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VOLUME O NE HUN DRED T HIRTEE N ADVANCES IN AGRONOMY ADVANCES IN AGRONOMY Advisory Board PAUL M BERTSCH RONALD L PHILLIPS University of Kentucky University of Minnesota KATE M SCOW LARRY P WILDING University of California, Davis Texas A&M University Emeritus Advisory Board Members JOHN S BOYER KENNETH J FREY University of Delaware Iowa State University EUGENE J KAMPRATH MARTIN ALEXANDER North Carolina State University Cornell University Prepared in cooperation with the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America Book and Multimedia Publishing Committee DAVID D BALTENSPERGER, CHAIR LISA K AL-AMOODI CRAIG A ROBERTS WARREN A DICK MARY C SAVIN HARI B KRISHNAN APRIL L ULERY SALLY D LOGSDON VOLUME O NE HUN DRED T HIRTEE N ADVANCES IN AGRONOMY EDITED BY DONALD L SPARKS Department of Plant and Soil Sciences University of Delaware Newark, Delaware, USA AMSTERDAM  BOSTON  HEIDELBERG  LONDON NEW YORK  OXFORD  PARIS  SAN DIEGO SAN FRANCISCO  SINGAPORE  SYDNEY  TOKYO Academic Press is an imprint of Elsevier Academic Press is an imprint of Elsevier 525 B Street, Suite 1900, San Diego, CA 92101-4495, USA 225 Wyman Street, Waltham, MA 02451, USA 32 Jamestown Road, London, NW1 7BY, UK Radarweg 29, PO Box 211, 1000 AE Amsterdam, The Netherlands First edition 2011 Copyright r 2011 Elsevier Inc All rights reserved No part of this publication may be reproduced, stored a retrieval system or transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without the prior written permission of the publisher Permissions may be sought directly from Elsevier’s Science & Technology Rights Department in Oxford, UK: phone (144) (0) 1865 843830; fax (144) (0) 1865 853333; email: permissions@elsevier.com Alternatively you can submit your request online by visiting the Elsevier web site at http://elsevier.com/locate/permissions, and selecting Obtaining permission to use Elsevier material Notice No responsibility is assumed by the publisher for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions or ideas contained in the material herein Because of rapid advances in the medical sciences, in particular, independent verification of diagnoses and drug dosages should be made ISBN: 978-0-12-386473-4 ISSN: 0065-2113 (series) For information on all Academic Press publications visit our website at elsevierdirect.com Printed and bound in USA 11 12 13 14 10 CONTENTS Contributors Preface Advances in Agronomy Quantifying Processes of Pedogenesis ix xi Uta Stockmann, Budiman Minasny, and Alexander McBratney Introduction Conceptual Models of Soil Formation—Factors, Processes, Pathways, Energy Soil Weathering and Production Soil Mixing—Vertical and Lateral Movements Models of Soil Formation Based on the Concept of Mass Balance Conclusions Appendix References 12 22 33 39 46 68 Irrigation Waters as a Source of Pathogenic Microorganisms in Produce: A Review 75 Yakov Pachepsky, Daniel R.Shelton, Jean E.T McLain, Jitendra Patel, and Robert E Mandrell Introduction Concentrations of Microbial Pathogens and Indicator Organisms in Irrigation Waters Implications of Irrigation Water in Spread of Foodborne Diseases Standards, Guidelines, and Risk Assessment Fate and Transport of Pathogenic and Indicator Microorganisms in Irrigation Systems Management and Control of Produce Contamination with Pathogens from Irrigation Waters Research and Development Needs References 76 78 84 91 101 117 121 123 Quo Vadis Soil Organic Matter Research? A Biological Link to the Chemistry of Humification 143 Morris Schnitzer and Carlos M Monreal Introduction Criticism on Soil HS Research 145 147 v vi Contents 10 Extraction of SOM Analysis of SOM Analysis by Py-FIMS Chemical Structure Chemical Characteristics of HS Spectrometric and Spectroscopic Characteristics of HS Effect of Time on the SOM Structure New Concepts on the Chemical and Microbial Synthesis of HAs and SOM 11 Microbial Humification of Small Organic Compounds into Soil PKs 12 Thermodynamic, Energy, and Kinetic Considerations 13 PKs and the Central Structure of HS and SOM 14 Future Research References 148 150 152 155 156 160 179 180 181 198 202 205 207 Zeolites and Their Potential Uses in Agriculture 219 Kulasekaran Ramesh and Dendi Damodar Reddy Origin and History of Zeolites Classification of Zeolites Structure and Nomenclature of Zeolites Physical and Chemical Properties of Zeolites Major Natural Zeolites of Agricultural Importance Zeolite Nutrient Interactions Agricultural Applications Researchable Issues Conclusions References 221 222 223 224 227 227 229 235 235 235 Proximal Soil Sensing: An Effective Approach for Soil Measurements in Space and Time 243 R.A Viscarra Rossel, V.I Adamchuk, K.A Sudduth, N.J McKenzie, and C Lobsey Introduction Proximal Soil Sensing Techniques Proximal Sensors Used to Measure Soil Properties Summary General Discussion and Future Aspects References 245 251 270 274 274 281 Contents The Role of Knowledge When Studying Innovation and the Associated Wicked Sustainability Problems in Agriculture vii 293 J Bouma, A.C van Altvorst, R Eweg, P.J.A.M Smeets, and H.C van Latesteijn Introduction Current Problems in Dutch Agriculture The Flow of Knowledge When Studying Sustainable Development Case Studies Discussion and Conclusions References 294 299 300 301 319 321 Crops Yield Increase Under Water-Limited Conditions: Review of Recent Physiological Advances for Soybean Genetic Improvement 325 Walid Sadok and Thomas R Sinclair Introduction Crop Water Use and Yield: A Framework for Trait Identification Traits Influencing Water Conservation Traits Influencing Water Access Traits for Special Sensitivities: Nitrogen Fixation