scholarly journals Drone-Based Participatory Mapping: Examining Local Agricultural Knowledge in the Galapagos

Drones ◽  
2020 ◽  
Vol 4 (4) ◽  
pp. 62
Author(s):  
Mia Colloredo-Mansfeld ◽  
Francisco J. Laso ◽  
Javier Arce-Nazario
Keyword(s):  
Management Strategies ◽  
Agricultural Practices ◽  
Invasive Species Management ◽  
Farming Practices ◽  
Spatial And Temporal Scales ◽  
Agricultural Knowledge ◽  
High Resolution Imagery ◽  
Aerial Vehicle ◽  
Uav Images ◽  
On Farm

Agriculture is cultural heritage, and studies of agricultural spaces and practices help this heritage to be valued and protected. In the Galapagos Islands, little focus has been placed on local agricultural practices and agroforestry, despite their increasing importance for food security and invasive species management. This article discusses the possibilities for unoccupied aerial vehicle (UAV) high-resolution imagery in examining agricultural and agroforestry spaces, techniques, and practices. It describes and assesses an UAV-assisted participatory methodology for on-farm qualitative research that aims to investigate the visible and invisible features of farming practices. An analysis of the types of responses elicited by different methods of interviews with Galapagos farmers demonstrates how incorporating UAV data affects what we took away from the interview, and how the perceived relationship between farmer and land is reflected. Specifically, we find that when interacting with orthomosaics created from UAV images of their farms, farmers’ responses reveal a greater focus on management strategies at larger spatial and temporal scales. UAV imagery thus supports studies of agricultural heritage not only by recording agricultural spaces but also by revealing agrarian knowledge and practices.

scholarly journals Socioecological Factors and Farmer Perceptions Impacting Pesticide Use and Pollinator Conservation on Cucurbit Farms

2021 ◽  
Vol 5 ◽  
Author(s):  
Elias H. Bloom ◽  
Dana Marie Bauer ◽  
Abigail Kaminski ◽  
Ian Kaplan ◽  
Zsofia Szendrei
Keyword(s):  
Habitat Restoration ◽  
Pesticide Exposure ◽  
Management Strategies ◽  
Agricultural Practices ◽  
Farming System ◽  
Farm Size ◽  
Pollinator Decline ◽  
Farmer Perceptions ◽  
On Farm ◽  
Pollinator Declines

While research suggests that pollinator decline is linked with agricultural practices, it is unclear whether farmers share this view and adapt management to promote pollinators based on their understanding of these threats. To address these issues, we surveyed farmers of pollinator-dependent cucurbit crops across four states in the Midwest, USA. We grouped farmers by their perceptions of pollinator declines and routes of pesticide exposure and used statistical models to evaluate if farmers manage pests and pollinators based on these perceptions. Out of 93 completed surveys, 39% of farmers believed pollinators were in decline. When grouped, 17% of farmers were classified as proponents, ranking (on a 1–5 Likert scale) the factors mediating pesticide exposure and pollinator declines as important or highly important. For comparison, 44 and 39% of farmers were classified as neutral or skeptical, respectively, of these same factors. Compared to the neutral and skeptic groups, proponents were on average younger, had fewer years farming but more years in family farming, and were more dependent on income from outside the farming system. Proponents also on average reported smaller farms, higher pest richness, more land in cucurbit production, and greater richness of crops that are not pollinator dependent, when compared to the neutrals and skeptics. We did not find pest and pollinator management to be related to farmer perceptions of pollinator decline or routes of pesticide exposure, but farmers classified as pollinator “proponents” were more likely to indicate participation in future pollinator habitat restoration programs. Rather, management strategies were better explained by on-farm environmental conditions (e.g., pest richness, farm size, number of pollinator dependent crops) and economic factors (e.g., sources of income). Generally, our research shows that farmers who perceive pollinator threats may not be using pollinator supportive practices. Thus, while some farmers believe in pollinator declines, there remains a need to connect this knowledge with on-farm practices.

