Precision farming or precision agriculture is an agricultural concept relying on the existence of in-field variability. It requires the use of new technologies, such as global positioning (GPS), sensors, satellites or aerial images, and information management tools (GIS) to assess and understand variations. Collected information may be used to more precisely evaluate optimum sowing density, estimate fertilizers and other inputs needs, and to more accurately predict crop yields. It seeks to avoid applying inflexible practices to a crop, regardless of local soil/climate conditions, and may help to better assess local situations of disease or lodging.
Satellites allow farmers to easily survey their land.[2] Global Positioning Systems (GPS) monitor can find the location of a field to within one meter. It can then present a series of GIS maps that demonstrate which fields are moist or dry, and where there is erosion of soil and other soil factors that stunt crop growth. The data can be used by the farmer to automatically regulate the machine application of fertilizer and pesticide[2].
In the American Midwest (US) it is associated not with sustainable agriculture but with mainstream farmers who are trying to maximize profits by spending money only in areas that need fertilizer. This practice allows the farmer to vary the rate of fertilizer across the field according to the need identified by GPS guided Grid Sampling. Fertilizer that would have been spread in areas that don't need it can be placed in areas that do, thereby optimizing its use.
Precision farming may be used to improve a field or a farm management from several perspectives:
* agronomical perspective: adjustment of cultural practices to take into account the real needs of the crop (e.g., better fertilization management)
* technical perspective: better time management at the farm level (e.g. planning of agricultural activity)
* environmental perspective: reduction of agricultural impacts (better estimation of crop nitrogen needs implying limitation of nitrogen run-off)
* economical perspective: increase of the output and/or reduction of the input, increase of efficiency (e.g., lower cost of nitrogen fertilization practice)
* geostatistics
* integrated farming
* Integrated Pest Management
* nutrient budgeting
* nutrient management
* precision viticulture
* Agriculture
* Landsat program
Geostatistics is a branch of statistics focusing on spatiotemporal datasets. Developed originally to predict probable distributions for mining operations, it is currently applied in diverse disciplines including petroleum geology, hydrogeology, hydrology, meteorology, oceanography, geochemistry, geometallurgy, geography, forestry, environmental control, landscape ecology, soil science, and agriculture (esp. in precision farming). Geostatistics is applied in varied branches of geography, particularly those involving the spread of disease (epidemiology), the practice of commerce and military planning (logistics), and the development of efficient spatial networks. Geostatistics are incorporated in tools such as geographic information systems (GIS) and digital elevation models.
This section requires expansion with: details.
When any phenomena is measured, the observation methodology will dictate the accuracy of subsequent analysis; in geography, this issue is complicated by unique variables and spatial patterns such as geospatial topology. An interesting feature in geostatistics is that every location displays some form of spatial pattern, whether in the form of the environment, climate, pollution, urbanization or human health. This is not to state that all variables are spatially dependent, simply that variables are incapable of measurement separate from their surroundings, such that there can be no perfect control population. Whether the study is concerned with the nature of traffic patterns in an urban core, or with the analysis of weather patterns over the Pacific, there are always variables which escape measurement; this is determined directly by the scale and distribution of the data collection, or survey, and its methodology. Limitations in data collection make it impossible to make a direct measure of continuous spatial data without inferring probabilities, some of these probability functions are applied to create an interpolation surface - predicting unmeasured variables at innumerable locations.
* Regionalized variable theory
* Covariance function
* Semi-variance
* Variogram
* Kriging
* Range (geostatistics)
* Sill (geostatistics)
* Nugget effect
A major contributor to this section (or its creator) appears to have a conflict of interest with its subject.
It may require cleanup to comply with Wikipedia's content policies, particularly neutral point of view. Please discuss further on the talk page. ({{{November 2009}}})
Jan W Merks, a mineral sampling expert consultant from Canada, has strongly criticized[1] geostatistics since 1992. Referring to it as "voodoo science"[2] and "scientific fraud", he claims that geostatistics is an invalid branch of statistics. Merks submits[2] that geostatistics
* ignores the variance of Agterberg's distance-weighted average point grade,
* ignores the concept of degrees of freedom of a data set when testing for spatial dependence by applying Fisher's F-test to the variance of a set and the first variance term of the ordered set,
* abuses statistics by not using analysis of variance properly,
* replaced genuine variances of single distance-weighted average point grades with pseudo-variances of sets of distance-weighted average point grades, violating the one-to-one correspondence between variances and functions such as Agterberg's distance-weighted average point grade.
Furthermore, Merks claims geostatistics inflates mineral reserve and resources such as in the case of Bre-X's fraud. Merks's expertise and credibility are supported by several company executives, who regularly hire his consulting services[3].
Philip and Watson have also criticized geostatistics in the past [4].
There is a consensus that inappropriate use of geostatistics makes the method susceptible to erroneous reading of results[3][5].
* gslib is a set of fortran 77 routines (open source) implementing most of the classical geostatistics estimation and simulation algorithms
* sgems is a cross-platform (windows, unix), open-source software that implements most of the classical geostatistics algorithms (kriging, Gaussian and indicator simulation, etc) as well as new developments (multiple-points geostatistics). It also provides an interactive 3D visualization and offers the scripting capabilities of python.
