 pandemic, most of the export-oriented Arabica coffee plantations experienced production and productivity constraints due to decreased maintenance costs; besides, export opportunities were constrained by regulations issued by several countries requiring the product to be sterile from the COVID-19 virus. export. Based on the above phenomenon, this study aims to analyze the impact of the COVID-19 pandemic on Arabica coffee agribusiness, especially the profitability and competitiveness of Arabica coffee during the pandemic. The method used to select the area is the production center area around Mount Ijen, the Ijen Ring Region. The research is descriptive, combined research (mixed methods), and the method of collecting data uses primary and secondary data, as well as purposive sampling and incidental sampling with observation and interviews. The analysis tool uses competitiveness and policy with PAM (Policy Analysis Matrix). Arabica coffee during the pandemic is still profitable both financially (privately) and economically (socially), has great competitiveness and export opportunities, and is indicated to be able to compete with similar commodities, both imported and domestic products.