Tolerance to Drought Concluding Remarks References Index 326 327 331 339 342 344 345 351 CONTRIBUTORS Numbers in Parentheses indicate the pages on which the authors’ contributions begin V.I Adamchuk (241) Bioresource Engineering Department, McGill University, Ste-Anne-de-Bellevue, QC, Canada J Bouma (291) Professor of Soil Science, Wageningen University, The Netherlands Dendi Damodar Reddy (217) Central Tobacco Research Institute (ICAR), Rajamundry, Andhra Pradesh, India R Eweg (291) TransForum Innovation Program, The Netherlands C Lobsey (241) CSIRO Land and Water, Bruce E Butler Laboratory, Canberra, ACT, Australia Robert E Mandrell (73) USDA-ARS, Western Regional Research Center, Produce Safety and Microbiology Research Unit, Albany, CA Alexander McBratney (1) Faculty of Agriculture, Food and Natural Resources, The University of Sydney, Sydney, NSW, Australia N.J McKenzie (241) CSIRO Land and Water, Bruce E Butler Laboratory, Canberra, ACT, Australia Jean E.T McLain (73) USDA-ARS Arid-Land Agricultural Research Center, Water Management and Conservation Research Unit, Maricopa, AZ Budiman Minasny (1) Faculty of Agriculture, Food and Natural Resources, The University of Sydney, Sydney, NSW, Australia Carlos M Monreal (141) Agriculture and Agri-Food Canada, Eastern Cereal and Oilseed Research Center, Ottawa, ON, Canada ix x Contributors Yakov Pachepsky (73) USDA-ARS Beltsville Agricultural Research Center, Environmental Microbial and Food Safety Laboratory, Beltsville, MD Jitendra Patel (73) USDA-ARS Beltsville Agricultural Research Center, Environmental Microbial and Food Safety Laboratory, Beltsville, MD Kulasekaran Ramesh (217) Indian Institute of Soil Science (ICAR), Nabibagh, Bhopal, Madhya Pradesh, India Walid Sadok (323) Earth and Life Institute, Universite´ Catholique de Louvain, Louvain-la-Neuve, Belgium Morris Schnitzer (141) Agriculture and Agri-Food Canada, Eastern Cereal and Oilseed Research Center, Ottawa, ON, Canada Daniel R Shelton (73) USDA-ARS Beltsville Agricultural Research Center, Environmental Microbial and Food Safety Laboratory, Beltsville, MD Thomas R Sinclair (323) Crop Science Department, North Carolina State University, Raleigh, NC P.J.A.M Smeets (291) Alterra, Wageningen University and Research Center, The Netherlands Uta Stockmann (1) Faculty of Agriculture, Food and Natural Resources, The University of Sydney, Sydney, NSW, Australia K.A Sudduth (241) USDA Agricultural Research Service, Cropping Systems and Water Quality Research, Columbia, MO A.C van Altvorst (291) Professor of Soil Science, Wageningen University, The Netherlands H.C van Latesteijn (291) TransForum Innovation Program, The Netherlands R.A Viscarra Rossel (241) CSIRO Land and Water, Bruce E Butler Laboratory, Canberra, ACT, Australia 344 Walid Sadok and Thomas R Sinclair displayed much higher N2 fixation rates than parent KS 4895 when soil dried to low levels, that is, low FTSW Likely, there is still more potential to improve NFDT in soybean Sinclair et al (2000) identified in a screen of 3500 plant introduction lines that eight genotypes exhibited substantial NFDT, exceeding that of Jackson, which is the parent of the already released germplasm Also, mechanisms other than ureide metabolism are involved in NFDT (reviewed in Serraj et al., 1999b) and can be potentially exploited, including carbon flux in nodules (Ladrera et al., 2007), nodule permeability to oxygen (King and Purcell, 2001), or feedback regulation (King and Purcell, 2005) Concluding Remarks In this review, it is suggested that traits improving drought tolerance in soybean can be one of three types: improving access to water, limiting water loss, and overcoming certain sensitivities that are critical to productivity such as NFDT All of these fall within the limits of the concept of matching physiology to water supply, a generalization of one of the trait-concepts offered by Ludlow and Muchow (1990) For this concept to work as a framework for breeding for drought tolerance in crops, the following considerations have to be taken into account As indicated by Eq (1) and Fig 4, it is critical to keep in mind that the highest yields can only be achieved in nonwater-limited environments (Phase I in Fig 4) and that survival situations (Phase III in Fig 4) are often not economically viable This narrows the window of opportunities where it is still possible to manipulate traits pertaining to one of the three above subcategories while guaranteeing yields that are economically meaningful to the grower It is suggested that in breeding efforts or trait discovery enterprises, such economic considerations must be considered A key consideration in any approach aimed at breeding for drought tolerance is development of a full understanding of the physiological traits involved in response to water deficits Through a set of specific experiments, physiological studies should help in at least identifying how traits operate with respect to water saving, accessing more water, or in terms of overcoming some special sensitivities The results of the physiological studies would also be very beneficial in implementing models to quantitatively assess trait impact on yield in different environments Increased probability of improving drought tolerance is likely to result from combining the above effort with other interdisciplinary approaches involving: (i) the dissection of the genetic and—when relevant—the Crops Yield Increase Under Water-Limited Conditions 345 molecular basis of these traits and (ii) high throughput phenotyping methods in the both field and laboratory It is such interdisciplinary effort that has led recently to the identification of new drought tolerance traits in soybean such as “slow-wilting” (Charlson et al., 2009; King et al., 2009), limited TR (Fletcher et al., 2007; Sinclair et al., 2008), and NFDT (Chen et al., 2007; Sinclair et al., 2007), some of which having led to the development of new cultivars ACKNOWLEDGMENT The authors are thankful for the financial support during the preparation of this review from the United Soybean Board REFERENCES Blizzard, W E., & Boyer, J S (1980) Comparative resistance of the soil and the plant to water transport Plant Physiology, 66, 809À814 Blum, A (2009) Effective use of water (EUW) and not water-use efficiency (WUE) is the target of crop yield improvement under drought stress Field Crops Research, 112, 119À123 Bruinsma, J (2009) The resource outlook to 2050: By how much land water and crop yield need to increase by 2050? 