Joseph G. Lauer

Influence of rotation sequence on the optimum corn and soybean plant population

reductions under no-tillage systems. Soybean yields in no-tillage systems are often lower than yields in convenRotation sequence and plant population are important managetional tillage systems (Philbrook et al., 1991). Reduced ment considerations for maximum yield. Response of corn (Zea mays L.) and soybean [Glycine max L. (Merr.)] to changes in plant populaemergence and final plant stands from comparable seedtion, rotation sequences, and tillage system was evaluated for 3 yr. ing rates may account for part of the yield reductions Corn was planted in 76-cm rows and had a final plant population of (Guy and Oplinger, 1989; Philbrook et al., 1991). 56 300, 65 800, and 75 200 plants ha 1; soybean was planted in 19-cm Information is not available in the literature on the rows with a final plant population of 294 200, 450 400, and 518 500 corn–soybean rotation effect on different plant populaplants ha 1 using conventional tillage and no-tillage systems. Both tions. Numerous papers published on plant populations crops were compared in seven rotation sequences. For corn yield for corn and soybean indicate that year, location, and there were no interactions of plant population with tillage or rotation hybrid/variety influences optimum plant population sequence. Averaged over years, tillage did not affect corn yield. Corn (Nafziger, 1994; Oplinger and Philbrook, 1992; Porter rotated annually with soybean and first-year corn after 5 yr of consecuet al., 1997). Soybean yields often increase, up to a point, tive soybean yielded 12% more than continuous grown corn. Corn yields increased 11% as plant population increased from 56 300 to with increasing plant population (Ablett et al., 1984; 75 200 plants ha 1, regardless of tillage or rotation treatment. AverOplinger and Philbrook, 1992). However, soybean yield aged over years, no interactions of plant population with tillage or responses to plant population are generally small and rotation sequence on soybean yield were found. Soybean yields were often inconsistent (Lehman and Lambert, 1960). In gen8% higher in conventional tillage than in the no-tillage systems. Firsteral, increasing plant populations has increased mature year soybean after 5 yr of consecutive corn yielded 8% more compared plant height and resulted in greater yield losses from with the other six rotation sequences. Plant population within the lodging (Weber and Fehr, 1966). Devlin et al. (1995) studied range did not affect soybean yield. It was concluded that reported that as plant population increased plant morneither corn–soybean cropping history nor tillage system were importality increased, and final plant population compared to tant for determining optimum plant population for corn or soybean. seeding rate decreased. The objective of this experiment was to determine the optimum plant population with continuous corn or R corn and soybean and its beneficial effects soybean compared with various corn–soybean rotations have been recognized and exploited for centuries using different tillage systems. as a management practice to increase crop yields (Bhowmik and Doll, 1982; Peterson and Varvel, 1989). Barber (1972) reported that corn yields declined with increasing MATERIALS AND METHODS frequency of corn in the rotation. However, other results Field research was conducted during 3 yr (1995–1997) on indicate that the type of crop in the rotation may not a Plano silt loam soil (fine-silty, mixed, mesic Typic Argiudolls) be important, as long as corn does not follow itself at the University of Wisconsin Agricultural Research Station, (Peterson and Varvel, 1989). Crookston et al. (1991) located near Arlington, WI. The experiment was a randomized reported a 5% yield advantage for first-year corn after complete block in a split-split plot arrangement with four several years of soybean compared with corn rotated replications. Main plots were no-tillage and conventional tillage systems that were established in 1986. Conventional tillage annually with soybean. Planting soybean in rotation has was accomplished by a chisel plow in the fall and two passes also resulted in consistently higher yields than when of field cultivation in the spring before planting. For no-tillage, grown in monoculture (Dabney et al., 1988; Edwards crops were planted directly into the undisturbed residue of the et al., 1988; Meese et al., 1991). In Wisconsin, soybean previous crop. The subplots consisted of 14 rotation sequences yields in an alternating corn and soybean rotation were involving corn and soybean, which had been initiated in 1983 15 to 20% lower (depending on the tillage system and on land previously planted to corn (Table 1). The sequences cultivar) compared with first-year soybean after several allowed comparisons to be made during 1995, 1996, and 1997 years of corn (Meese et al., 1991). of (i) first-year corn and soybean (after a minimum of 4 consecCorn and soybean yield response to different tillage utive years of the other crop); (ii) corn and soybean alternated systems varies depending on previous crop and soil annually with the other crop; and (iii) 2, 3, 4, and 5 or more drainage characteristics (Dick and van Doren, 1985; years of continuous corn and soybean (13th, 14th, and 15th year in 1995, 1996, and 1997, respectively). The sub-subplots Philbrook et al., 1991). No-tillage corn yields are least were plant populations. Corn was planted in 76-cm rows at likely to equal or exceed those for conventional tillage 62 700, 74 100, and 86 400 plants ha ; soybean was planted with poorly drained soils (Dick and van Doren, 1985), in 19-cm rows at 432 200, 555 600, and 679 000 plants ha . but rotating corn and soybean usually minimizes yield The three seeding rates for both corn and soybean represent a low, medium, and a high seeding rate for the specific planting Dep. of Agronomy, Moore Hall, Univ. of Wisconsin, 1575 Linden date and region. The corn hybrid was Pioneer Brand 3769 Dr., Madison, WI 53706. Received 24 Sept. 2001. *Corresponding and the soybean variety was Northern King Brand S24-92. author (pedersen@wisc.edu). Plot size of the sub-subplot experimental units was 3 by 9 m. Potassium was applied to all plots at a rate of 0–0–270 kg Published in Agron. J. 94:968–974 (2002).