scholarly journals New Research about Educational Activity Scientists-Agrarians

2020 ◽  
Vol 20 (3) ◽  
pp. 416-420
Author(s):  
Petr S. Kabytov ◽  
◽  
Ekaterina P. Barinova ◽  
Keyword(s):  
Agricultural Education ◽  
Significant Contribution ◽  
Agricultural Practices ◽  
Russian Empire ◽  
Educational Activity ◽  
Farming Practices ◽  
Agrarian Sector ◽  
Agricultural Knowledge ◽  
The Russian Empire ◽  
New Research

The review gave an analysis of the monograph of S. A. Kozlov, which presented the reconstruction of biographies of prominent Russian scientists, having made a significant contribution to the development and implementation of new agricultural practices and sustainable farming practices, and also in promotion of scientific knowledge and creation of a system of agricultural education in the Russian Empire in XIX and early XX of centuries. Features of author’s approach, the importance of the research done by the historian are noted, debatable questions are designated. According to reviewers, S. A. Kozlov ‘s monograph through biographies of agricultural scientists shows the panorama of the development of agricultural knowledge in the Russian Empire and their impact on the agrarian sector of the economy of the country.

scholarly journals Socioeconomic benefits of conserving Iran’s water resources through modifying agricultural practices and water management strategies

AMBIO ◽  
2021 ◽  
Author(s):  
Fatemeh Karandish
Keyword(s):  
Water Consumption ◽  
Water Scarcity ◽  
Management Strategies ◽  
Agricultural Practices ◽  
Consumption Pattern ◽  
Blue Water ◽  
Management Scenarios ◽  
Current Consumption ◽  
The Status ◽  
On Farm

AbstractSustainable development requires modifying the current consumption pattern of natural resources. This study investigates efficient tactics for reducing the unsustainability and inefficiency of human’s food-related blue water consumption alongside improving national environmental and socioeconomic status. As a case study for Iran, 15 alternative management scenarios (AMS) were defined compared to the current on-farm management, and their effects were assessed on a monthly scale. Based on the results, 45.5 billion m3 y−1 (BCM) blue water is consumed within the croplands, 78% and 34% of which are unsustainable and inefficient, respectively. AMCs reduces the unsustainable and inefficient blue water consumption by 2–17 BCM and 2–13 BCM, respectively. The combination of yield gap closure, drip irrigation, soil mulching, and deficit irrigation has the largest effect on blue water saving; it releases or changes the status of monthly blue water scarcity in 11 provinces; increases field-employees by 132%, food security by 9%, international food-export by 87%, and gross domestic production by 54%. However, it doesn’t fully address blue water overconsumption in the summer period; hence, further measures are needed to reduce blue water scarcity to the sustainable level in these environmental hotspots.

scholarly journals 3D Characterization of Sorghum Panicles Using a 3D Point Cloud Derived from UAV Imagery

2021 ◽  
Vol 13 (2) ◽  
pp. 282
Author(s):  
Anjin Chang ◽  
Jinha Jung ◽  
Junho Yeom ◽  
Juan Landivar
Keyword(s):  
Point Cloud ◽  
3D Point Cloud ◽  
Panicle Length ◽  
Color Ratio ◽  
High Resolution Imagery ◽  
Aerial Vehicle ◽  
Highly Correlated ◽  
Uav Images ◽  
Panicle Weight ◽  
Cylinder Fitting

Sorghum is one of the most important crops worldwide. An accurate and efficient high-throughput phenotyping method for individual sorghum panicles is needed for assessing genetic diversity, variety selection, and yield estimation. High-resolution imagery acquired using an unmanned aerial vehicle (UAV) provides a high-density 3D point cloud with color information. In this study, we developed a detecting and characterizing method for individual sorghum panicles using a 3D point cloud derived from UAV images. The RGB color ratio was used to filter non-panicle points out and select potential panicle points. Individual sorghum panicles were detected using the concept of tree identification. Panicle length and width were determined from potential panicle points. We proposed cylinder fitting and disk stacking to estimate individual panicle volumes, which are directly related to yield. The results showed that the correlation coefficient of the average panicle length and width between the UAV-based and ground measurements were 0.61 and 0.83, respectively. The UAV-derived panicle length and diameter were more highly correlated with the panicle weight than ground measurements. The cylinder fitting and disk stacking yielded R2 values of 0.77 and 0.67 with the actual panicle weight, respectively. The experimental results showed that the 3D point cloud derived from UAV imagery can provide reliable and consistent individual sorghum panicle parameters, which were highly correlated with ground measurements of panicle weight.