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phenotyping methods for screening wheat and barley for beneficial responses to water deficit Journal of Experimental Botany, 61, 3499À3507 Parry, M A J., Reynolds, M., Salvucci, M E., Raines, C., Andralojc, P J., Zhu, X -G., et al (2011) Raising yield potential of wheat II Increasing photosynthetic capacity and efficiency Journal of Experimental Botany, 62, 453À467 Passioura, J B (1972) The effect of root geometry on the yield of wheat growing on stored water Australian Journal of Agricultural Research, 23, 745À752 Passioura, J B (1983) Roots and drought resistance Agricultural Water Management, 7, 265À280 Passioura, J B., & Angus, J F (2010) Improving productivity of crops in water-limited environments Advances in Agronomy, 106, 37À75 Purcell, L C., & King, C A (1996) Drought and nitrogen source effects on nitrogen nutrition, seed growth, and yield in soybean Journal of Plant Nutrition, 19, 969À993 Purcell, L C., & Specht, J E (2004) Physiological traits for ameliorating drought stress In H R Boerma & J E Specht (Eds.), Soybeans: Improvement, production, and uses (pp 569À620) Madison, WI: ASA, CSSA, and SSSA Purcell, L C., King, C A., & Ball, R A (2000) Soybean cultivar differences in ureides and the relationship to drought tolerant nitrogen fixation and manganese nutrition Crop Science, 40, 1062À1070 Raper, C D., Jr., & Barber, S A (1970) Rooting systems of soybeans I Differences in root morphology among varieties Agronomy Journal, 62, 581À584 Ray, J D., Gesch, R W., Sinclair, T R., & Allen, L H (2002) The effect of vapor pressure deficit on maize transpiration response to drying soil Plant Soil, 239, 113À121 Ray, J D., Heatherly, L G., & Fritschi, F B (2006) Influence of large amounts of nitrogen on non-irrigated and irrigated soybean Crop Science, 46, 52À60 Reymond, M., Muller, B., Leonardi, A., Charcosset, A., & Tardieu, F (2003) Combining quantitative trait loci analysis and an ecophysiological model to analyze the genetic variability of the responses of maize leaf growth to temperature and water deficit Plant Physiology, 131, 664À675 Richards, R A., & Passioura, J B (1989) A breeding program to reduce the diameter of the major xylem vessel in the seminal roots of wheat and its effect on grain yield in rain-fed environments Australian Journal of Agricultural Research, 40, 943À950 Rincon, C A., Raper, C D., Jr., & Patterson, R P (2003) Genotypic differences in root anatomy affecting water movement through roots of soybean International Journal of Plant Sciences, 164, 543À551 Sadok, W., & Sinclair, T R (2009a) Genetic variability of transpiration response to vapor pressure deficit among soybean (Glycine max [L.] Merr.) cultivars Crop Science, 49, 955À960 Sadok, W., & Sinclair, T R (2009b) Genetic variability of transpiration response to vapor pressure deficit among soybean (Glycine max [L.] Merr.) genotypes selected from a recombinant inbred line population Field Crops Research, 113, 156À160 Sadok, W., & Sinclair, T R (2010) Transpiration response of “slow-wilting” and commercial soybean (Glycine max (L.) Merr.) genotypes to three aquaporin inhibitors under high evaporative demand Journal of Experimental Botony, 61, 821À829 Sadok, W., Naudin, P., Boussuge, B., Muller, B., Welcker, C., & Tardieu, F (2007) Leaf growth rate per unit thermal time follows QTL-dependent daily patterns in hundreds of maize lines under naturally fluctuating conditions Plant, Cell and Environment, 30, 135À146 Salih, A A., Ali, I A., Lux, A., Luxova, M., Cohen, Y., Sugimoto, Y., et al (1999) Rooting, water uptake, and xylem structure adaptation to drought of two sorghum cultivars Crop Science, 39, 168À173 348 Walid Sadok and Thomas R Sinclair Sall, K., & Sinclair, T R (1991) Soybean genotypic differences in sensitivity of symbiotic nitrogen fixation to soil dehydration Plant Soil, 133, 31À37 Serraj, R., & Sinclair, T R (1997) Variation among soybean cultivars in dinitrogen fixation response to drought Agronomy Journal, 89, 963À969 Serraj, R., & Sinclair, T R (2002) Osmolyte accumulation: Can it really help increase crop under drought conditions? Plant, Cell and Environment, 25, 333À341 Serraj, R., Dimayuga, G., Gowda, V., Guan, Y., He, H., Impa, S., et al (2008) Drought-resistant rice Physiological framework for an integrated research strategy In R Serraj, J Bennett, & R Hardy (Eds.), Drought frontiers in rice—Crop improvement for increased rainfed production Singapore: World Scientific Publishing Serraj, R., Kumar, A., McNally, K L., Slamet-Loedin, I., Bruskiewich, R., Mauleon, R., et al (2009) Improvement of drought resistance in rice Advances in Agronomy, 103, 41À99 Serraj, R., Sinclair, T R., & Purcell, L C (1999a) Symbiotic N2 fixation response to drought Journal of Experimental Botony, 50, 143À155 Serraj, R., Vadez, V., Denison, R