Selectivity and Kinetics of Ion Uptake by Barley Plants Following Nutrient Deficiency

Introduct ion ................................................................................................................................................................ 533 Compar ison of Cl ipping to G r a z i n g .............................................................................................. 533 Effect of Herbage Removal on Above-Ground Par ts of P lants ........................ 533 Dry Mat te r Yield ............................................................................................................................... 533 Grasses ........................................................................................................................................... 533 Forbs ...................................................................................................................................................... 537 Grass -Legume Mixtures ...................................................................................................... 537 Shrubs ..................................................................................................................................................... 538 Relat ionship of Dry Mat ter Yield to Physiological Processes .................. 539 Competit ion for Light and Carbon Diox ide the Leaf Area Index .................................................................................................... 539 Apical Dominance and Growth of Lateral Buds ......................................... 541 P lan t Form ........................................................................................................................................................ 547 Protein Yield ................................................................................................................................................ 547 Seed Product ion ......................................................................................................................................... 550 Genera l .................................................................................................................................................. 550 Relat ionship to Photoperiodism and Vernal izat ion ................................... 554 Effect of Herbage Removal on Root Growth and Root Weigh t s ..................... 555 Effect of Root Removal on T op Growth ..................................................................................... 557 Relat ionship of Season and Fru i t ing to Carbohydrate Storage .......................... 558 T r e n d s in Herbaceous Plants ....................................................................................................... 558 T r e n d s in Woody Plants ................................................................................................................ 559 Mechan i sms and Variat ions ............................................................................................................ 560 Effects of Herbage Removal on Chemical Relat ionships of Roots .................. 562 Chemical Benefits of G r a z i n g An ima l s to Herbage Plants ...................................... 571 Conclusions ................................................................................................................................................................... 571 Li terature Cited .................................................................................................................................................. 573

