{"id":137411,"date":"2011-01-20T11:07:31","date_gmt":"2011-01-20T10:07:31","guid":{"rendered":"http:\/\/www.madrimasd.org\/blogs\/universo\/?p=137411"},"modified":"2011-04-08T18:55:57","modified_gmt":"2011-04-08T17:55:57","slug":"progresos-tecnologicos-en-la-determinacion-del-color-de-los-suelos","status":"publish","type":"post","link":"https:\/\/www.madrimasd.org\/blogs\/universo\/2011\/01\/20\/137411","title":{"rendered":"Progresos Tecnol\u00f3gicos en la Determinaci\u00f3n del Color de los Suelos"},"content":{"rendered":"

Desde luego un dalt\u00f3nico<\/a> sufrir\u00eda serias dificultades con vistas a ser un buen edaf\u00f3logo de campo. Los colores del suelo nos informan mucho<\/strong> sobre los<\/strong><\/span> avatares que ha sufrido un suelo a lo largo de su evoluci\u00f3n, de sus condiciones actuales, siendo un elemento imprescindible para su correcta clasificaci\u00f3n en las taxonom\u00edas edafol\u00f3gicas<\/span><\/strong>. A\u00a0 tal fin, se vienen utilizando normativamente las<\/span><\/strong> Cartas de Munsell<\/a>. Sin embargo, la visualizaci\u00f3n y procesamiento de los colores por nuestros sentidos y aparato cognitivo dista de ser exacta<\/span><\/strong> e inequ\u00edvoca. Resulta a menudo divertido vernos a varios colegas discutir sobre el \u201cverdadero\u201d color de una muestra, por cuanto no siempre lo percibimos igual. M\u00e1s aun, un mismo suelo puede atesorar diferentes colores, siendo entonces imprescindible especificar<\/span><\/strong> cada uno de ellos, as\u00ed como su forma (por ejemplo moteados rojizos en una matriz amarillenta) y \u00e1rea aproximada (hablando en t\u00e9rminos muy groseros). Con tal motivo, las gu\u00edas de descripci\u00f3n de los perfiles<\/span><\/strong> (como la de la FAO) nos ofrecen metodolog\u00edas est\u00e1ndar adecuadas. La noticia de hoy pretende ofrecer una t\u00e9cnica m\u00e1s objetiva, apelando al uso de an\u00e1lisis digital de im\u00e1genes y software en condiciones controladas de laboratorio<\/span><\/strong>. Tal modo de proceder, obviamente, atesora virtudes, pero tambi\u00e9n numerosos inconvenientes<\/strong><\/span>. En cualquier, caso la nota de prensa que os ofrecemos hoy ser\u00eda una primicia de constituir una genuina novedad. Sin embargo no es as\u00ed, por cuanto ya se comercializan instrumentales al respecto incluso para condiciones de campo \u00bf?<\/span><\/strong>.<\/p>\n

\"determinacion-automatica-del-color<\/p>\n

Digital images of soil features classified by hue, value (lightness or darkness) and chroma (saturation). (Credit: Courtesy Kevin O’Donnell, University of Missouri). Fuente: Sciencedaily<\/a><\/p>\n

<\/p>\n

Ya hace a\u00f1os que escuch\u00e9 hablar de la necesidad de estimar el color en condiciones controladas de laboratorio, bajo una iluminaci\u00f3n homog\u00e9nea y adecuada. Por tanto, deben existir antecedentes<\/span><\/strong>. En cualquier caso, el trabajo se encuentra en acceso abierto<\/span><\/strong> (a pesar de ser un estudio publicado en una revista indexada de pago, la USDA suele conseguirlo, no se si pagando a la editorial u de otra forma), por lo que vosotros mismos podr\u00e9is comprobar si se mencionan los esfuerzos realizados en estudios previos. Abajo os ofrecemos el enlace<\/span><\/strong>.<\/p>\n

Nuestro amigo Carlos Cruz (del INEGI) me mostr\u00f3 en un viaje de campo (M\u00e9xico, 2009) una c\u00e1mara especial, y francamente cara en t\u00e9rminos pecuniarios, \u00a0con vistas a determinar los colores de los suelos en condiciones de campo<\/span><\/strong>. Por esa raz\u00f3n, me sorprende que la nota de prensa, a dem\u00e1s de exagerar las bondades del producto, se muestre como primicia en 2010<\/span><\/strong>.<\/p>\n