* gstat is an open source computer code for multivariable geostatistical modelling, prediction and simulation. The gstat functionality is also available as an S extension, either as R package or S-Plus library.
* besides gstat, R has at least six other packages dedicated to geostatistics and other areas in spatial statistics.
1. ^ A website that criticizes Matheronian geostatistics
^ a b See (Merks 1992)
3. ^ a b Sandra Rubin, "Whistleblower raises doubts over ore bodies," Financial Post, September 30, 2002.
^ See (Philip and Watson 1986).
5. ^ Statistics for Spatial Data, Revised Edition, Noel A. C. Cressie, ISBN 978-0-471-00255-0.
1. Armstrong, M and Champigny, N, 1988, A Study on Kriging Small Blocks, CIM Bulletin, Vol 82, No 923
Armstrong, M, 1992, Freedom of Speech? De Geeostatisticis, July, No 14
3. Champigny, N, 1992, Geostatistics: A tool that works, The Northern Miner, May 18
4. Clark I, 1979, Practical Geostatistics, Applied Science Publishers, London
5. David, M, 1977, Geostatistical Ore Reserve Estimation, Elsevier Scientific Publishing Company, Amsterdam
6. Hald, A, 1952, Statistical Theory with Engineering Applications, John Wiley & Sons, New York
7. Chilès, J.P., Delfiner, P. 1999. Geostatistics: modelling spatial uncertainty, Wiley Series in Probability and Mathematical Statistics, 695 pp.
8. Deutsch, C.V., Journel, A.G, 1997. GSLIB: Geostatistical Software Library and User's Guide (Applied Geostatistics Series), Second Edition, Oxford University Press, 369 pp., https://www.gslib.com/
9. Deutsch, C.V., 2002. Geostatistical Reservoir Modeling, Oxford University Press, 384 pp., https://www.statios.com/WinGslib/index.html
10. Isaaks, E.H., Srivastava R.M.: Applied Geostatistics. 1989.
11. ISO/DIS 11648-1 Statistical aspects of sampling from bulk materials-Part1: General principles
12. Journel, A G and Huijbregts, 1978, Mining Geostatistics, Academic Press
13:.Kitanidis, P.K.: Introduction to Geostatistics: Applications in Hydrogeology, Cambridge University Press. 1997.
14. Lantuéjoul, C. 2002. Geostatistical simulation: models and algorithms. Springer, 256 pp.
15. Lipschutz, S, 1968, Theory and Problems of Probability, McCraw-Hill Book Company, New York.
16. Matheron, G. 1962. Traité de géostatistique appliquée. Tome 1, Editions Technip, Paris, 334 pp.
17. Matheron, G. 1989. Estimating and choosing, Springer-Verlag, Berlin.
18. McGrew, J. Chapman, & Monroe, Charles B., 2000. An introduction to statistical problem solving in geography, second edition, McGraw-Hill, New York.
19. Merks, J W, 1992, Geostatistics or voodoo science, The Northern Miner, May 18
20. Merks, J W, Abuse of statistics, CIM Bulletin, January 1993, Vol 86, No 966
21. Myers, Donald E.; "What Is Geostatistics?
22. Philip, G M and Watson, D F, 1986, Matheronian Geostatistics; Quo Vadis?, Mathematical Geology, Vol 18, No 1
23. Sharov, A: Quantitative Population Ecology, 1996, https://www.ento.vt.edu/~sharov/PopEcol/popecol.html
24. Shine, J.A., Wakefield, G.I.: A comparison of supervised imagery classification using analyst-chosen and geostatistically-chosen training sets, 1999, https://www.geovista.psu.edu/sites/geocomp99/Gc99/044/gc_044.htm
25. Strahler, A. H., and Strahler A., 2006, Introducing Physical Geography, 4th Ed., Wiley.
26. Volk, W, 1980, Applied Statistics for Engineers, Krieger Publishing Company, Huntington, New York.
27. Wackernagel, H. 2003. Multivariate geostatistics, Third edition, Springer-Verlag, Berlin, 387 pp.
28. Yang, X. S., 2009, Introductory Mathematics for Earth Scientists, Dunedin Academic Press, 240pp.
29. Youden, W J, 1951, Statistical Methods for Chemists: John Wiley & Sons, New York.
* Kriging link, contains explanations of variance in geostats
* Arizona university geostats page
* A resource on the internet about geostatistics and spatial statistics
* On-Line Library that chronicles Matheron's journey from classical statistics to the new science of geostatistics
Retrieved from "https://en.wikipedia.org/wiki/Geostatistics"
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Integrated farming (or integrated agriculture) is a commonly and broadly used word to explain a more integrated approach to farming as compared to existing monoculture approaches. It refers to agricultural systems that integrate livestock and crop production and may sometimes be known as Integrated Biosystems.
While not often considered as part of the permaculture movement Integrated Farming is a similar "whole systems approach" to agriculture[1]. There have been efforts to link the two together such as at the 2007 International Permaculture Conference in Brazil[2]. Agro-ecology (which was developed at University of California Santa Cruz) and Bio-dynamic farming also describe similar integrated approaches.
* "pig tractor" systems where the animals are confined in crop fields well prior to planting and "plow" the field by digging for roots
* poultry used in orchards or vineyards after harvest to clear rotten fruit and weeds while fertilizing the soil
* cattle or other livestock allowed to graze cover crops between crops on farms that contain both cropland and pasture (or where transhumance is employed)
* Water based agricultural systems that provide way for effective and efficient recycling of farm nutrients producing fuel, fertilizer and a compost tea/mineralized irrigation water in the process.