Stage of maturity, processing, and hybrid effects on ruminal in situ disappearance of whole-plant corn silage

Five in situ trials with whole-plant corn silage (WPCS) were conducted in two ruminally-cannulated Holstein cows to determine 24-h ruminal disappearance of dry matter (DM), starch, and neutral detergent fiber (NDF). In Trial 1, the effect of maturity of WPCS on ruminal nutrient disappearance was evaluated. Treatments were early dent (ED), 1/4 milk-line (1/4 ML), 2/3 milk-line (2/3 ML), and black-layer (BL) stage of maturity. Ruminal disappearance of DM was lower (p<0.01) for BL (474 g/kg) than ED (547 g/kg), 1/4 ML (579 g/kg), or 2/3 ML (530 g/kg). Ruminal starch disappearance was lower (p<0.01) for BL (862 g/kg) than ED, 1/4 ML, or 2/3 ML which averaged 950 g/kg. In Trial 2, the effect of mechanical processing of mature and immature WPCS and stover silage at harvest was evaluated. Processing increased (p<0.01) ruminal starch disappearance for both immature (844 vs. 664 g/kg) and mature (790 vs. 525 g/kg) WPCS. In Trial 3, two WPCS hybrids (grain vs. leafy) at two plant populations (low=59,000 or high=79,000 plants/ha) were evaluated. Type of hybrid or plant population did not affect DM or NDF disappearance. However, starch disappearance was higher (p<0.01) for the leafy hybrid (872 vs. 731 g/kg). In Trial 4, brown-midrib (BMR) corn harvested as WPCS was evaluated for ruminal nutrient disappearance versus a conventional grain hybrid. Ruminal DM (602 vs. 561 g/kg) and NDF (326 vs. 220 g/kg) disappearance were higher (p<0.01) for BMR. In Trial 5, ruminal nutrient disappearance of high- and low-NDF corn silage hybrids were compared. Ruminal DM (662 vs. 620 g/kg) and starch (987 vs. 950 g/kg) disappearance were higher, but NDF disappearance was lower (176 vs. 225 g/kg) for the low-NDF hybrid (p<0.001). In summary, delaying silage harvest to BL reduced ruminal nutrient disappearance. Mechanical processing increased ruminal disappearance of WPCS, primarily through greater ruminal starch disappearance. Ruminal starch and NDF disappearance were higher for leafy and BMR hybrids, respectively, relative to a conventional grain hybrid. Ruminal DM disappearance was increased for a low-NDF hybrid, but effects were positive for starch and negative for NDF disappearance.