Es cierto que en \u201calgunas ocasiones\u201d la mala determinaci\u00f3n del color puede acarrear una deficiente clasificaci\u00f3n del perfil de suelos analizado<\/span><\/strong>. Obviamente, el problema se complica cuando<\/strong><\/span> aparecen pr\u00f3ximos varios colores diferentes, como en el caso de los suelos con rasgos hidrom\u00f3rficos, por cuanto los moteados suelen ser muy frecuentes (se trata del caso al que alude esta investigaci\u00f3n). Ahora bien tal dificultad, en mi opini\u00f3n, obedece m\u00e1s a la falta de pr\u00e1ctica que a los ciertamente existentes sesgos sensoriales-cognitivos individuales<\/span><\/strong>. En cualquier caso las taxonom\u00edas precisan que se explicite el color del suelo (hue, value y chroma) en condiciones de capacidad de campo (h\u00famedo pero no encharcado; capacidad m\u00e1xima de retencui\u00f3n de humedad) y una vez secadas las muestras en el laboratorio. Generalmente, sobre el terreno se realiza una primera aproximaci\u00f3n.<\/p>\n

\"<\/p>\n

Determinaci\u00f3n del Color del suelo mediante las cartas Munsell. Fuente Kevin O’Donnell. University of Missoury, aunque realmente no se realiza de una manera tan burda<\/a><\/p>\n

No albergo dudas que bajo las condiciones controladas que nos muestra \u00a0O’Donnell<\/strong> en la nota de prensa y su p\u00e1gina Web,<\/span> haciendo uso de<\/strong><\/span> c\u00e1maras digitales potentes,\u00a0software de an\u00e1lisis digital, as\u00ed como de la iluminaci\u00f3n adecuada, tales determinaciones deban ser mucho m\u00e1s precisas que las cl\u00e1sicas<\/span><\/strong>. Tambi\u00e9n este investigador alega que podr\u00eda mejorarse su procedimiento con vistas a ser usado como instrumental de campo (aun que tal modo de proceder no evita la necesidad de hacerlo tambi\u00e9n en el laboratorio, si se desean dar los datos sobre una muestra seca y h\u00fameda). Ho haga\u00eds caso\u00a0a la segunda foto que os ofrecemos<\/span><\/strong>, <\/span>as\u00ed jam\u00e1s se mide el color del suelo. Simplemente es pura ignorancia. Francamente, el que este producto se presente como algo novedoso, as\u00ed como el propio contenido de la noticia, repleta de un marketing m\u00e1s que desmesurado, no se me antoja correcto<\/span><\/strong>. Se trata de vender algo ya conocido<\/span><\/strong> (aunque pueda haberse mejorado tecnol\u00f3gicamente respecto a la c\u00e1mara que me mostr\u00f3 Caros Cruz) como una genuina novedad<\/span><\/strong>, cuando no es cierto. No entrar\u00e9 en detalles ya que no es esencial para los profanos, y los colegas bien pueden leerla en suahili, como la exponemos.<\/p>\n

Sin embargo, hay otro aspecto que no debemos soslayar. Si en pro de obtener determinaciones m\u00e1s exactas de rasgos sencillos comenzamos a complicar y encarecer el instrumental, convertiremos a la edafolog\u00eda de campo en una actividad que solo pueden llevar a cabo los ricos<\/span><\/strong>. Hoy por hoy, y a la espera de instrumentos baratos y sencillos, la mayor parte de los edaf\u00f3logos seguir\u00e1n haciendo uso de las Cartas Munsell<\/span><\/strong>. \u00a0En definitiva, no es muy frecuente que un\u00a0edaf\u00f3logo haga toda la tarea en el campo (ni de laboratorio) por si solo y como dos, tres o cuatro pares de ojos son m\u00e1s \u201cobjetivos que uno\u201d (\u2026) (tan solo hace falta tenerlo en cuenta<\/span><\/strong>), como lo hac\u00eda yo, que soy francamente torpe con eso de los colores (aun no se si tengo los ojos verdes y azules \u00bf?).<\/p>\n

Con todo mi respeto a Kevin (al que no tengo el gusto de conocer), no creo que sea la mejor forma de \u201cvender\u201d su ciencia. Finalmente, como an\u00e9cdota personal<\/span><\/strong>, os dir\u00e9 que sol\u00eda bromear con algunos compa\u00f1eros alegando que prefer\u00eda llevar a cabo los levantamientos de campo por la noche. Cuando me interpelaban sorprendidos la raz\u00f3n les respond\u00eda: \u201cde noche todos los suelos son pardos\u201d<\/p>\n

Juan Jos\u00e9 Ib\u00e1\u00f1ez<\/span><\/strong><\/p>\n

Taking the Guesswork out of Soil Classification<\/a><\/h3>\n

<\/strong>ScienceDaily (<\/strong>June 7, 2010<\/strong>)<\/strong><\/span> \u2014 A University of Missouri doctoral student has developed a technique that uses digital imaging of soil samples to take some of the guesswork out of wetland identification<\/strong>.<\/p>\n