Responses of individual plants to harvesting

Traditionally, ideal cotton (Gossypium ssp.) fibers are said to be as white as snow, as trong as steel, as fine as silk and as long as wool. It is difficult to incorporate these specifications favored by cotton processors into a breeding program or to set them as quantitative goals for cotton producers. Since the 36 JOURNAL OF COTTON SCIENCE, Volume 4, Issue 1, 2000 early 1980s in the USA, the USDA-AMS cotton classing offices have become the primary connection for fiber quality between cotton producers and processors. The high volumes of cotton passing through the classing offices every year have forced workers there to make compromises for the sake of speed and productivity, and to develop rapid, semiautomatic classing techniques that have blurred some fiber-quality definitions in ways that may favor one industry segment over another. The vertical integration of the U.S. cotton industry from field to fabric depends on efficient use and cooperative refinement of the existing line of communication. Fiber-classing technologies now in use and under development and evaluation allow quantitation of fiber properties, application of improved standards for end-product quality, and, most importantly, creation of a fiber-quality language and a system of fiber-quality measurements that can be meaningful and useful to producers and processors alike. A cotton physiologist working in production research examines the interface between cotton production and processing in terms of the fiber properties currently quantified by the USDA-AMS cotton-classing offices, describes the measurement protocols available, and investigates possible environmental sources of the significant variations in fiber quality that reduce grower and processor profits. The interaction of growth environment, genetic potential, and fiber properties quantified at harvest are discussed where appropriate data or references exist. From the physiologist’s perspective, the fiber quality of a specific cotton genotype is a composite of fiber shape and maturity properties that depend on complex interactions among the genetics and physiology of the plants producing the fibers and the growth environment prevailing during the cotton production season. Fiber shape properties, particularly length and diameter, are largely dependent on genetics. Fiber maturity properties, which are dependent on deposition of photosynthate in the fiber cell wall, are more sensitive to changes in the growth environment. The effects of the growth environment on the genetic potential of a genotype modulate both shape and maturity properties to varying degrees. Anatomically, a cotton fiber is a seed hair, a single hyperelongated cell arising from the protodermal cells of the outer integument layer of the seed coat. Like all living plant cells, developing cotton fibers respond individually to fluctuations in the macroand microenvironments. Thus, the fibers on a single seed constitute continua of fiber length, shape, cell-wall thickness, and physical maturity (Bradow et al., 1996b,c, 1997a). Environmental variations within the plant canopy, among the individual plants, and within and among fields ensure that the fiber population in each boll, indeed on each seed, encompasses a broad range of fiber properties and that every bale of cotton contains a highly variable population of fibers. Successful processing of cotton lint depends on appropriate management during and after harvest of those highly variable fiber properties that have been shown to affect finished-product quality and manufacturing efficiency (Bradow et al., 1996b). If fiber-blending strategies and subsequent spinning and dyeing processes are to be optimized for specific end-uses and profitability, production managers in textile mills need accurate and effective descriptive and predictive quantitative measures of both the means and the ranges of these highly variable fiber properties (Moore, 1996). In the USA, the components of cotton fiber quality are usually defined as those properties reported for every bale by the classing offices of the USDA-AMS, which currently include length, length uniformity index, strength, micronaire, color as reflectance (Rd) and yellowness (+b), and trash content, all quantified by the High Volume Instrument (HVI) line. The classing offices also provide each bale with the more qua litative classers’ color and leaf grades and with estimates of preparation (degree of roughness of ginned lint) and content of extraneous matter. The naturally wide variations in fiber quality, in combination with differences in end-use requirements, result in significant variability in the value of the cotton lint to the processor. Therefore, a system of premiums and discounts has been established to denote a specified base quality. In general, cotton fiber value increases as the bulkaveraged fibers increase in whiteness (+Rd), length, strength, and micronaire; and discounts are made for both low mike (micronaire less than 3.5) and high mike (micronaire more than 4.9). Ideal fiber-quality specifications favored by processors traditionally have been summarized thusly: “as white as snow, as long as wool, as strong as steel, as fine as silk, and as cheap as hell.” These 37 BRADOW AND DAVIDONIS: FIBER QUALITY, COTTON PRODUCTION, AND PROCESSING specifications are extremely difficult to incorporate into a breeding program or to set as goals for cotton producers. Fiber-classing technologies in use and being tested allow quantitation of fiber properties, improvement of standards for end-product quality, and, perhaps most importantly, creation of a fiberquality language and system of fiber-qua lity measurements that can be meaningful and useful to producers and processors alike. GENETIC POTENTIAL, GENETIC CONTROL, AND ENVIRONMENTAL VARIABILITY Improvements in textile processing, particularly advances in spinning technology, have led to increased emphasis on breeding cotton for both improved yield and improved fiber properties (Meredith and Bridge, 1972; Green and Culp, 1990; Patil and Singh, 1995). Studies of gene action suggest that, within upland cotton genotypes there is little non-additive gene action in fiber length, strength, and fineness (Meredith and Bridge, 1972); that is, genes determine those fiber properties. However, large interactions between combined annual environmental factors (primarily weather) and fiber strength suggest that environmental variability can prevent full realization of the fiberquality potential of a cotton genotype (Green and Culp, 1990). More recently, statistical comparisons of the relative genetic and environmental influences upon fiber strength suggest that fiber strength is determined by a few major genes, rather than by variations in the growth environment (May, 1999). Indeed, spatial variations of single fertility factors in the edaphic environment were found to be unrelated to fiber strength and only weakly correlated with fiber length (Bradow et al., 1999b,c; Johnson et al., 1999). Genetic potential of a specific genotype is defined as the level of fiber yield or quality that could be attained under optimal growing conditions. The degree to which genetic potential is realized changes in response to environmental fluctuations such as application of water or fertilizer and the inevitable seasonal shifts such as temperature, day length, and insolation. Season-related shifts in cotton plant metabolism and fiber properties take the form of higher levels of fiber maturation in upland and pima bolls from July flowers, compared with the maturity levels of fibers in bolls from August flowers on the same plants (Sassenrath-Cole and Hedin, 1996; Bradow et al., 1996c; Bradow et al., 1997a). Similar effects of environment on genetic potential have been quantified in plant and field maps of micronaire and maturity (Bradow et al., 1996b, 1999b; Johnson et al., 1999). In addition to environment-related modulations of fiber quality at the crop and whole-plant levels, significant differences in fiber properties also can be traced to variations among the shapes and matur ities of fibers on a single seed and, consequently, within a given boll. Comparisons of the fiber-length arrays from different regions on a single seed have revealed that markedly different patterns in fiber length can be found in the micropylar, middle, and chalazal regions of a cotton seed at either end and around the middle (Delanghe, 1986). Mean fiber lengths were shortest at the micropylar (upper, pointed end of the seed) in G. hirsutum, G. barbadense , and G. arboreum genotypes (Vincke et al., 1985). The most mature fibers and the fibers having the largest perimeters also were found in the micropylar region of the seed. After hand ginning, the percentage of short fibers less than 0.5 inch or 12.7 mm long on a cotton seed was extremely low. It has been reported that, in ginned and baled cotton, the short fibers with small perimeters did not originate in the micropylar region of the seed (Vincke et al., 1985; Delanghe, 1986). Further, AFIS-A2 (Advanced Fiber Information System, Model A-2, Zellweger, Knoxville, TN) measurements of fibers from micropylar and chalazal regions of seeds revealed that the location of a seed within the boll was related to the magnitude of the differences in the properties of fibers from the micropylar and chalazal regions (Davidonis and Hinojosa, 1994). Significant variations in fiber maturity also can be related to the seed position (apical, medial, or 1 Trade names are necessary for reporting factually on available data. The USDA neither guarantees nor warrants the standard of the product or the service. The use of the name USDA implies no approval of the product or service to the exclusion of others that may be suitable. 38 JOURNAL OF COTTON SCIENCE, Volume 4, Issue 1, 2000 basal) within the boll and locule. Degree of secondary wall thickening (quantified by the AFISA2 as the fiber cell-wall maturity measurem