Commercialized transgenic traits, maize productivity and yield risk

111 1. Zerbino, D.r. et al. Science 336, 179–182 (2012). 2. Tan, T.W. et al. BMC Genomics 10 (suppl 3), S36 (2009). 3. Wollman, r. & Stuurman, N. J. Cell Sci. 120, 3715– 3722 (2007). 4. Joyce, A. & palsson, B. Nat. Rev. Mol. Cell Biol. 7, 198–210 (2006). 5. Arnaout, r. et al. PLoS ONE 6, e22365 (2011). 6. Brown, B., chui, M. & Manyika, J. McKinsey Q. 4, 24–35 (2011). 7. Taylor, c.r. Am. Econ. Rev. 85, 872–890 (1995). 8. Scotchmer, S. Innovation and Incentives (MIT press, cambridge, MA; 2004). 9. Levine, D.K. Science 323, 1296–1297 (2009). 10. Terwiesch, c. & Xu, Y. Manage. Sci. 54, 1529–1543 (2008). 11. Travis, J. Science 319, 1750–1752 (2008). 12. Howe, J. Crowdsourcing (crown Books, New York; 2008). 13. eiben, c.B. et al. Nat. Biotechnol. 30, 190–192 (2012). 14. Khatib, F. et al. Proc. Natl. Acad. Sci. USA 108, 18949–18953 (2011). 15. cooper, S. et al. Nature 466, 756–760 (2010). 16. Khatib, F. et al. Nat. Struct. Mol. Biol. 18, 1175–1177 (2011). 17. Scudellari, M. Nat. Med. 18, 326 (2012). 18. Jeppesen, L. & Lakhani, K.r. Organ. Sci. 21, 1016– 1033 (2010). 19. Boudreau, K.J., Lacetera, N. & Lakhani, K.r. Manage. Sci. 57, 843–863 (2011). 20. Marbach, D. et al. Nat. Methods 9, 796–804 (2012). 21. Boyd, S.D. et al. Sci. Transl. Med. 1, 12ra23 (2009). 22. Weinstein, J.A. et al. Science 324, 807–810 (2009). 23. robins, H.S. et al. Sci. Transl. Med. 2, 47ra64 (2010). 24. Jung, D. et al. Annu. Rev. Immunol. 24, 541–570 (2006). 25. Altschul, S.F. et al. J. Mol. Biol. 215, 403–410 (1990). 26. Brochet, X. et al. Nucleic Acids Res. 36, W503–W508 (2008). 27. Hong, L. & page, S. Proc. Natl. Acad. Sci. USA 101, 16385–16389 (2004). and collected data. R.A.A. identified and codeveloped the immunogenomics problem, tested the submissions and helped write the manuscript. M.L. and L.B. codeveloped the problem statement and test data. P.-R.L. analyzed and categorized all submission data and helped write the manuscript.