Identifying wetlands isn’t always easy. The U.S. Army Corps of Engineers’ manual on wetlands identification<\/strong> is 143 pages long. Land that is wet isn’t necessarily a wetland, and some wetlands aren’t always wet<\/strong>. One important tool is looking at the soil for colors and patterns characteristic of frequent and prolonged saturation<\/strong>, said Kevin O’Donnell, a doctoral student in soil science at MU.<\/p>\n

Chronic saturation changes a soil’s structure and chemical composition and affects the types of microorganisms it harbors. These changes determine the colors and other visible features of soil. Soil scientists use those features to identify what they call \u00abhydric soils.\u00bb<\/p>\n

A trusty companion of soil scientists in the field is a small loose-leaf binder holding a set of \u00abMunsell Soil Color Charts,\u00bb which contains 238 color chips and other visual aides for classifying soils.<\/p>\n

There’s a small hole adjacent to each chip that lets you compare the color chip and soil sample side-by-side.<\/p>\n

\u00abThere’s a lot of room for error,\u00bb O’Donnell said. Cloud cover, time of day and many other factors can affect perception of a soil’s appearance. Experienced soil scientists learn to take this into account, but even seasoned pros might come to different conclusions about a given sample.<\/p>\n

\u00abYou’re dealing with jurisdictional identification of wetlands<\/strong>,\u00bb he said. \u00abImagine you’re a landowner and a soil scientist comes out and says you have a hydric soil<\/strong>.\u00bb<\/p>\n

Wetlands are protected under the federal law<\/strong>, so landowners can end up facing restrictions on developing or farming their land based on a subjective assessment of the soil. \u00abWill that hold up in court? I saw some major issues there.\u00bb<\/p>\n

In an earlier project, O’Donnell used software to analyze aerial photos of large areas and determine land use based on color and other attributes. \u00abWhy not use that technology on a smaller scale?<\/strong>\u00ab<\/p>\n

He decided to bring soil samples to the laboratory and photograph them under controlled conditions<\/strong>.<\/p>\n

For advice on photo equipment, O’Donnell sought out David Rees, chair of photojournalism at MU. O’Donnell procured a Nikon D80 camera, a 60mm f\/2.8 macro lens and a pair of lens-mounted flashes to provide uniform, consistent lighting<\/strong>. His equipment purchases were funded in part by a scholarship named in honor of the late C.E. Marshall, an MU soil scientist and, as it turned out, the father-in-law of David Rees.<\/p>\n

O’Donnell calibrated the software by photographing a brand-new set of Munsell color charts. \u00abI didn’t know if this was going to work,\u00bb O’Donnell recalled. The goal was to precisely quantify a soil sample’s dominant colors in terms of hue, chroma<\/strong> (saturation) and value<\/strong> (lightness or darkness), as well as the abundance and distribution of those colors<\/strong>. \u00abIt turns out that it works really well,\u00bb he said. \u00abThe color identification was approximately 99 percent accurate for all the colors in the book.\u00bb<\/p>\n

Not only does the technique provide a more reliable way to identify hydric soils, it opens an avenue for collaboration with other disciplines by producing data about soil in a standardized, quantitative form<\/strong>, he said.<\/p>\n

\u00abOnce you get here it opens up a door to new ways of looking at soils<\/strong> that haven’t been looked at in the past,\u00bb he said.<\/p>\n

\u00abIt is a pretty ingenious amalgamation of techniques and ideas that provides soil scientists with a new tool for the 21st century<\/strong>,\u00bb said Keith Goyne, an MU soil scientist. O’Donnell describes his project in a paper that appeared recently in Geoderma, considered a top-tier journal by soil scientists<\/strong>. O’Donnell’s co-authors on the paper were Goyne, Stephen Anderson and Randall Miles of MU, and Claire Baffaut and Kenneth Sudduth of the USDA Agricultural Research Service.<\/p>\n

O’Donnell’s research is funded by a grant from the USDA’s Conservation Effects Assessment Project with partial support from the University of Missouri Research Council.<\/p>\n

O’Donnell said that it should be possible to adapt his system for use in the field by attaching a box to the camera to block out natural light when photographing a soil sample.<\/strong> In certain instances, this would avoid the expense and burden of extracting hefty core samples and hauling them to the lab.<\/p>\n

Story Source<\/strong>: The above story is reprinted (with editorial adaptations by ScienceDaily staff) from materials provided by University of Missouri-Columbia<\/a>.<\/p>\n

Journal Reference<\/strong>: T. Kevin O’Donnell, Keith W. Goyne, Randall J. Miles, Claire Baffaut, Stephen H. Anderson, Kenneth A. Sudduth. Identification and quantification of soil redoximorphic features by digital image processing. Geoderma, 2010; DOI: 10.1016\/j.geoderma.2010.03.<\/a><\/p>\n

Resumen del Trabajo Original<\/span><\/strong><\/p>\n

Soil redoximorphic features (SRFs)<\/strong> have provided scientists and land managers with insight into relative soil moisture for approximately 60 years. The overall objective of this study was to develop a new method of SRF identification and quantification from soil cores using a digital camera and image classification software<\/strong>.<\/p>\n