F., & Sinclair, T R (1999b) Involvement of ureides in nitrogen fixation inhibition in soybean Plant Physiology, 119, 289À296 Sinclair, T R (1986) Water and nitrogen limitations in soybean grain production I Model development Field Crops Research, 15, 125À141 Sinclair, T R (2000) Model analysis of plant traits leading to prolonged crop survival during severe drought Field Crops Research, 68, 211À217 Sinclair, T R (2007) Optimizing water use efficiency in soybean crops XIV Congress of AAPRESID, 14À17 (Rosario, Argentina) Sinclair, T R (2010) Precipitation: The thousand-pound gorilla in crop response to climate change In D Hillel & C Rosenzweig (Eds.), Handbook of climate change and agroecosystems (pp 179À190) London: Imperial College Press Sinclair, T R., & deWit, C T (1975) Photosynthate and N requirements for seed production by various crops Science, 189, 565À567 Sinclair, T R., & Ludlow, M M (1986) Influence of soil water supply on the plant water balance of four tropical grain legumes Australian Journal of Plant Physiology, 13, 329À341 Sinclair, T R., & Muchow, R C (2001) System analysis of plant traits to increase grain yield on limited water supplies Agronomy Journal, 93, 263À270 Sinclair, T R., & Serraj, R (1995) Legume nitrogen fixation and drought Nature, 378, 344 Sinclair, T R, Hammer, G L., & van Oosterom, E J (2005) Potential yield and water-use efficiency benefits in sorghum from limited maximum transpiration rate Functional Plant Biology, 32, 945À952 Sinclair, T R., Messina, C D., Beatty, A., & Samples, M (2010) Assessment across the United States of the benefits of altered soybean drought traits Agronomy Journal, 102, 475À482 Sinclair, T R., Purcell, L C., King, C A., Sneller, C H., Chen, P., & Vadez, V (2007) Drought tolerance and yield increase of soybean resulting from improved symbiotic N2 fixation Field Crops Research, 101, 68À71 Sinclair, T R., Purcell, L C., Vadez, V., Serraj, R., King, C A, & Nelson, R (2000) Identification of soybean genotypes with N2 fixation tolerance to water deficits Crop Science, 40, 1803À1809 Sinclair, T R., Zwieniecki, M A., & Holbrook, N M (2008) Low leaf hydraulic conductance associated with drought tolerance in soybean Plant Physiology, 132, 446À451 Sloane, R J., Patterson, R P., & Carter, T E (1990) Field drought tolerance of a soybean plant introduction Crop Science, 30, 118À123 Spaeth, S C., Randall, H C., Sinclair, T R., & Vendeland, J S (1984) Stability of soybean harvest index Agronomy Journal, 76, 482À486 Crops Yield Increase Under Water-Limited Conditions 349 Sperry, J S (2000) Hydraulic constraints on plant gas exchange Agriculture and Forest Meteorology, 104, 13À23 Sperry, J S., Stiller, V., & Hacke, U G (2003) Xylem hydraulics and the soilÀplantÀatmosphere continuum: Opportunities and unresolved issues Agronomy Journal, 95, 1362À1370 Tanner, C B., & Sinclair, T R (1983) Efficient water use in crop production: Research or re-search In H M Taylor, W R Jordan, & T R Sinclair (Eds.), Limitations to efficient water use in crop production (pp 1À27) Madison, WI: ASA, CSSA, and SSSA Tardieu, F (2005) Plant tolerance to water deficit: Physical limits and possibilities for progress Comptes Rendus Geosciences, 337, 57À67 Taylor, H M (1980) Modifying root systems of cotton and soybean to increase water absorption In N C Turner & P J Kramer (Eds.), Adaptation of plants to water and high temperature stresses (pp 75À84) New York, NY: John Wiley and Sons Vadez, V., & Sinclair, T R (2002) Sensitivity of N2 fixation traits in soybean cultivar Jackson to manganese Crop Science, 42, 791À796 Vadez, V., Sinclair, T R., & Serraj, R (2000) Asparagine and ureide accumulation in nodules and shoots as feedback inhibitors of N2 fixation in soybean Plant Physiology, 110, 215À223 Yamaguchi, M., & Sharp, R E (2010) Complexity and coordination of root growth at low water potentials: Recent advances from transcriptomic and proteomic analyses Plant, Cell and Environment, 33, 590À603 Index A ABA See Applied behavior analysis Absolute gravimetry, 262 Acoustic sensors, 266 Active γ-ray sensors, 251 Adenosine triphosphate (ATP), 198 Ad hoc wireless networking, 267 Aeromonas in bottom sediments, 107À108 in treated wastewater plants, 101À102 Aeromonas hydrophila, 107À108 Agricultural applications, of zeolites, 229À234 crop yields, improving, 233 heavy metal contaminated soils, remediation of, 233À234 herbicide use efficiency, improving, 233 nitrogen use efficiency, enhancing, 230À231 organic manure efficiency, enhancing, 232À233 phosphorus use efficiency, improving, 232 soil physico-chemical and microbial properties, improving, 230 wastewater treatment, 234 water use efficiency, improving, 233 Amebae, 114 Ammonium trapping, 228À229 rock phosphate dissolution, 229 Animal husbandry practices microbial pollution in irrigation waters, 118 Antibiotics effects, on soil microbial activity, 194À196 Antimony electrodes, 264 Applied behavior analysis (ABA), 337, 342 Aquaporins (AQPs), 334À335 Aquatic biota, 114À115 Arabidopsis thaliana, 334 Arachis hypogea L., 337 ATP See Adenosine triphosphate (ATP) Australia, study sites in, 25, 26, 50t, 61t B Bacillus cereus, 76À77 Bank soils, 113À114 Barley, VPD in, 334 Biofilms control of, in irrigation water, 119 environmental microbial reservoirs, 115À117 Biota, 17 Biotic humification, 196À198, 203À205 Bioturbation, 24À30 faunaturbation, 27À29 floraturbation, 29À30 horizonation and haplodization, 27 Macquarie school research, 25 pedology, 26 stone layer formation, 27 Biphasic decay, 103, 104f Bottom sediments, 112À113 environmental microbial reservoirs, 107À111 Brachiaria decumbens, 232 C Campylobacter inactivation patterns, 106À107 