Estimating silage energy value and milk yield to rank corn hybrids

This paper provides a revised summative energy equation and applies it to estimate the energy value of corn (Zea mays) silage. Estimating the energy value of corn silage is important, because energy is the primary nutrient contributed by corn silage to dairy cattle rations. Estimated energy intake from corn silage was used to estimate milk yield from corn silage by dairy cows. The milk yield estimate was used to rank corn hybrids in silage evaluation and breeding programs. The revised (MILK2000) forage quality (milk Mg −1 ) and yield (milk ha −1 ) indices were evaluated relative to MILK1995 indices in corn silage hybrid performance trials. A previously published summative energy equation (Weiss, 1996), with crude protein, fat, non-fiber carbohydrate (NFC), and neutral detergent fiber (NDF) fractions and corresponding digestibility coefficients, was adapted for corn silage as follows: the crude protein and fat fractions were not altered, the NFC fraction with constant digestibility was replaced with starch and non-starch NFC fractions, the starch digestibility coefficient was varied in relationship to whole-plant dry matter (DM) concentration and kernel processing, and the NDF digestibility coefficient based on lignin concentration was replaced by a 48 h or maintenance intake in vitro measurement of NDF digestibility (NDFD). Our summative approach integrates known differences in starch digestibility, as affected by whole-plant DM concentration and kernel processing, and NDFD into estimates of the energy value of corn silage. It also provides a framework for the future incorporation of laboratory measures of starch digestibility into estimates of the energy value of corn silage. For the MILK2000 model, we used our net energy for lactation estimates along with DM intake estimated from NDF concentration and NDFD to Abbreviations:ADF, acid detergent fiber; BW, body weight; CP, crude protein; DM, dry matter; DMI, dry matter intake; FA, fatty acids; IVTD, in vitro true digestibility; MILK2000, revised milk Mg −1 and milk ha −1 indices; MILK1995, original milk Mg −1 and milk ha −1 indices; N, nitrogen; NDF, neutral detergent fiber; NDFD, in vitro NDF digestibility; NEL, net energy of lactation; NFC, non-fiber carbohydrate; NIRS, near infra-red reflectance spectroscopy ∗

Planting Date and Hybrid Influence on Corn Forage Yield and Quality

April resulted in grain yield decline, but because the maximum dry matter yield of corn stover was obtained Producers believe that corn (Zea mays L.) forage can be planted from a mid-May planting date, later planting of forage at later dates than corn grain because forage harvest does not have to wait until the grain matures fully. The objectives of this study were corn was recommended (Bunting, 1978). In Canada, to determine relationships between planting date and corn forage White (1977) and Fairey (1983) documented maturity yield and quality and to determine optimum planting dates of corn and yield advantages for corn planted in mid-May folforage for the state of Wisconsin. Fulland shorter-season hybrids lowed by a significant decline in dry matter content of were planted on six dates at six locations in Wisconsin during 1998 corn forage if planting was delayed past early June. and 1999. Few significant hybrid planting date interactions or hybrid Fairey (1983) reported a 1% reduction in dry matter differences were observed. The optimum planting dates for dry matter digestibility for every day planting was delayed beyond yield and quality for southern, central, and northern Wisconsin were mid-May. Graybill et al. (1991) reported differences in 10 May, 27 April, and 8 May, respectively. Corn forage yields remained fiber content between corn planted at varying dates and at 95% of maximum yields when corn was planted in late May for suggested that corn forage be planted between late April all zones. In all zones, early June plantings exhibited an accelerated rate of yield decline of 0.2 Mg ha 1 d 1 delay in planting. Corn forage and early May in New York. quality decreased progressively as planting dates progressed into June. Corn hybrids respond differently to planting dates The optimum planting date for milk yield ha 1 was 2 May in southern (Lauer et al., 1999; Graybill et al., 1991; Fairey, 1980). and central zones and late April in the northern zone. As planting Hicks et al. (1970) reported an interaction between a was delayed past mid-May, rates of quality decline were more severe hybrid’s growing season length and optimum planting in central and northern zones compared with the southern zone. date, with a full-season hybrid benefiting most from an Therefore, planting of corn forage should occur between late April early planting date and also suffering the most from a and mid-May for all production zones in Wisconsin, but planting could delayed planting date. Bunting (1978) reported no plantoccur into late May in the southern production zone because milk ing date hybrid interactions, and Nafziger (1994) reyield ha 1 declined by only 8%. ported varying results dependent on the particular year. Few recent studies have been conducted to evaluate effects of planting date and hybrid on forage corn yield M practices used to produce corn forage and quality. Optimum planting dates for forage corn are the same as those used for grain production will be affected by both yield and quality. The objectives in most areas. It has not been well established that the of this study were to (i) describe relationships between same management practices used for corn grain will planting date and hybrid on corn forage yield and quality produce optimum corn forage. Few management studies and (ii) determine optimum planting dates for forage have been conducted on planting dates for corn forage. corn in Wisconsin. Several studies have reported the influence of planting date and hybrid on corn grain yield. A recent WisMATERIALS AND METHODS consin study observed optimum planting dates between 1 to 7 May in southern locations and 8 to 14 May in Experiments were conducted during 1998 and 1999 at the University of Wisconsin Research Stations located at Arlingnorthern locations (Lauer et al., 1999). A summary of ton and Lancaster (southern zone), Marshfield and Hancock planting date recommendations compiled by Benson (central zone), and Spooner and Ashland (northern zone). (1990) reported optimum planting dates for the Corn The experimental design at all locations was a randomized Belt to be between 20 April and 10 May. Along with complete block in a split plot arrangement with four replicarecommended optimums, several researchers have detions. Main plots were six planting dates spaced at about 14-d scribed a quadratic corn yield response to planting date intervals from 20 April to 26 June. Split plots were two hybrids (Lauer et al., 1999; Nafziger, 1994; Johnson and Mulvawith similar quality traits that ranged from full-season to ney, 1980). shorter-season maturity and were adapted to each production The relationship between corn forage yield and plantzone. ing date has not been established. It has been hypotheOther than planting date treatments, all plots were managed by practices similar to those used by producers in the sursized that planting corn for forage could theoretically rounding area of that location (Table 1). Plot size was 3.1 by be later than corn for grain because forage does not 7.6 m with four rows per plots. Plots were seeded at a rate of have to be harvested at maturity (Allen et al., 1995). In 83 500 kernels ha 1 and then hand-thinned to 78 600 plants England, corn planted earlier or later than the end of ha 1 at the stage when five leaf collars were visible (V5) (Ritchie et al., 1996) to achieve as near a uniform stand as H.M. Darby, Dep. of Hortic., Oregon State Univ., 4017 ALS, Corvallis, possible. OR 97331; and J.G. Lauer, Dep. of Agron., Univ. of Wisconsin, 1575 The kernel milkline was used as a visible indicator of when Linden Drive, Moore Hall, Madison, WI 53706. Contribution of the University of Wisconsin Experiment Station and supported by Hatch. Abbreviations: ADF, acid detergent fiber; CP crude protein; IVTD, Received 6 Mar. 2001. *Corresponding author (darbyh@bcc.orst.edu). in vitro true digestibility; NDF, neutral detergent fiber; NIRS, nearinfrared reflectance spectroscopy. Published in Agron. J. 94:281–289 (2002).