/pdf/quantitation-of-fiber-quality-and-the-cotton-production-1ixqcsrnfb.pdf

Quantitation of fiber quality and the cotton production-processing interface: a physiologist's perspective.

From a review of published data on S- and N-fractions it has been shown that on a gram atom basis these elements occur in organic forms in a ratio ranging from 0.025 (legumes) to 0.032 (gramineous plants) and that this is the same as the S : N ratio in the proteins which constitute about 80 per cent of the organic S and N present. In plants deficient in sulphur, the ratio organic-S : organic-N becomes less than normal due to an increase in the proportion of non-protein organic-N compounds low in sulphur. With sulphur deficiency the cytoplasmic proteins decrease out of proportion to the chloroplast proteins of a higher S content so that the ratio of protein-S to protein-N tends to increase. A similar change may occur during the fall in tissue protein content with increasing plant age. Sulphur-deficient plants show a subnormal ratio of organic-S to organic-N in the absence of sulphate in the tissues. Plants in which the protein content is decreased by proteolysis may have subnormal organic-S : organic-S ratios in the presence of sulphate in the tissues,i.e. without S shortage. This may occur during dark starvation or in seedlings drawing upon reserve proteins in the seeds. The S-requirements for growth are reflected in the normal ratio of organic-S to organic-N. In most species investigated, organic-S occurs mainly as cystine and methionine and is directly related to protein metabolism. Because of the presence of other forms of organic-S, the organic-S : organic-N ratio in the Brassica species is higher.

The sulphur requirements of plants as evidenced by the sulphur - nitrogen ratio in the organic matter : a review of published data

Studies on the Nutrition of Forest Tree Seedlings. III Mineral Nutrition of Pine

http://www.plantphysiol.org/content/plantphysiol/26/4/639.full.pdf

Sulphur nutrition of cotton.

20. SABLE, H. Z. Pentose metabolism in extracts of yeast and mammalian tissues. Biochim. Biophys. Acta 8: 687-697. 1952. 21. SEEGMILLER, J. E. and HORECKER, B. L. The synthesis of glucose-6-phosphate and 6-phosphogluconate. Jour. Biol. Chem. 192: 175-180. 1951. 22. STUMPF, P. K. Breakdown of fructose diphosphate by pea extracts. Jour. Biol. Chem. 182: 261-272. 1950. 23. STUMPF, P. K. Glycolytic enzymes in higher plants. Ann. Rev. Plant Physiol. 3: 17-34. 1952. 24. TEWFiK, S. and STUMPF, P. K. Enzymic oxidation of fructose diphosphate. Jour. Biol. Chem. 192: 527-533. 1951.

Effects of Shade and Partial Defoliation on Carbohydrate Levels and the Growth, Fruiting and Fiber Properties of Cotton Plants.

Aspects of Phosphorus Metabolism in the Cotton Plant.

Compositional Factors Associated with the Growth Responses of Young Cotton Plants to Gibberellic Acid.

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

David R. Ergle

Author Tools

Chat about Author

Papers

Sulphur nutrition of cotton.

Effects of Shade and Partial Defoliation on Carbohydrate Levels and the Growth, Fruiting and Fiber Properties of Cotton Plants.

Aspects of Phosphorus Metabolism in the Cotton Plant.

Compositional Factors Associated with the Growth Responses of Young Cotton Plants to Gibberellic Acid.