in aquatic biota, 114, 114 in bottom sediments, 107À111 in irrigation water, 76À77, 79, 82À83 Capacitance sensors, 257, 258 Carbon, measurement of, 272 Cation exchange capacity (CEC), 272 CEC See Cation exchange capacity Central unit structure (CUS), 192, 203À205 Chabazite, 227 Chalcone synthase (CHS), 191À192 CHEMFETs, 264 Chemical weathering Bega Valley, 21 of bedrock, 18À22 box plot distributions of, 23f field sites, 21À22 laboratory studies, 18 rates (CWR), 46t saprolite, 20À21 soil mantle, 17À18 351 352 Chemical weathering (Continued) soil mixing rates and, 32f soil residence time, 21 supply limited weathering, 20À21 and total denudation rate, 50t watershed studies, 19 weathering indices, 20 ChemPlus, 173À174, 178 CHS See Chalcone synthase Clinoptilolite, 222, 224, 227 agricultural importance of, 227 chemical composition of, 225t “Clorpt” model, Clostridium botulinum, 107À108 Clostridium perfringens, 88 13 C NMR spectra CP-MAS, 161 hot acid hydrolysis, 162À164 of humic acids, 160À161, 162À164 of humic substances, 160À162 of whole soils, 150À151, 151f Communities of Practice (CoPs), 295 Communities of Scientific Practice (CSPs), 295 Community Supported Agriculture (CSA), 77 Connected value development, 298, 304À305, 308À309, 318, 319 Contact electrodes, 262À264 electrical resistivity, 263 electrochemical sensors, 263 induced polarization, 263 ion-selective electrodes, 263À264 ion-selective field effect transistors, 264 metal electrodes, 264 Contamination risks, management of, 101f, 117À121 CoPs See Communities of Practice Core scanning and borehole sensors, 269, 270f CpÀGCÀMs See Curie-point pyrolysis-gas chromatography-mass spectrometry CP-MAS See Cross polarization magic angle spinning Cradle-to-Cradle (C2C) concept, 301À302 Critical zone, 2, 3f, definition of, Cronstedt, Alex Fredrik, 221À222 Crop restriction, 120 Crop water use and yield, 327À331 NFDT genetic variability, 343À344 Index physiological basis, 343 R01-416F and R01-581F, 343À344 nitrogen fixation tolerance to drought, 342À344 trait identification harvest index, 330À331 transpiration coefficient k, 329À330 vapor pressure deficit, 331 water access, 339À342 decreased root hydraulic conductance, 341 increased rooting depth, 339À340 increased rooting rate, 340À341 rooting traits, 342 water conservation, 331À339 limited TR and slow-wilting, 331À335 slow leaf area development, 337À338 stomatal closure timing, in soil drying cycle, 336À337 water conservation traits, 338À339 Cross polarization magic angle spinning (CPMAS), 160À161 Cryptosporidium in bottom sediments, 107À108 fate and transport, 102 food poisoning outbreaks and, 85À86 in irrigation water, 76À77, 79, 82À83 CSA See Community Supported Agriculture CSPs See Communities of Scientific Practice Culp soil, 150, 151f Curie-point pyrolysis-gas chromatography-mass spectrometry (CpÀGCÀMs), 164À166 CUS See Central unit structure Cyclospora cayetanensis, 76À77, 85À86 D Darwin, Charles, 26 DEM See Digital elevation model Deoxyerythronolide-B-synthase, 187f Desulfovibrio, 198À199 DGPS See Differential global positioning systems Differential global positioning systems (DGPS), 267À268 Diffuse reflectance spectroscopy, 254 Digisoil, 280 Digital elevation model (DEM), 267À268 Dokuchaev, V.V., 6À7 Down-borehole sensor systems, 269 Drinking water distribution systems, 116 Drop in transpiration, 335f Dutch agriculture, current problems in, 299À300 353 Index E Earthworms, bioturbation rates for, 25À26 Earth’s surface, definition of, 2À3 “8-Ring” structure, 224 Electrical conductivity of soil, 260, 261 Electrical resistivity (ER), of soil, 263 Electrochemical sensors, 263 Electromagnetic (EM) spectrum, 245f Electromagnetic induction (EMI), 260À261 EMI See Electromagnetic induction Endopedonic agents, 27 Energy, kinetic, and thermodynamic relationships, in soil systems, 198À202 Entamoeba histolytica, 76À77 Enteric communicable diseases, 89À90 Environmental microbial reservoirs aquatic biota, 114À115 bank soils, 113À114 biofilms, 115À117 bottom sediments, 107À111 resuspension of sediments, 111À113 Erionite, 227 Escherichia coli adherence to plants, 88 in aquatic biota, 114 bank soils, 113 in bottom sediments, 108, 109À111 fate and transport, 102 food poisoning outbreaks and, 85À86, 87 inactivation phase, 103, 104f, 106À107 in irrigation water, 76À77, 78À79, 82 nutrients and, 105 pathways into plants, 87À88 pH and, 105 resuspension of sediments, 111À112 sunlight and, 106 Exopedonic agents, 27 Exponential soil production model, 15À16 Exposure model, QMRA, 98À99 Extra-large-pore zeolites, 223 F FA See Fluvic acid Faunaturbation, 27À29 FC See Fecal coliform FDR See Frequency-domain reflectometry Fecal coliform (FC), 79, 91 in sediment, 108, 109À111 FET See Field effect transistor Field effect transistor (FET), 264 Flavonoids, 191À192 Floraturbation, 29À30 Foodborne diseases, irrigation waters and, 84À90 “cause-effect” relationships, 84 epidemiological investigations, 85À86 increased incidence with high concentrations of pathogens, 89À90 pathogens in produce irrigated with contaminated water, 87À89 adherence to plants, 88 concentration, effect of, 88À89 pathogen pathways into plants, 87À88 Fraction of transpirable soil water (FTSW), 336 Frequency-domain reflectometry (FDR), 257À258 FTSW See Fraction of transpirable soil water Fulvic acid (FA) definition of, 148À149 Infrared and Fourier transform infrared spectrophotometry, 156À157 oxidative degradation of, 157À160 Py-FIMS spectrum of, 152, 153f X-ray analysis of, 167À170 proposed structures based on, 169À170 radial distribution analysis, 167À169 γ-ray spectrometer, 251À253 active, 251 passive, 251À252, 252f G Geographic positioning and