In 1993 FARRE (Forum de l'Agriculture Raisonnée Respecteuse l'Environnement) developed agricultural techniques France as part of an attempt to reconcile agricultural methods with the principles of sustainable development. FARRE, promotes an integrated and/or multi-sector approach to food production that includes profitability, safety, animal welfare, social responsibility and environmental care.
Zero Emissions Research and Initiatives (formed in 1994 by the eco-entrepreneur [1]) developed a similar approach to FARRE seeking to promote agricultural and industrial production models that sought to incorporate nature's wisdom into the process. ZERI helped support an effort by an environmental engineer from Mauritius named George Chan.
Chan working with a network of poly-culture farming pioneers began refining Integrated Farming practices that had already been developed in south-east Asia in the 60,70s and 80s, building on the ancient Night soil farming practice.
In China, programs embracing this form of integrated farming have been successful in demonstrating how an intensive growing systems can use organic and sustainable farming practices, while providing a high agriculture yield.
Taking what he learned from the Chinese during his time there, Chan worked at the UN University in the 1990s and forwarded an approach to Integrated Farming which was termed Integrated Biomass Systems working specifically under the UNU/ZERI ZERI Bag Program. Chan during his work with UNU sought to make the case that Integrated Biomass Systems were well suited to help small island nations and low lying tropical regions become more self-reliant and prosperous in the production of food[3]. Working with ZERI, he developed several prototypes for this approach around the world including sites in Namibia and Fiji. The scientifically verified results in a UNDP sponsored congress in 1997 resulted in the adoption of the IBS by the State Government of Paraná, Brazil where dozens of piggeries have applied the system generating food, energy while improving health and environmental conditions.
Montfort Boy's Town in Fiji was one of the first Integrated Biomass Systems developed outside of Southeast Asia with the support of UNU, UNDP and other international agencies. The project which is still operational continues to be a model of how farm operations can provide multiple benefits to stakeholders both local and international.
ZERI Bag had a significant African component that included assisting Father Godfrey Nzamujo in the development of the Songhai Farm Integrated Farming project in Benin[4] .
Most recently The Heifer Foundation - a major international NGO based in the USA - has taken a lead role in deploying Integrated Farming so that it can be replicated globally as an effective approach to sustainable farming in non-affluent regions such as Vietnam[5].
1. ^ Steve Diver's work linking Integrated Farming with Permaculture: https://attra.ncat.org/attra-pub/perma.html
2. ^ Report includes reference to presentation on Integrated Farming by permaculture and ZERI practitioner Eric Fedus and Alexandre Takamatsu
3. ^ Small Islands and ZERI: A unique case for the Application of ZERI: A Paper presented by George Chan of the United Nations University at an International Symposium on "Small Islands and Sustainable Development organized by the United Nations University and the National Land Agency of Japan: https://www.gdrc.org/oceans/chan.html
4. ^ ZERI Bag was designed to focus on small scale deployment of appropriate technologies with a focus on the Integrated Biomass System approach developed by ZERI and George Chan https://www.zeri.unam.na/africa.htm
5. ^ https://www.heifer.org/site/c.edJRKQNiFiG/b.2877337/
* FARRE homepage
* Integrated farming of fish, crop and livestock
* Design an construction of an intergated fish farm
* Integrated Farming System by George Chan
* wiki on integrated farming
* Songhai Centre in Benin
In agriculture, integrated pest management (IPM) is a pest control strategy that uses a variety of complementary strategies including: mechanical devices, physical devices, genetic, biological, cultural management, and chemical management. These methods are done in three stages: prevention, observation, and intervention. It is an ecological approach with a main goal of significantly reducing or eliminating the use of pesticides while at the same time managing pest populations at an acceptable level.[1]
For their leadership in developing and spreading IPM worldwide, Dr. Perry Adkisson and Dr. Ray F. Smith received the 1997 World Food Prize.
Shortly after World War II, when synthetic insecticides became widely available, entomologists in California developed the concept of "supervised insect control." Around the same time, entomologists in cotton-belt states such as Arkansas were advocating a similar approach. Under this scheme, insect control was "supervised" by qualified entomologists, and insecticide applications were based on conclusions reached from periodic monitoring of pest and natural-enemy populations. This was viewed as an alternative to calendar-based insecticide programs. Supervised control was based on a sound knowledge of the ecology and analysis of projected trends in pest and natural-enemy populations.
Supervised control formed much of the conceptual basis for the "integrated control" that University of California entomologists articulated in the 1950s. Integrated control sought to identify the best mix of chemical and biological controls for a given insect pest. Chemical insecticides were to be used in manner least disruptive to biological control. The term "integrated" was thus synonymous with "compatible." Chemical controls were to be applied only after regular monitoring indicated that a pest population had reached a level (the economic threshold) that required treatment to prevent the population from reaching a level (the economic injury level) at which economic losses would exceed the cost of the artificial control measures.