Addressing on-farm management to enhance pasture productivity and persistence

2013 ◽  
pp. 241-244
Author(s):  
W.N. Reynolds
Keyword(s):  
Management Strategies ◽  
Dairy Farm ◽  
Stocking Rate ◽  
Pasture Management ◽  
Pasture Production ◽  
Operating Profit ◽  
The North ◽  
The Cost ◽  
On Farm ◽  
Attention To Detail

Following the 2007/08 drought, we experienced poor pasture production and persistence on our dairy farm in north Waikato, leading to decreased milksolids production and a greater reliance on bought-in feed. It is estimated that the cost of this to our farming operation was about $1300 per hectare per year in lost operating profit. While climate and black beetle were factors, they did not explain everything, and other factors were also involved. In the last 3 years we have changed our management strategies to better withstand dry summers, the catalyst for which was becoming the DairyNZ Pasture Improvement Focus Farm for the north Waikato. The major changes we made were to reduce stocking rate, actively manage pastures in summer to reduce over-grazing, and pay more attention to detail in our pasture renewal programme. To date the result has been a reduced need for pasture renewal, a lift in whole farm performance and increased profitability. Keywords: Focus farm, over-grazing, pasture management, pasture persistence, profitability

Agricultural practices of improve hardiness a winter-annual rape

2016 ◽  
Vol 2 (91) ◽  
pp. 57-62
Author(s):  
O.L. Kyrylesko
Keyword(s):  
Dry Matter ◽  
Agricultural Practices ◽  
Mineral Fertilizers ◽  
Farming Practices ◽  
Winter Rape ◽  
Output Capacity ◽  
Careful Preparation ◽  
Digestible Protein ◽  
Winter Annual ◽  
Selection Of

Influence of top-dressing is considered in the article, norms and terms of sowing on of winter-annual rape. The assessment conducted by the yield of green mass and seeds, output capacity by about 1 hectare of dry matter, feed units and digestible protein, the number of dead plants and density of herbage. Established that hardiness and productivity of winter rape can be enhanced through the use of farming practices as: by creating a moderate density of herbage, using optimal terms of planting and doses of mineral fertilizers, selection of predecessors and careful preparation of the soil ect. The mechanism of influence of agrotechnical receptions is exposed on of winter-annual rape through determination in roots before the offensive of the winter of separate biochemical indexes (sugar, starch, to protein).

scholarly journals Identifying the Branch of Kiwifruit Based on Unmanned Aerial Vehicle (UAV) Images Using Deep Learning Method

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4442
Author(s):  
Zijie Niu ◽  
Juntao Deng ◽  
Xu Zhang ◽  
Jun Zhang ◽  
Shijia Pan ◽  
...  
Keyword(s):  
Deep Learning ◽  
Unmanned Aerial Vehicle ◽  
Semantic Segmentation ◽  
Dynamic Monitoring ◽  
Support Vector ◽  
Distribution Maps ◽  
Time Operation ◽  
Aerial Vehicle ◽  
Uav Images ◽  
Segmentation Image

It is important to obtain accurate information about kiwifruit vines to monitoring their physiological states and undertake precise orchard operations. However, because vines are small and cling to trellises, and have branches laying on the ground, numerous challenges exist in the acquisition of accurate data for kiwifruit vines. In this paper, a kiwifruit canopy distribution prediction model is proposed on the basis of low-altitude unmanned aerial vehicle (UAV) images and deep learning techniques. First, the location of the kiwifruit plants and vine distribution are extracted from high-precision images collected by UAV. The canopy gradient distribution maps with different noise reduction and distribution effects are generated by modifying the threshold and sampling size using the resampling normalization method. The results showed that the accuracies of the vine segmentation using PSPnet, support vector machine, and random forest classification were 71.2%, 85.8%, and 75.26%, respectively. However, the segmentation image obtained using depth semantic segmentation had a higher signal-to-noise ratio and was closer to the real situation. The average intersection over union of the deep semantic segmentation was more than or equal to 80% in distribution maps, whereas, in traditional machine learning, the average intersection was between 20% and 60%. This indicates the proposed model can quickly extract the vine distribution and plant position, and is thus able to perform dynamic monitoring of orchards to provide real-time operation guidance.