elevation, 267À268 Giardia in bottom sediments, 107À108 fate and transport, 102 in irrigation water, 76À77, 79, 82À83 Glicotoxin, 195 Gliocladium virens, 195 Glycine max (L.) Merr., 326 GPR See Ground-penetrating radar Gravimetric sensors, 262 Green care, case study, 309À315 flow of knowledge, 314 knowledge management, 314À315 players involvement, 310À311 problems and objectives, 309À310 track record of, 311À313, 312f Ground-penetrating radar (GPR), 259À260, 260f 354 Index H HA See Humic acids Haploidization, 27 Harvest index (HI), 330À331 Harvest interval, 120 Helicobacter pylori, 114 Heulandite, 224, 227 HI See Harvest index Hordeum vulgare L., 334 Horizonation, 27 HS See Humic substances Humic acids (HAs) 13 C NMR spectra of, 160À161, 161f effect of hot acid hydrolysis on, 162À164 analytical characteristics of, 156 chemical and microbial synthesis of, 180À181 chemical structure of, 166f corrected 2D model, 175À177, 176f Curie-point pyrolysis-gas chromatographymass spectrometry (CpÀGCÀMS) of, 164À166 definition of, 148À149 Infrared (IR) and Fourier transform infrared (FTIR) spectrophotometry, 156À157 oxidative degradation of, 157À160 Py-FIMS analysis of, 152, 153f and SOM relationships between, 174À175 3D structure for, 172À174 2D structure for, 170À172, 176f X-ray analysis of, 167À170 Humic substances (HS) 13 C NMR spectrometry of, 160À162 effect of hot acid hydrolysis on, 162À164 benzenecarboxylic acid oxidative degradation products of, 158f chemical characteristics of, 156À160 analytical characteristics, 156 Infrared and Fourier transform infrared spectrophotometry, 156À157 oxidative degradation of, 157À160 reductive degradation, 160 chemical structure for, 159f corrected 2D HA model, 175À177 criticism on soil HS research, 147À148 Curie-point pyrolysis-gas chromatographymass spectrometry, 164À166 definition of, 145 phenolic oxidation products of, 159f relationships between HA and SOM, 174À175 3D model structure for SOM plus water, 177À178 3D structure, 172À174 2D structure, 170À172 X-ray analysis, 167À170 Humification stages, 145À146 Humin, 148À149 oxidative degradation of, 157À160 Humped soil production model, 16À18 I ICSU See International Council for Science Indicator organisms, in irrigation waters, 78À83 environmental microbial reservoirs, 107À117 aquatic biota, 114À115 bank soils, 113À114 biofilms, 115À117 bottom sediments, 107À111 resuspension of sediments, 111À113 fate and transport of, 101À117 inactivation patterns, 106À107 survival of, 103À107 Indigenous biota, 106 Induced polarization (IP) measurements, 263 Inelastic neutron scattering (INS), 252 Infectivity model, QMRA, 98À99 Infrared reflectance spectroscopy, 254À256 Innovation, in agriculture case studies, 301À318 Dutch agriculture, current problems in, 299À300 “knowledge paradox”, 295 and sustainable development knowledge flow role, 300À301 transdisciplinary approach, 295 INS See Inelastic neutron scattering International Council for Science (ICSU), 295 Ion-selective electrodes (ISEs), 263À264 Ion-selective field effect transistors (ISFETs), 264 Irrigation water foodborne diseases, spread of, 84À90 “cause-effect” relationships, 84 epidemiological investigations, 85À86 increased incidence with high concentrations of pathogens, 89À90 pathogens in produce irrigated with contaminated water, 87À89 355 Index pathogenic microorganisms in concentration, 78À83 contamination risks, management and control of, 101f, 117À121 developing vs developed countries, 80 environmental microbial reservoirs, 107À117 fate and transport of, 101À117 inactivation patterns, 106À107 indicator organism, 78À83 (see also Indicator organisms, in irrigation waters) local differences, 80À82 overview, 76À78 regional differences, 80À82 research and development, need for, 121À123 risk assessment, 98À100 spatial variabilities, 82À83 standards/guidelines, 91À100 survey, 79 survival of, 103À107 temporal variabilities, 82À83 ISEs See Ion-selective electrodes (ISEs) ISFETs See Ion-selective field effect transistors iSoil, 280 K KENGi partners, 295, 296, 298 connected value development, 298 transdisciplinary approach in, 319, 320 Knowledge brokers, 298 Knowledge types, 300À301, 300f L Landscape evolution models, 34À35 Large-pore zeolites, 223 Laser-induced breakdown spectroscopy (LIBS), 256, 256f Legionella, 101À102 LIBS See Laser-induced breakdown spectroscopy Listeria monocytogenes, 76À77 M Macquarie School of “bioturbation”, 25 Magnetic resonance sounding (Mrs), 259 Magnetic sensors, 261À262 Maize, 331À332, 334 Mass balance model, 37 Mechanical sensors, 264À266 acoustic sensors, 266 fluid permeability, 265À266 integrated draft, 264À265 mechanical resistance, 265 Medium-pore zeolites, 223 “Mesh” networking, 267 Metal electrodes, 264 Metropolitan agriculture, 299 Microbial PKSs model, for studying biotic humification in soils, 196À198 Microbial polyketides, 192À194, 206À207 Microwave sensors, 256À257 Mid-IR systems, 255 Mineralogy, measurement of, 273 Mordenite, 227 Mrs See Magnetic resonance sounding Multisensor systems, 268, 269f Mycobacterium, 114 Mycobacterium avium, 107À108 N N2 fixation drought tolerance (NFDT), 342À344, 343f Near-infrared (NIR) reflectance spectroscopy, 254À255 Neutron scattering, 252À253 New Mixed Farm and industrial ecology, case study, 305À309 flow of knowledge, 308À309 knowledge management, 309 players involvement, 306 problems and objectives, 305À306 track record of, 307À308, 307f NFDT See N2 fixation drought tolerance NGOs See Nongovernmental organizations Nitrate leaching, 228 Nitrification, 231À232 NMR See Nuclear magnetic resonance Nongovernmental organizations ( NGOs), 295 Northern Frisian Woods, case study, 301À305 Cradle-to-Cradle (C2C) concept, 301À302 flow of knowledge, 304À305 knowledge management, 305 players involvement, 302 problems and objectives, 301À302 track record of, 302À305, 303f NRC See National Research Council Nuclear magnetic resonance (NMR), 259 356 Index Nutrients bacteria survival and, 105 measurement of, 271À272 O On-the-go proximal soil sensors, 251, 265 On-the-go soil electromagnetic induction (EM-38) system, 261f Optically stimulated luminescence (OSL), 30, 43 Oryza sativa L., 326 OSL See Optically stimulated luminescence P Passive γ-ray sensors, 251À252 Pathogenic microorganisms in irrigation waters See Irrigation water, pathogenic microorganisms in Pathogen pathways into plants, 87À88 PAWC See Plant-available water capacity Pedogenesis, quantifying processes of conceptual models of soil formation, 5À12 energy, 10À12 factors, 5À8 pathways, 9À10 processes, 8À9 models of soil formation, based on concept of mass balance, 33À39 in landscape, 35À39 landscape evolution models, 34À35 soil mixing, 22À33 bioturbation, 24À30 faunaturbation, 27À29 floraturbation, 29À30 pedoturbation, 31 rain splash, 30À31 soil creep, 30 soil production, 12À22 exponential soil production model, 15À16 from parent materials, 13À18 humped soil production model, 16À18 soil weathering, 12À22 chemical weathering, of bedrock, 18À22 Pedoturbation, 13 forms and agents of, 24t modeling, 31 Penetration resistance of soil, 265 pH bacteria survival and, 105 measurement of, 272À273 Phillipsite, 227 Phosphorus measurement, 271 PKs See Polyketides PKSs See Polyketide synthases Plant-available water capacity (PAWC), 270À271 Polyketides (PKs) biosynthesis of, 184À189 and central structure of HS and SOM, 202À205 biotic humification process forming CUS of HS and SOM, 203À205 PKs as a passive SOM pool, 202À203 chemical analysis of, in soils, 184 chemical and functional features of, 183À184 chemical diversity of, 190f complex biological link to the chemistry of humification, 181À182 ecological function and associated genetic evolution of, 190À191 example of, 183f future research, 205À207 microbial PKs, 192À194 microbial PKSs model, for studying biotic humification in soils, 196À198 nature, 182 plant PKs, 191À192 in soils, 194À196 Polyketide synthases (PKSs), 185, 206 classification of, 185À188 microbial PKSs model for studying biotic humification in soils, 196À198 Potassium measurement, 271À272 Process water, 78À79 Proximal soil sensing (PSS) definition, 246À250 development status and approximate costs, 277t future aspects, 274À281 measurements, location of, 250 “on-the-go” system, 246À247 soil properties, measurement of, 270À274 carbon, 272 cation exchange capacity, 272 clay, silt, and sand, 273 mineralogy, 273 nutrients and elements, 271À272 pH, 272À273 soil strength, bulk density, and related properties, 273À274 soil water and related properties, 270À271 357 Index technologies, 248t, 251À269 contact electrodes, 262À264 core scanning and borehole sensors, 269, 270f electromagnetic induction (EMI), 260À261 frequency-domain reflectometry (FDR), 257À258 γ-rays, 251À253 geographic positioning and elevation, 267À268 gravimetric sensors, 262 ground-penetrating radar (GPR), 259À260, 260f infrared reflectance spectroscopy, 254À256 laser-induced breakdown spectroscopy (LIBS), 256 magnetic sensors, 261À262 mechanical sensors, 264À266 microwaves, 256À257 multisensor systems, 268 neutron scattering, 252À253 nuclear magnetic resonance (NMR), 259 radio waves, 257À261 seismic sensors, 262 telemetry, 266À267 time-domain reflectometry (TDR), 257À258 ultraviolet radiation, 254À256 visible radiation, 254À256 X-rays, 253 PSS See Proximal soil sensing Py-FIMS See Pyrolysis-field ionization mass spectrum Pyrolysis-field ionization mass spectrum (PyFIMS) compound classes identified, 155t, 154 of fulvic acid, 152, 153f of humic acids, 152, 153f of humin, 152À154, 153f of whole soil, 153f, 154 Q QMRA See Quantitative microbial risk assessment Quantitative microbial risk assessment (QMRA), 98À100 advantage of, 100 exposure model, 98À99 infectivity model, 98À99 R Radio waves, 257À261 Rainfall events, role of, 82À83 Rain splash, 30À31 Reflection seismology, 262 Regolith, 3, 18 Rendzinas, 13 Research and development, need for, 121À123 Restricted irrigation, 91À94 Rock phosphate dissolution, 229 “Rondeel” chicken housing system, case study, 315À318 flow of knowledge, 317À318 knowledge management, 318 players involvement, 315À316 problems and objectives, 315 track record of, 316À317, 316f S Salmonella adherence to plants, 88 in aquatic biota, 114 in bottom sediments, 107À108 fate and transport, 102 food poisoning outbreaks and, 85, 87 inactivation phase, 103, 104f, 106À107 in irrigation water, 76À77, 79 pathways into plants, 87À88 sunlight and, 106 Saprolite, 17, 21À22 SCAPS See Site characterization and analysis penetrometer system “Scorpan” model, Seismic sensors, 262 Shigella, 106À111 Site characterization and analysis penetrometer system (SCAPS), 268 Slope of the regression, 103, 104f Slow-wilting, 327, 344À345 and limited TR, 331À335 line N01-11136, 334À335, 335f line PI 416937, 334À335 line PI 471938, 341 Small-pore zeolites, 223 SMZ See Surfactant-modified zeolite Soil bulk density, measurement of, 273À274 Soil creep, 24À25, 30 Soil formation conceptual models, 5À12, 40t energy, 10À12 factors, 5À8 358 Soil formation (Continued) mechanistic models of, 3À5 pathways, 9À10 processes, 8À9 mass balance model, 33À39 landscape evolution models, 34À35 modeling in landscape, 35À39 Soil-forming factors, Soil mineralogy, 273 Soil mixing, 22À33 bioturbation, 24À30 faunaturbation, 27À29 floraturbation, 29À30 modeling pedoturbation, 31 rain splash, 30À31 rates of, 