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Impact of different cover crops and termination methods on collard yield

A three-year experiment was conducted in Cullman, AL, to determine the impact of iron clay pea, sunn-hemp, soybean, velvet Bean, sorghum Sudan, and pearl millet cover crops terminated with two methods (rolling and flail mowing) on collard (brassica oleracea var. acephala, L.) yield. Overall, each of the three growing seasons (2013, 2014, and 2015) produced significant differences in cover crop biomass production among cover crops. Across three growing seasons sorghum Sudan and Pearl Millet generated the highest biomass (23,752 and 23,333 kg ha -1 respectively). During the same period, sunn hemp produced 10,908 kg/ha -1 and soybean, velvet bean and iron clay pea produced lower biomass (6,754, 6,068, and 4,360 kg ha -1 , respectively). Termination rates of cover crops used in this study were mostly below 90%. Termination rates above 90% have been recommended by agricultural extension services to plant cash crop into cover crop residue. In all three growing seasons volumetric soil moisture content during evaluation have showed that plots with rolled residue consistently held more VMC than the standing cover crops, indicating that rolled cover crop residue better preserved soil moisture content. Collard green yield was significantly different in each growing season for different covers and termination methods. Averaged over three growing seasons, the highest collard yield was observed for iron clay pea (12,623 kg ha -1 ), Velvet bean (11,020 kg ha -1 ) and sunn hemp (10,802 kg ha -1 ). Data suggest that higher collard yield was obtained with legume cover crops with the benefit of released nitrogen into the soil and utilized by collards. In addition, across all years, the average collard green yield was higher for cover crops which were flail mowed (11,875 kg ha -1 ) compared to rolled/crimped cover crops (7,349 kg ha -1 ).

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Zonal yield expectation maps for Precision Agriculture generated using a combined Fuzzy-Expert system

The development of procedures which facilitate the determination of realistic yield expectations for management units within agricultural fields represents a scientific challenge. For this an applicable and scenario-apt Fuzzy-Expert system was developed. The procedure for generation of sites-specific yield expectation maps is divided into three methodical steps – step 1: estimation of yield potential, step 2: influences of pre-crop and crop variety and step 3: influence of site-specific parameters. The regional approach takes into account physical parameters as well as meteorological input data or results of variety testing trials for prediction of regional average yields. This prediction is starting point for the joined site-specific fuzzy model. For yield estimation site-specific heterogeneity spatial information of parameter influencing yield formation are taken into account. Physical soil parameter (plant available water, potential capillary rise, ground water table, landform attributes) are used to generate the site specific yield expectation map. This map is generated using the Spatial Analysis and Modeling Tool (SAMT). A method for training of the fuzzy model is described. The procedure was tested on a 45 ha field cropped with winter wheat in a Chernozem area of Saxony-Anhalt in East-Germany for the years 2000 and 2005.

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