IPM extended the concept of integrated control to all classes of pests and was expanded to include tactics other than just chemical and biological controls. Artificial controls such as pesticides were to be applied as in integrated control, but these now had to be compatible with control tactics for all classes of pests. Other tactics, such as host-plant resistance and cultural manipulations, became part of the IPM arsenal. IPM added the multidisciplinary element, involving entomologists, plant pathologists, nematologists, and weed scientists.
In the United States, IPM was formulated into national policy in February 1972 when President Nixon directed federal agencies to take steps to advance the concept and application of IPM in all relevant sectors. In 1979, President Carter established an interagency IPM Coordinating Committee to ensure development and implementation of IPM practices. (references: "The History of IPM", BioControl Reference Center. [1]
An IPM regime can be quite simple or sophisticated. Historically, the main focus of IPM programs was on agricultural insect pests.[2] Although originally developed for agricultural pest management, IPM programs are now developed to encompass diseases, weeds, and other pests that interfere with the management objectives of sites such as residential and commercial structures, lawn and turf areas, and home and community gardens.
An IPM system is designed around six basic components: The US Environmental Protection Agency has a useful set of IPM principles. [2]
1. Acceptable pest levels: The emphasis is on control, not eradication. IPM holds that wiping out an entire pest population is often impossible, and the attempt can be more costly, environmentally unsafe, and frequently unachievable. IPM programs first work to establish acceptable pest levels, called action thresholds, and apply controls if those thresholds are crossed. These thresholds are pest and site specific, meaning that it may be acceptable at one site to have a weed such as white clover, but at another site it may not be acceptable. This stops the pest gaining resistance to chemicals produced by the plant or applied to the crops. If many of the pests are killed then any that have resistance to the chemical will rapidly reproduce forming a resistant population. By not killing all the pests there are some un-resistant pests left that will dilute any resistant genes that appear.
2. Preventive cultural practices: Selecting varieties best for local growing conditions, and maintaining healthy crops, is the first line of defense, together with plant quarantine and 'cultural techniques' such as crop sanitation (e.g. removal of diseased plants to prevent spread of infection).
3. Monitoring: Regular observation is the cornerstone of IPM. Observation is broken into two steps, first; inspection and second; identification.[3] Visual inspection, insect and spore traps, and other measurement methods and monitoring tools are used to monitor pest levels. Accurate pest identification is critical to a successful IPM program. Record-keeping is essential, as is a thorough knowledge of the behavior and reproductive cycles of target pests. Since insects are cold-blooded, their physical development is dependent on the temperature of their environment. Many insects have had their development cycles modeled in terms of degree days. Monitor the degree days of an environment to determine when is the optimal time for a specific insect's outbreak.
4. Mechanical controls: Should a pest reach an unacceptable level, mechanical methods are the first options to consider. They include simple hand-picking, erecting insect barriers, using traps, vacuuming, and tillage to disrupt breeding.
5. Biological controls: Natural biological processes and materials can provide control, with minimal environmental impact, and often at low cost. The main focus here is on promoting beneficial insects that eat target pests. Biological insecticides, derived from naturally occurring microorganisms (e.g.: Bt, entomopathogenic fungi and entomopathogenic nematodes), also fit in this category.
6. Chemical controls: Synthetic pesticides are generally only used as required and often only at specific times in a pests life cycle. Many of the newer pesticide groups are derived from plants or naturally occurring substances (e.g.: nicotine, pyrethrum and insect juvenile hormone analogues), and further 'biology-based' or 'ecological' techniques are under evaluation.
IPM is applicable to all types of agriculture and sites such as residential and commercial structures, lawn and turf areas, and home and community gardens. Reliance on knowledge, experience, observation, and integration of multiple techniques makes IPM a perfect fit for organic farming (the synthetic chemical option is simply not considered). For large-scale, chemical-based farms, IPM can reduce human and environmental exposure to hazardous chemicals, and potentially lower overall costs of pesticide application material and labor.
1. Proper identification of pest - What is it? Cases of mistaken identity may result in ineffective actions. If plant damage due to over-watering are mistaken for a fungal infection, a spray may be used needlessly and the plant still dies.
2. Learn pest and host life cycle and biology. At the time you see a pest, it may be too late to do much about it except maybe spray with a pesticide. Often, there is another stage of the life cycle that is susceptible to preventative actions. For example, weeds reproducing from last year's seed can be prevented with mulches. Also, learning what a pest needs to survive allows you to remove these.
3. Monitor or sample environment for pest population - How many are here? Preventative actions must be taken at the correct time if they are to be effective. For this reason, once you have correctly identified the pest, you begin monitoring BEFORE it becomes a problem. For example, in school cafeterias where roaches may be expected to appear, sticky traps are set out before school starts. Traps are checked at regular intervals so you can see them right away and do something before they get out of hand. Some of the things you might want to monitor about pest populations include: Is the pest present/absent? What is the distribution - all over or only in certain spots? Is the pest population increasing or decreasing?
