All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher. Permanganate Oxidizable Carbon Refl ects a ProcessedSoil Fraction that is Sensitive to Management Soil Biology & Biochemistry P articulate organic C and MBC are important C fractions that refl ect key processes such as nutrient cycling and availability, soil aggregation, and soil C accrual (Wardle, 1992;Six et al., 1998;Wander, 2004). A large number of studies have shown that both POC and MBC are sensitive to changes in management such as reduced tillage, cover cropping and land use (Cambardella and Elliott, 1992;Wardle, 1992;Wander and Bidart, 2000;Grandy and Robertson, 2007). Th is sensitivity has led to wide adoption of these methods in soil science as indicators of change in the soil ecosystem (Wander, 2004;Gil-Sotres et al., 2005;Kaschuk et al., 2010).As informative as POC and MBC are, they are expensive soil measures for most applications outside of a research setting. Although adaptations have been made to streamline the extraction process of POC (Marriott and Wander, 2006a) and MBC (Fierer et al., 2003), these methods remain costly due to the required labor and combustion analyzer to quantify the total C in the extracted fraction. In addition to the cost, there is a large degree of variation on how researchers extract

Cover crop–based organic rotational no-till soybean production has attracted attention from farmers, researchers, and other agricultural professionals because of the ability of this new system to enhance soil conservation, reduce labor requirements, and decrease diesel fuel use compared to traditional organic production. This system is based on the use of cereal rye cover crops that are mechanically terminated with a roller-crimper to create in situ mulch that suppresses weeds and promotes soybean growth. In this paper, we report experiments that were conducted over the past decade in the eastern region of the United States on cover crop–based organic rotational no-till soybean production, and we outline current management strategies and future research needs. Our research has focused on maximizing cereal rye spring ground cover and biomass because of the crucial role this cover crop plays in weed suppression. Soil fertility and cereal rye sowing and termination timing affect biomass production, and these factors can be manipulated to achieve levels greater than 8,000 kg ha−1, a threshold identified for consistent suppression of annual weeds. Manipulating cereal rye seeding rate and seeding method also influences ground cover and weed suppression. In general, weed suppression is species-specific, with early emerging summer annual weeds (e.g., common ragweed), high weed seed bank densities (e.g. > 10,000 seeds m−2), and perennial weeds (e.g., yellow nutsedge) posing the greatest challenges. Due to the challenges with maximizing cereal rye weed suppression potential, we have also found high-residue cultivation to significantly improve weed control. In addition to cover crop and weed management, we have made progress with planting equipment and planting density for establishing soybean into a thick cover crop residue. Our current and future research will focus on integrated multitactic weed management, cultivar selection, insect pest suppression, and nitrogen management as part of a systems approach to advancing this new production system.

A gronomy J our n al • Volume 110 , I ssue 1 • 2 018 1 T he goal of an N recommendation system is to accurately estimate the gap between the N provided by the soil and the N required by the plant. Accurately estimating this gap depends on the ability of the recommendation system to accurately estimate fi eld or subfi eld specifi c economically optimal nitrogen rates (EONR). Current recommendation systems are not as accurate as needed to provide consistently reliable estimates of N needs across years at the fi eld or subfi eld scale. Uncontrollable factors like temperature, rainfall timing, intensity and amount, and interactions of temperature and rainfall with factors such as N source, timing and placement, plant genetics, and soil characteristics combine to make N rate recommendations for an individual fi eld or rates for subfi elds a process guided as much by science as by the best professional judgement of farmers and farm advisors.Substantial evidence has accumulated that EONRs can vary widely across fi elds, within fi elds and over years in the same fi eld for a wide range of crops and geographies. Examples ABSTRACTNitrogen fi xation by the Haber-Bosch process has more than doubled the amount of fi xed N on Earth, signifi cantly infl uencing the global N cycle. Much of this fi xed N is made into N fertilizer that is used to produce nearly half of the world's food. Too much of the N fertilizer pollutes air and water when it is lost from agroecosystems through volatilization, denitrifi cation, leaching, and runoff . Most of the N fertilizer used in the United States is applied to corn (Zea mays L.), and the profi tability and environmental footprint of corn production is directly tied to N fertilizer applications. Accurately predicting the amount of N needed by corn, however, has proven to be challenging because of the eff ects of rainfall, temperature, and interactions with soil properties on the N cycle. For this reason, improving N recommendations is critical for profi table corn production and for reducing N losses to the environment. Th e objectives of this paper were to review current methods for estimating N needs of corn by: (i) reviewing fundamental background information about how N recommendations are created; (ii) evaluating the performance, strengths, and limitations of systems and tools used for making N fertilizer recommendations; (iii) discussing how adaptive management principles and methods can improve recommendations; and (iv) providing a framework for improving N fertilizer rate recommendations.