32f, 33f, 63t soil creep, 30 Soil organic matter (SOM) analysis of, 150À151 by 13C NMR, 150À151 in situ analysis in whole soils, 150 by Py-FIMS, 152À154 chemical and microbial synthesis of, 180À181 chemical structure of, 155À156 compound classes identified, 154 extraction of, 148À150 extractants, 149À150 with dilute base, 148À149 future research, 205À207 and humic acids, 174À175 structure, effect of time on, 179 3D model structure, for SOM plus water, 177À178 Soil production, 12À22 exponential soil production model, 15À16 humped soil production model, 16À18 from parent materials, 13À18 Soil production rates (SPRs), 16 Soil profile model, 36, 37 Soil properties, measurement of, 270À274 carbon, 272 cation exchange capacity, 272 clay, silt, and sand, 273 mineralogy, 273 nutrients and elements, 271À272 pH, 272À273 soil strength, bulk density, and related properties, 273À274 soil water and related properties, 270À271 Soil science, 45 Soil spectrum, in visible rage, 254, 255f Index Soil strength, measurement of, 273À274 Soil texture, measurement of, 273 Soil urease adsorption, 228 Soil water content, measurement of, 270À271 Soil weathering, 12À22 SOM See Soil organic matter Sorghum, 331À332, 339 Sorghum bicolor L., 331À332, 339 Soybean aquaporins (AQPs), 334À335 doseÀresponse curves, of drop in transpiration in, 335f drought-tolerant traits, 327, 328t genetic variability, 328t of TR response to VPD, 333f genotype R01-416F, 343À344 genotype R01-581F, 343À344 quantitative trait loci (QTL), 334 slow-wilting, 327, 344À345 and limited TR, 331À335 line N01-11136, 334À335, 335f line PI 416937, 334À335 line PI 471938, 341 SPRs See Soil production rates Standards for microbial quality of irrigation water, 91À98 Staphylococcus aureus, 76À77 Stilbite, 227 Streptomyces, 196 Streptomyces aureofaciens, 195 Streptomyces globisporus, 193, 203 Streptomyces rimosus, 195 Sunlight, 106 Surface NMR, 259 Surfactant-modified zeolite (SMZ), 231À232 Sustainable development, 295, 299À300 and innovation in agriculture, 293 cases studies, 301À318 knowledge flow role, 300À301 problems of, 296À297 TransForum program, 297À298, 299À300 Synthrophomonas wolfei, 198À199 T Tacit knowledge, 300À301, 320 TC See Total coliform TCN See Terrestrial cosmogenic nuclide TDR See Time-domain reflectometry Telemetry, 266À267 Terminal restriction fragment length polymorphism (TRFLP), 197 359 Index Terrestrial cosmogenic nuclide (TCN), 16, 20, 43 Tetracenomycin, 199 Time-domain reflectometry (TDR), 257À258 Total coliform (TC), 91 Total denudation rate, 20 TR See Transpiration rate “TransForum” innovation program, 297À298 Connected value development, 298 Transpiration coefficient k, for soybean, 329À330 Transpiration rate (TR) soybean genetic variability response to VPD, 333f Travel time, factors affecting, 81 TRFLP See Terminal restriction fragment length polymorphism Triketide pyrone, 199 Triticum aestivum L., 334 T-shaped skills, 319, 321 U UK Food Safety Agency, 120 Ultraviolet radiation, 254À256 Unrestricted irrigation, 91À94 V Value capture, 314À315, 317À318 connected value development, 298 objective, 298À299 Value creation, 314À315, 318 connected value development, 298 objective, 298À299 Value proposition, 314À315, 318 connected value development, 298 objective, 298À299 Vapor pressure deficit (VPD), 331 Vibrio cholerae, 114 Visible radiation, 254À256 VisÀNIR spectrometers, 255À256 VPD See Vapor pressure deficit W Well water, 81 Wireless sensor networks, 266À267 X X-rays, 253 X-ray diffraction (XRD), 253 X-ray fluorescence (XRF), 253 Xylem embolism, 338 Y Yersinia enterocolitica, 76À77, 106À107 Z Zea mays L., 331À332 Zeolites agricultural applications, 229À234 crop yields, improving, 233 heavy metal contaminated soils, remediation of, 233À234 herbicide use efficiency, improving, 233 nitrogen use efficiency, enhancing, 230À231 organic manure efficiency, enhancing, 232À233 phosphorus use efficiency, improving, 232 soil physico-chemical and microbial properties, improving, 230 wastewater treatment, 234 water use efficiency, improving, 233 agricultural importance of, 227 ammonium trapping, 228À229 rock phosphate dissolution, 229 chemical composition of, 225t classification of, 222À223 nutrient interactions nitrate leaching, 228 soil urease adsorption, 228 origin and history, 221À222 physical and chemical properties of, 224À227 researchable issues, 235 ... Canberra, ACT, Australia PREFACE Volume 113 of Advances in Agronomy continues the long-standing tradition of including an eclectic group of reviews on cutting-edge topics in the plant, soil, and environmental... a certain soil type and produce individual soil horizons (Continued) Advances in Agronomy Quantifying Processes of Pedogenesis Box (Continued ) In 2007, volume (Number 5) of the magazine Elements... yr21) At present, interdisciplinary research is focusing on exploring how chemical, physical, and biological processes work together within the weathering engine In 2006 a working group was formed,
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Xem thêm: Advances in agronomy volume 113 , Advances in agronomy volume 113 , 3 Oxidative degradation of HAs, FAs, and humins, 2 The sampling dilema - Where to measure using proximal soil sensors?, 3 Ultraviolet, visible, and infrared reflectance spectroscopy, 7 Magnetic, gravimetric, and seismic sensors, 8 Soil strength, bulk density, and related properties, 1 Case 1: Northern Frisian Woods: Cradle-to-Cradle dairy farming, 2 Case 2: The new mixed farm: an example of industrial ecology, 3 Green care: health care on the farm, 4 Case 4: Developing the new “Rondeel” chicken housing system

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