Additional objectives included a determination of soil moisture effects on quantified SRFs and image processing effects on interpretation of SRF metrics<\/strong>. Eighteen horizons from selected landscapes in the Central Claypan Area, northcentral Missouri, USA were photographed from exposed soil cores under controlled light conditions. A 20 cm2 <\/sup>area was used for SRF quantification following a determination of the initial gravimetric water content of horizon faces. Overall color determination accuracy was 99.6% based on Munsell soil color groupings used for SRF identification. Rewetting of air-dry horizon faces by successive application of 1 mL of deionized water demonstrated little change in identified SRFs after seven applications. Mean change in identified<\/strong> Low Chroma and High Chroma SRFs between the seventh and tenth rewetting sequences was 2% (SD\u00b14) and 0.03% (SD\u00b10.3), respectively. However, ten of eighteen horizons contained a greater area of Low Chroma after ten rewetting sequences compared to the same horizon at the initial moisture state.<\/p>\n

Metrics characterizing SRF boundaries, shapes, number of SRFs, and mean area of SRFs were sensitive to post-classification image smoothing. Methods demonstrated by this study provide an opportunity to better integrate pedology with other related earth sciences by allowing standardized quantification of SRFs as well as a determination of human error associated with current visual estimates<\/strong>.<\/p>\n

Introducci\u00f3n Inicio<\/strong>.<\/p>\n

Color is the most cited attribute used for soil classification and land use decisions by people around the world (Barrera-Bassols and Zinck, 2003). <\/strong>Human perception of color is dependent on both a physical stimulus<\/strong> (e.g., reflected wavelengths striking receptors within the eye) and the processing of nerve impulses within the brain. The latter of these represents a subjective, psychological aspect of color perception that is dependent on an individual’s color experiences and varies among multiple observers <\/strong>(Thompson, 1995). While color references have been adopted to aid in transfer of soil color knowledge (e.g., Munsell soil color charts), the lack of a standardized, objective color perception by humans remains a notable source of error when describing and classifying soils. Reliable land management decisions based on interpretations of soil color and color patterns (e.g., soil redoximorphic features) require accurate, concise measurements.<\/p>\n

Publicaci\u00f3n en Acceso Abierto Pinchando Aqu\u00ed<\/a><\/h2>\n","protected":false},"excerpt":{"rendered":"

Desde luego un dalt\u00f3nico sufrir\u00eda serias dificultades con vistas a ser un buen edaf\u00f3logo de campo. Los colores del suelo nos informan mucho sobre los avatares que ha sufrido un suelo a lo largo de su evoluci\u00f3n, de sus condiciones actuales, siendo un elemento imprescindible para su correcta clasificaci\u00f3n en las taxonom\u00edas edafol\u00f3gicas. A\u00a0 tal fin, se vienen utilizando normativamente las Cartas de Munsell. Sin embargo, la visualizaci\u00f3n y procesamiento de los colores por nuestros sentidos y aparato cognitivo dista de ser exacta e inequ\u00edvoca. Resulta a menudo divertido vernos a varios colegas discutir sobre el \u201cverdadero\u201d color de una\u2026<\/p>\n","protected":false},"author":26,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"ngg_post_thumbnail":0},"categories":[603,590,597,606,601],"tags":[46903,2579],"blocksy_meta":{"styles_descriptor":{"styles":{"desktop":"","tablet":"","mobile":""},"google_fonts":[],"version":4}},"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/www.madrimasd.org\/blogs\/universo\/wp-json\/wp\/v2\/posts\/137411"}],"collection":[{"href":"https:\/\/www.madrimasd.org\/blogs\/universo\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.madrimasd.org\/blogs\/universo\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.madrimasd.org\/blogs\/universo\/wp-json\/wp\/v2\/users\/26"}],"replies":[{"embeddable":true,"href":"https:\/\/www.madrimasd.org\/blogs\/universo\/wp-json\/wp\/v2\/comments?post=137411"}],"version-history":[{"count":14,"href":"https:\/\/www.madrimasd.org\/blogs\/universo\/wp-json\/wp\/v2\/posts\/137411\/revisions"}],"predecessor-version":[{"id":138841,"href":"https:\/\/www.madrimasd.org\/blogs\/universo\/wp-json\/wp\/v2\/posts\/137411\/revisions\/138841"}],"wp:attachment":[{"href":"https:\/\/www.madrimasd.org\/blogs\/universo\/wp-json\/wp\/v2\/media?parent=137411"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.madrimasd.org\/blogs\/universo\/wp-json\/wp\/v2\/categories?post=137411"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.madrimasd.org\/blogs\/universo\/wp-json\/wp\/v2\/tags?post=137411"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}