scholarly journals Reference Measurements in Developing UAV Systems for Detecting Pests, Weeds, and Diseases

2021 ◽  
Vol 13 (7) ◽  
pp. 1238
Author(s):  
Jere Kaivosoja ◽  
Juho Hautsalo ◽  
Jaakko Heikkinen ◽  
Lea Hiltunen ◽  
Pentti Ruuttunen ◽  
...  
Keyword(s):  
Reference Data ◽  
Measurement Techniques ◽  
Synthetic Data ◽  
Ground Truth ◽  
Precision Farming ◽  
Aerial Imaging ◽  
Aerial Vehicle ◽  
Uav Images ◽  
Reference Measurements

The development of UAV (unmanned aerial vehicle) imaging technologies for precision farming applications is rapid, and new studies are published frequently. In cases where measurements are based on aerial imaging, there is the need to have ground truth or reference data in order to develop reliable applications. However, in several precision farming use cases such as pests, weeds, and diseases detection, the reference data can be subjective or relatively difficult to capture. Furthermore, the collection of reference data is usually laborious and time consuming. It also appears that it is difficult to develop generalisable solutions for these areas. This review studies previous research related to pests, weeds, and diseases detection and mapping using UAV imaging in the precision farming context, underpinning the applied reference measurement techniques. The majority of the reviewed studies utilised subjective visual observations of UAV images, and only a few applied in situ measurements. The conclusion of the review is that there is a lack of quantitative and repeatable reference data measurement solutions in the areas of mapping pests, weeds, and diseases. In addition, the results that the studies present should be reflected in the applied references. An option in the future approach could be the use of synthetic data as reference.

scholarly journals Application of Nematode Community Analyses-Based Models towards Identifying Sustainable Soil Health Management Outcomes: A Review of the Concepts

Soil Systems ◽  
2021 ◽  
Vol 5 (2) ◽  
pp. 32
Author(s):  
Haddish Melakeberhan ◽  
Gregory Bonito ◽  
Alexandra N. Kravchenko
Keyword(s):  
Nutrient Cycling ◽  
Health Management ◽  
Management Strategies ◽  
Soil Health ◽  
Agricultural Practices ◽  
Nematode Community ◽  
Parasitic Nematodes ◽  
Worst Case ◽  
Pests And Diseases ◽  
Water Holding

Soil health connotes the balance of biological, physicochemical, nutritional, structural, and water-holding components necessary to sustain plant productivity. Despite a substantial knowledge base, achieving sustainable soil health remains a goal because it is difficult to simultaneously: (i) improve soil structure, physicochemistry, water-holding capacity, and nutrient cycling; (ii) suppress pests and diseases while increasing beneficial organisms; and (iii) improve biological functioning leading to improved biomass/crop yield. The objectives of this review are (a) to identify agricultural practices (APs) driving soil health degradations and barriers to developing sustainable soil health, and (b) to describe how the nematode community analyses-based soil food web (SFW) and fertilizer use efficiency (FUE) data visualization models can be used towards developing sustainable soil health. The SFW model considers changes in beneficial nematode population dynamics relative to food and reproduction (enrichment index, EI; y-axis) and resistance to disturbance (structure index, SI; x-axis) in order to identify best-to-worst case scenarios for nutrient cycling and agroecosystem suitability of AP-driven outcomes. The FUE model visualizes associations between beneficial and plant-parasitic nematodes (x-axis) and ecosystem services (e.g., yield or nutrients, y-axis). The x-y relationship identifies best-to-worst case scenarios of the outcomes for sustainability. Both models can serve as platforms towards developing integrated and sustainable soil health management strategies on a location-specific or a one-size-fits-all basis. Future improvements for increased implementation of these models are discussed.

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