What does it take to detect a change in soil carbon stock? A regional comparison of minimum detectable difference and experiment duration in the north central United States

Variability in soil organic carbon (SOC) results from natural and human processes interacting across time and space, and leads to large variation in the minimum difference in SOC that can be detected with a particular experimental design. Here we report a unique comparison of minimum detectable differences (MDDs) in SOC, and the estimated times required to observe those MDDs across the north central United States, calculated for the two most common SOC experiments: (1) a comparison between two treatments, e.g., moldboard plow (MP) and no-tillage (NT), using a randomized complete block design experiment; and (2) a comparison of changes in SOC over time for a particular treatment, e.g., NT, using a randomized complete block design experiment with time as an additional factor. We estimated the duration of the two experiment types required to achieve MDD through simulation of SOC dynamics. Data for the study came from 13 experimental sites located in Iowa, Illinois, Ohio, Michigan, Wisconsin, Missouri, and Minnesota. Soil organic carbon, bulk density, and texture were measured at four soil depths. Minimum detectable differences were calculated with probability of Type I error of 0.05 and probability of Type II error of 0.15. The MDDs in SOC were highly variable across the region and increased with soil depth. At 0 to 10 cm (0 to 3.9 in) soil depth, MDDs with five replications ranged from 1.04 g C kg−1 (0.017 oz C lb−1; 6%) to 7.15 g C kg−1 (0.114 oz C lb−1; 31%) for comparison of two treatments; and from 0.46 g C kg−1 (0.007 oz C lb−1; 3%) to 3.12 g C kg−1 (0.050 oz C lb−1; 13%) for SOC change over time. Large differences were also predicted in the experiment duration required to detect a difference in SOC between MP and NT (from 8 to >100 years with five replications), or a change in SOC over time under NT management (from 11 to 71 years with five replications). At most locations, the time required to detect a change in SOC under NT was shorter than the time required to detect a difference between MP and NT. Minimum detectable difference and experiment duration decreased with the number of replications and were correlated with SOC variability and soil texture of the experimental sites, i.e., they tended to be lower in fine textured soils. Experiment duration was also reduced by increased crop productivity and the amount of residue left on the soil. The relationships and methods described here enable the design of experiments with high power of detecting differences and changes in SOC and enhance our understanding of how management practices influence SOC storage.