4. Establish action threshold (economic, health or aesthetic) - How many are too many? In some cases, a certain number of pests can be tolerated. Soybeans are quite tolerant of defoliation, so if you have only a few caterpillars in the field and their population is not increasing dramatically, there is no need to do anything. Conversely, there is a point at which you MUST do something. For the farmer, that point is the one at which the cost of damage by the pest is MORE than the cost of control. This is an economic threshold. Tolerance of pests varies also by whether or not they are a health hazard (low tolerance) or merely a cosmetic damage (high tolerance in a non-commercial situation). Personal tolerances also vary - many people dislike any insect; some people cannot tolerate dandelions in their yards. Different sites may also have varying requirements based on specific areas. White clover may be perfectly acceptable on the sides of a tee box on a golf course, but unacceptable in the fairway where it could cause confusion in the field of play.[4]
5. Choose an appropriate combination of management tactics For any pest situation, there will be several options to consider. Options include, mechanical or physical control, cultural controls, biological controls and chemical controls. Mechanical or physical controls include picking pests off plants, or using netting or other material to exclude pests such as birds from grapes or rodents from structures. Cultural controls include keeping an area free of conducive conditions by removing or storing waste properly, removing diseased areas of plants properly. Biological controls can be support either through conservation of natural predators or augmentation of natural predators[5]. Augmentative control includes the introduction of naturally occurring predators at either an inundative or inoculative level[6]. An inundative release would be one that seeks to inundate a site with a pest's predator to impact the pest population[7][8]. An inoculative release would be a smaller number of pest predators to supplement the natural population and provide ongoing control.[9] Chemical controls would include horticultural oils or the application of pesticides such as insecticides and herbicides. A Green Pest Management IPM program would use pesticides derived from plants, such as botanicals, or other naturally occurring materials.
6. Evaluate results - How did it work? Evaluation is often one of the most important steps.[10] This is the process to review an IPM program and the results it generated. Asking the following questions is useful: Did your actions have the desired effect? Was the pest prevented or managed to your satisfaction? Was the method itself satisfactory? Were there any unintended side effects? What will you do in the future for this pest situation? Understanding the effectiveness of the IPM program allows the site manager to make modifications to the IPM plan prior to pests reaching the action threshold and requiring action again.
1. ^ United States Environmental Protection Agency, "Pesticides and Food: What Integrated Pest Management Means."
2. ^ https://www.umass.edu/umext/ipm/publications/guidelines/index.html.
3. ^ Bennett, Et Al., "Truman's Scientific Guide to Pest Management Operations", 6th edition, page 10, Purdue University/Questex Press, 2005.
4. ^ Purdue University Turf Pest Management Correspondence Course, Introduction, 2006
5. ^ https://www.knowledgebank.irri.org/IPM/biocontrol/
6. ^ https://www.hort.uconn.edu/ipm/veg/htms/ecbtrich.htm
7. ^ https://pinellas.ifas.ufl.edu/green_pros/ipm_basics.shtml
8. ^ https://www.knowledgebank.irri.org/IPM/biocontrol/Inundative_release.htm
9. ^ https://www.knowledgebank.irri.org/IPM/biocontrol/Inoculative_release_.htm
10. ^ Bennett, Et Al., "Truman's Scientific Guide to Pest Management Operations", 6th edition, page 12, Purdue University/Questex Press, 2005.
* Pests of Landscape Trees and Shrubs: An Integrated Pest Management Guide.
Steve H. Dreistadt, Mary Louise Flint, et al., ANR Publications, University of California, Oakland, California, 1994. 328pp, paper, photos, reference tables, diagrams.
* Bennett, Gary W., Ph.d., Owens, John M., Ph.d., Corrigan, Robert M, Ph.d. Truman's Scientific Guide to Pest Management Operations, 6th Edition, pages 10, 11, 12, Purdue University, Questex, 2005.
* Jahn, GC, PG Cox., E Rubia-Sanchez, and M Cohen 2001. The quest for connections: developing a research agenda for integrated pest and nutrient management. pp. 413-430, In S. Peng and B. Hardy [eds.] “Rice Research for Food Security and Poverty Alleviation.” Proceeding the International Rice Research Conference, 31 March - 3 April 2000, Los Baños, Philippines. Los Baños (Philippines): International Rice Research Institute. 692 p.
* Jahn, GC, B. Khiev, C Pol, N. Chhorn and V Preap 2001. Sustainable pest management for rice in Cambodia. In P. Cox and R Chhay [eds.] “The Impact of Agricultural Research for Development in Southeast Asia” Proceedings of an International Conference held at the Cambodian Agricultural Research and Development Institute, Phnom Penh, Cambodia, 24-26 Oct. 2000, Phnom Penh (Cambodia): CARDI.
* Jahn, GC, JA Litsinger, Y Chen and A Barrion. 2007. Integrated Pest Management of Rice: Ecological Concepts. In Ecologically Based Integrated Pest Management (eds. O. Koul and G.W. Cuperus). CAB International Pp. 315-366.
* Kogan, M 1998. INTEGRATED PEST MANAGEMENT:Historical Perspectives and Contemporary Developments, Annual Review of Entomology Vol. 43: 243-270 (Volume publication date January 1998) (doi:10.1146/annurev.ento.43.1.243)
* Nonveiller, Guido 1984. Catalogue commenté et illustré des insectes du Cameroun d'intérêt agricole: (apparitions, répartition, importance) / University of Belgrade/Institut pour la protection des plantes
* US Environmental Protection Agency, "Pesticides and Food: What Does Integrated Pest Management Mean?" https://www.epa.gov/pesticides/food/ipm.htm
On building organic pest-free gardens
* The Time Saving Garden by David and Charles PLC/Reader's Digest, ISBN 13: 9780276442452
* Integrated Pest Management: Collaborative Research Support Program (IPM CRSP)
* WhatIsIPM.org - Pest control trade-association web site on IPM.