Standardized research protocols enable transdisciplinary research of climate variation impacts in corn production systems

The important questions about agriculture, climate, and sustainability have become increasingly complex and require a coordinated, multifaceted approach for developing new knowledge and understanding. A multistate, transdisciplinary project was begun in 2011 to study the potential for both mitigation and adaptation of corn-based cropping systems to climate variations. The team is measuring the baseline as well as change of the systems carbon (C), nitrogen (N), and water footprints, crop productivity, and pest pressure in response to existing and novel production practices. Nine states and 11 institutions are participating in the project, necessitating a well thought out approach to coordinating field data collection procedures at 35 research sites. In addition, the collected data must be brought together in a way that can be stored and used by persons not originally involved in the data collection, necessitating robust procedures for linking metadata with the data and clearly delineated rules for use and publication of data from the overall project. In order to improve the ability to compare data across sites and begin to make inferences about soil and cropping system responses to climate across the region, detailed research protocols were developed to standardize the types of measurements taken and the specific details such as depth, time, method, numbers of samples, and minimum data set required from each site. This process required significant time, debate, and commitment of all the investigators involved with field data collection and was also informed by the data needed to run the simulation models and life cycle analyses. Although individual research teams are collecting additional measurements beyond those stated in the standardized protocols, the written protocols are used by the team for the base measurements to be compared across the region. A centralized database was constructed to meet the needs of current researchers on this project as well as for future use for data synthesis and modeling for agricultural, ecosystem, and climate sciences.

An Analysis of Selectivity in the Productivity Evaluation of Biotechnology: An Application to Corn

We investigate selectivity bias in the evaluation of biotech hybrid productivity. The analysis is applied to experimental data on Wisconsin corn yields from 1990 to 2010. Relying on a Heckman-like factor that accounts for selectivity, we find evidence of selection bias, indicating that some of the observed yield advantage associated with GM hybrids can be attributed to their conventional genes. We document how the rising market concentration of biotech firms has contributed to increasing selectivity bias in corn yield. The impact, however, is offset by the negative effect of the rising adoption rate of GM corn on selectivity bias. Copyright 2013, Oxford University Press.

Late-Season Weed Escape Survey Reveals Discontinued Atrazine Use Associated with Greater Abundance of Broadleaf Weeds

Abstract Atrazine has been used for control of many weeds, primarily broadleaf weeds, in U.S. corn fields since 1957. Recently, the adoption of glyphosate-resistant corn hybrids have led to glyphosate eclipsing atrazine as the most commonly used herbicide in corn production. However, the evolution and spread of glyphosate-resistant weeds is a major concern. Atrazine use in Wisconsin is prohibited in 102 areas encompassing 0.49 million ha where total chlorinated residues were found in drinking water wells at concentrations > 3 μg L−1. Atrazine has been prohibited in many of those areas for > 10 yr, providing an opportunity to evaluate weed community composition differences due to herbicide regulation. In question, has the abundance of broadleaf weeds increased, coupled with an increased reliance on glyphosate, where atrazine use has been discontinued? To answer this, an online questionnaire was distributed to Wisconsin growers in June and then weeds present in 343 fields in late July through mid-September in 2012 and 2013 were counted. Data were summarized for frequency, uniformity, density, and relative abundance to compare weed community composition in fields with discontinued vs. recent atrazine use. Growers used glyphosate in 70 vs. 54% of fields with discontinued vs. recent atrazine use, respectively (P = 0.021). Moreover, broadleaf weeds were found more frequently, (73 vs. 61%; P = 0.03), they had 50% greater in-field uniformity (P = 0.002), and density was 0.4 vs. 0.19 plants m−2 (i.e., twofold greater; P < 0.0001) in discontinued vs. recent atrazine-use fields. Changes were most evident with troublesome glyphosate-resistant broadleaf weeds such as Amaranthus species and giant ragweed. In conclusion, weed community composition consisted of more broadleaf weeds in fields where atrazine has not been used in the recent decade coupled with greater glyphosate use. These results provide evidence of negative long-term implications for glyphosate resistance where growers increased reliance on glyphosate in place of atrazine. Nomenclature: Atrazine; glyphosate; giant ragweed, Ambrosia trifida L. AMBTR; corn, Zea mays L. Resumen Atrazine ha sido usado para el control de muchas malezas, principalmente malezas de hoja ancha, en campos de maíz en los Estados Unidos desde 1957. Recientemente, la adopción de híbridos de maíz resistentes a glyphosate ha hecho que glyphosate eclipse el uso de atrazine como el herbicida más usado en la producción de maíz. Sin embargo, la evolución y diseminación de malezas resistentes a glyphosate causa gran preocupación. El uso de atrazine en Wisconsin está prohibido en 102 áreas cubriendo 0.49 millones de hectáreas, donde residuos clorinados totales fueron encontrados en pozos de agua potable a concentraciones > 3 μ L−1. Atrazine ha estado prohibido en muchas de esas áreas por > 10 años, lo que brinda una oportunidad para evaluar las diferencias en la composición de la comunidad de malezas debido a la regulación del uso de herbicidas. ¿Ha incrementado la abundancia de malezas de hoja ancha en combinación con la mayor dependencia en glyphosate, cuando se descontinuó el uso de atrazine? Para responder esta pregunta se distribuyó un cuestionario en línea a productores de Wisconsin en Junio y después se contaron las malezas presentes en 343 campos desde el final de Julio hasta la mitad de Septiembre en 2012 y 2013. Los datos fueron resumidos en frecuencia, uniformidad, densidad, y abundancia relativa para comparar la composición de la comunidad de malezas en campos con uso de atrazine descontinuado vs. reciente. Los productores usaron glyphosate en 70 vs. 54% de los campos con uso de atrazine descontinuado vs. reciente, respectivamente (P = 0.021). Además, las malezas de hoja ancha fueron encontradas más frecuentemente (73 vs. 61%; P = 0.03), tuvieron 50% mayor uniformidad dentro de los campos (P = 0.002), y la densidad fue 0.4 vs. 0.19 plantas m−2 (i.e., más del doble; P < 0.0001) en campos con uso de atrazine discontinuado vs. reciente. Los cambios fueron más evidentes con malezas de hoja ancha resistentes a glyphosate problemáticas, tales como especies de Amaranthus y Ambrosia trifida. En conclusión, la composición de las comunidades de malezas consistió de más malezas de hoja ancha en campos donde atrazine no ha sido usado durante la pasada década y el uso de glyphosate es mayor. Estos resultados proveen evidencia de las implicaciones negativas con relación a la resistencia a glyphosate en el largo plazo donde se ha incrementado la dependencia al glyphosate en lugar de atrazine.

Evaluation of a Microwave Resonator for Predicting Grain Moisture Independent of Bulk Density

This work evaluated the utility of a planar resonator to predict moisture considering moisture and densities expected in an on-harvester application. A calibration model was developed to accurately predict moisture over the moisture, density, and temperature ranges evaluated. This model, comprised of bandwidth and center frequency of a resonance peak at 2.38 GHz, predicted moisture content compared to oven moisture reference data with an r2 of 0.996 and a root mean square error (RMSE) of 1.32. When bulk density was added to the moisture prediction model, no statistically significant improvement was obtained.