* [3] - Rationalising pesticide use through improved application methods
* IPM for Lawn care
* UC IPM - University of California Statewide Integrated Pest Management Program
This site received a 4-star excellent rating in a recent magazine column dedicated to science-related web sites. (Kevin Ahern, Ph.D. (2009), "GEN Best of the Web", Genetic Engineering & Biotechnology News 29 (8): 66)
* Harvard University IPM - Harvard University IPM Program
* IFAS IPM - University of Florida's Institute of Food and Agricultural Sciences IPM Program
* New York State IPM Program - New York State (Cornell University) IPM Program
* OSU IPM Program - Ohio State University IPM Program
* IPM Images - Thousands of Images related to IPM and Agriculture
* UGA IPM Program - University of Georgia IPM Program
* MSU IPM resources - IPM Resources at Michigan State University
* IPM Institute of North America - Non-profit organization promoting IPM practices
* Green Shield Certified: Effective pest control. Peace of mind. - A third-party certification for effective pest control without unnecessary pesticides
* Top Ten Reasons Why IPM Doesn't Work
* SAFECROP Centre for research and development of crop protection with low environment and consumer health impact
* University of Nebraska IPM write up example
Retrieved from "https://en.wikipedia.org/wiki/Integrated_pest_management"
The process involves balancing nutrients coming into the farming system with those leaving. The aim is to prevent pollution events and save costs by precisely matching the nutrient requirements of the crop with application of organic and inorganic fertilizers.
* Residual nutrients in the soil and organic matter remaining in the soil from previous crops
* Green manure
* Animal manures and slurries
* Inorganic fertilizer application
Nutrient management is a process used by farmers to manage the amount, form, placement, and timing of the application of nutrients (whether as manure, commercial fertilizer, or other form of nutrients) to plants. The purpose is to supply plant nutrients for optimum forage and crop yields, to minimize nonpoint source pollution (runoff of pollutants to surface water) and contamination of groundwater, and to maintain and/or improve the condition of soil.[1] [2]
A nutrient management plan is a set of conservation practices designed to use fertilizer and/or manure effectively while protecting against the potential adverse impacts of manure, erosion and organic byproducts on water quality. When such a plan is designed for animal feeding operations (AFO) it may be termed a "manure management plan." The plans typically address:
* soil testing
* manure testing
* erosion control practices
* According to the soil pH the recommend dose may be varying.
* timing of fertilizer/manure application.[2]
In the United States some regulatory agencies recommend or require that farms implement these plans, in order to prevent water pollution. The U.S. Natural Resources Conservation Service (NRCS) has published guidance documents on preparing a comprehensive nutrient management plan (CNMP) for AFOs.[3] [4]
^ U.S. Natural Resources Conservation Service (NRCS). Fort Worth, TX. "National Conservation Practice Standard: Nutrient Management." Code 590. August 2006.
^ a b U.S. Environmental Protection Agency (EPA). Washington, DC. "Nutrient Management." September 11, 2007.
^ NRCS. Beltsville, MD. "Comprehensive Nutrient Management Plans." Fact Sheet. 2003.
^ NRCS. "National Planning Procedures Handbook: Draft Comprehensive Nutrient Management Planning Technical Guidance." Subpart E, Parts 600.50-600.54 and Subpart F, Part 600.75. December 2000.
This agriculture article is a stub. You can help Wikipedia by expanding it.
Precision viticulture is precision farming applied to optimize vineyard performance, in particular maximizing grape yield and quality while minimizing environmental impacts and risk [1]. This is accomplished by measuring local variation in factors that influence grape yield and quality (soil, topography, microclimate, vine health, etc.) and applying appropriate viticulture management practices (trellis design, pruning, fertilizer application, irrigation, timing of harvest, etc.)[2][3]. Precision viticulture is based on the premise that high in-field variability for factors that affect vine growth and grape ripening warrants intensive management customized according to local conditions. Precision viticulture depends on new and emerging technologies such as global positioning systems (GPS), meteorologic and other environmental sensors, satellite and airborne remote sensing, and geographic information systems (GIS) to assess and respond to variability.
Precision viticulture is unique in its emphasis on vineyard management according to local variation, and in its use of science and technology to accomplish this. While Australian viticulturalists are generally recognized as leaders in precision viticulture, and while viticulturalists worldwide have embraced the approach, the fundamental concepts have deep roots in the traditions of Old World winemaking regions. Terroir, a related French concept, refers to the special geographic qualities or "sense of place" embodied in the wine produced in a particular region [4].
Precision agriculture emphasizes "doing the right thing, in the right place, at the right time", and is practical for viticulture because of high local variability of conditions within vineyards, and because of responsiveness to intensive management in terms of increased grape yield and quality. According to CSIRO, Australia [5] "Typically grape yield varies eight to ten-fold under uniform management"; "patterns of yield variation are stable in time and driven by soil and topographic variation"; and "patterns of variation in fruit quality tend to be similar to those for yield, suggesting opportunities for zonal management and selective harvest". Australian precision viticulture has focused on yield monitoring, whereas California precision viticulture has focused on remote sensing [6].
Precision viticulture uses a broad set of enabling technologies to observe and respond to vineyard variability:
* Global Positioning Systems (GPS) provide satellite-based georeferencing for mapping vineyard environmental variability.
* Meteorologic Stations monitor climatic factors important for vine growth and grape ripening, including temperature, precipitation, humidity, and wind.
* Remote Sensing from satellite and airborne platforms provides images depicting vineyard conditions, for example vine productivity from normalized difference vegetation index (NDVI).
* Digital Elevation Models (DEM) provide detailed topographic information.
* High Resolution Soil Surveys provide detailed information about soil fertility and hydrologic characteristics.
* Relational Databases organize environmental and economic information.
* Geographic Information Systems (GIS) provide digital tools for map-based analysis.
* Other Environmental Sensors monitor important biophysical factors such as solar radiation, soil moisture, and temperature regimes.
Precision viticulture draws upon a variety of management approaches, including zonal management, in which different areas of the vineyard are managed according to their unique conditions, and adaptive management, in which different management practices are applied according to observed needs and improved knowledge. Trellis design, in terms of row orientation and geometry of vine support, and pruning practices can be tailored to optimize vine health, to protect grapes from frost, sunburn, and mildew damage, and to ensure even grape ripening[7]. Irrigation and fertilizer application schedules, pest management, and selective harvest based on timing of ripening can all be managed to minimize costs and maximize vineyard performance based on observed needs. Increasingly, precision viticulture, with its focus on management according to local variability, is coupled with organic farming, with its focus on environmentally friendly practices without the use of chemical pesticides and fertilizers, and with sustainable agriculture, with emphasis on long-term environmental stewardship and economic viability.
Various integrative technological approaches are gaining increasing attention for application in precision viticulture:
* Distributed Sensor Networks use strategic deployment of sensors throughout a vineyard to monitor key factors such as water stress and temperature.
* Vineyard Models simulate microclimate, vine growth, grape ripening, and economic return on investment to evaluate management options.
* Decision Support Systems (DSS) bring together vineyard environmental and economic databases, vineyard models, and GIS in an interactive software-based system to solve management problems and better make decisions.
^ Proffitt, T., R. Bramley, D. Lamb, and E. Winter. 2006. Precision Viticulture: A New Era in Vineyard Management and Wine Production. WineTitles, Adelaide. ISBN 9780975685044
^ Bramley R.G.V., Hamilton R.P. 2004. Understanding variability in winegrape production systems. 1. Within vineyard variation in yield over several vintages. Australian Journal of Grape and Wine Research 10: 32-45.
3. ^ Bramley R.G.V. 2005. Understanding variability in winegrape production systems. 2. Within vineyard variation in quality over several vintages. Australian Journal of Grape and Wine Research 11: 33-42.
^ Robinson, J. (ed). 2006. The Oxford Companion to Wine, Third Edition. Oxford University Press. ISBN 0198609906
5. ^ CSIRO, 2008. Australia Precision Viticulture Overview, https://www.csiro.au/science/Precision-Viticulture.html, accessed December 15, 2008
^ Goode, J. 2005. The Science of Wine: from Vine to Glass. University of California Press, Berkeley. ISBN 0520248007, ISBN 9780520248007
^ Weiss, S.B., D.C. Luth, and B. Guerra. 2003. Potential solar radiation in a VSP trellis at 38°N latitude. Practical Winery and Vineyard 25:16-27.
The Science of Wine: from Vine to Glass. University of California Press, Berkeley. ISBN 0520248007, ISBN 9780520248007
Proffitt, T., R. Bramley, D. Lamb, and E. Winter. 2006. Precision Viticulture: A New Era in Vineyard Management and Wine Production. WineTitles, Adelaide. ISBN 9780975685044
Sommers, B.J. 2008. The Geography of Wine: How Landscapes, Cultures, Terroir, and the Weather Make a Good Drop. Plume Press/Penguin Prentice-Hall Press. ISBN 0452288908
Swinchatt, J., and D.G. Howell. 2004. The Winemaker's Dance: Exploring Terroir in the Napa Valley. University of California Press, Berkeley. ISBN 0520235134
The Landsat program is the longest running enterprise for acquisition of imagery of Earth from space. The first Landsat satellite was launched in 1972; the most recent, Landsat 7, was launched on April 15, 1999. The instruments on the Landsat satellites have acquired millions of images. The images, archived in the United States and at Landsat receiving stations around the world, are a unique resource for global change research and applications in agriculture, cartography, geology, forestry, regional planning, surveillance, education and national security. Landsat 7 data has eight spectral bands with spatial resolutions ranging from 15 to 60 meters.
Hughes Santa Barbara Research Center initiated design and fabrication of the first three MSS Multi-Spectral-Scanners in the same year man landed on the moon, 1969. The first prototype MSS was completed within nine months by fall of 1970 when it was tested by scanning Half Dome at Yosemite National Park.
The initial centerline for the primary layout of the MSS was drawn by Jim Kodak, the opto-mechanical design engineer who designed the Pioneer spacecraft optical camera, the first instrument to leave the solar system.
The program was called the Earth Resources Observation Satellites Program when it was initiated in 1966, but the name was changed to Landsat in 1975. In 1979, Presidential Directive 54 under President of the United States Jimmy Carter transferred Landsat operations from NASA to NOAA, recommended development of long term operational system with four additional satellites beyond Landsat 3, and recommended transition to private sector operation of Landsat. This occurred in 1985 when the Earth Observation Satellite Company (EOSAT), a partnership of Hughes Aircraft and RCA, was selected by NOAA to operate the Landsat system under a ten year contract. EOSAT operated Landsats 4 and 5, had exclusive rights to market Landsat data, and was to build Landsats 6 and 7.
In 1989, this transition had not been fully completed when NOAA's funding for the Landsat program ran out and NOAA directed that Landsats 4 and 5 be shut down, but an act of the United States Congress provided emergency funding for the rest of the year. Funding ran out again in 1990 and once again Congress provided emergency funding to NOAA for six more months of operations, requesting that agencies that used Landsat data provide the funding for the other six months of the upcoming year. The same funding problem and solution was repeated in 1991. In 1992, various efforts were made to finally procure funding for follow on Landsats and continued operations, but by the end of the year EOSAT ceased processing Landsat data. Landsat 6 was finally launched on October 5, 1993, but was lost in a launch failure. Processing of Landsat 4 and 5 data was resumed by EOSAT in 1994. NASA finally launched Landsat 7 on April 15, 1999.
The value of the Landsat program was recognized by Congress in October 1992 when it passed the Land Remote Sensing Policy Act (Public Law 102-555) authorizing the procurement of Landsat 7 and assuring the continued availability of Landsat digital data and images, at the lowest possible cost, to traditional and new users of the data.
* Landsat 1 (originally named Earth Resources Technology Satellite 1) - launched July 23, 1972, terminated operations January 6, 1978
* Landsat 2 - launched January 22, 1975, terminated January 22, 1981
* Landsat 3 - launched March 5, 1978, terminated March 31, 1983
* Landsat 4 - launched July 16, 1982, terminated 1993
* Landsat 5 - launched March 1, 1984, still functioning. [1] [2]
* Landsat 6 - launched October 5, 1993, failed to reach orbit
* Landsat 7 - launched April 15, 1999, still functioning, but with faulty scan line corrector (May 2003) [3]
This false-color composite (processed to simulate true color) image of the island of Hawaii was constructed from data gathered between 1999 and 2001 by the Enhanced Thematic Mapper plus (ETM+) instrument, flying aboard the Landsat 7 satellite. The Landsat data were processed by the National Oceanographic and Atmospheric Administration (NOAA) to develop a landcover map. The black areas on the island (in this scene) that resemble a pair of sun-baked palm fronds are hardened lava flows formed by the active Mauna Loa Volcano. Just to the north of Mauna Loa is the dormant grayish Mauna Kea Volcano, which hasn't erupted in an estimated 3,500 years. A thin greyish plume of smoke is visible near the island's southeastern shore, rising from Kilauea—the most active volcano on Earth. Heavy rainfall and fertile volcanic soil have given rise to Hawaii's lush tropical forests, which appear as solid dark green areas in the image. The light green, patchy areas near the coasts are likely sugar cane plantations, pineapple farms, and human settlements.
The Multi-Spectral-Scanner had a 9" fused silica dinner-plate mirror epoxy bonded to three invar tangent bars mounted to base of a Ni/ Au brazed Invar frame in a serreuire truss that was arranged with four "Hobbs-Links" (conceived by Dr. Gregg Hobbs) crossing at mid truss. This construct ensured the secondary mirror would simply oscillate about the primary optic axis to maintain focus despite vibration inherent from the 14-inch (360mm) Be scan mirror. This engineering solution allowed the US to develop LANDSAT at least five years ahead of French SPOT which first used CCD arrays to stare without need for a scanner.
The MSS FPA, or Focal Plane Array consisted of 24 square optical fibers extruded down to .0002"square fiber tips in a 4x6 array to be scanned across the Nimbus spacecraft path in a +/-6 degree scan as the satellite was in a 10:30 polar orbit, hence it had to be launched from Vandenburg AFB. The fiber optic bundle was embedded in a fiber optic plate to be terminated at a relay optic device that transmitted fiber end signal on into six photodiodes and 18 photomultiplier tubes that were arrayed across a 0.30-inch (7.6mm) thick aluminum tool plate, with sensor weight balanced vs the 9-inch (230mm) telescope on opposite side. This main plate was assembled on a frame, then attached to the silver-loaded magnesium housing with helicoil fasteners.
Key to MSS success was the scan monitor mounted on the underbelly of the Mg housing. It consisted of a diode source & sensor mounted at ends of four flat mirrors that were tilted so that it took 14 bounces for a beam to reflect length of the three mirrors from source to sender striking Be scan mirror seven times as it reflected seven times off the flat mirrors. It only sensed three positions, both ends of scan & the mid scan, but that was all that was required to determine where MSS was pointed and electronics scanning could be calibrated to display a map.
The Landsat Data Continuity Mission, scheduled to be launched in 2012, will be the next satellite in the Landsat series. The new satellite is being built in Arizona by General Dynamics Advanced Information Systems. [4]
1. ^ Universe Today» Landsat 5 Reaches 20 Years in Space
2. ^ 20 Years of Landsat 5
3. ^ The Landsat Program
4. ^ "Landsat Data Continuity Mission". NASA. https://ldcm.gsfc.nasa.gov/.
Precision agriculture. (2017, Jun 26).
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