Crop, Forage and Turfgrass Management最新文献

{"title":"Dryland pea seeding rates can be reduced without yield or economic penalty","authors":"Patrick M. Carr,&nbsp;Simon I. Fordyce,&nbsp;Samuel T. Koeshall,&nbsp;Peggy F. Lamb,&nbsp;Perry R. Miller,&nbsp;Jessica A. Torrion,&nbsp;Justin M. Vetch","doi":"10.1002/cft2.70009","DOIUrl":"https://doi.org/10.1002/cft2.70009","url":null,"abstract":"<p>Montana is the leading producer of field peas (<i>Pisum sativum</i> L.) in the United States. A density of 8 to 10 plants ft⁻² is recommended when growing field peas in that state, but this recommendation is based on work done elsewhere. Field experiments were conducted in central Montana from 2021 through 2023 and at three additional locations in the final year to determine the yield and the economically optimum plant population (EOPP) when growing field peas for grain. The semi-leafless, yellow-cotyledon variety Montech 4152 was planted at five rates (5, 7, 9, 11, and 13 pure live seed [PLS] ft⁻²) in all 3 years with two additional rates (3 and 15 PLS ft⁻²) added in the final year. A minimum plant density of 6 to 8 plants ft⁻², or planting field pea at 7 to 9 PLS ft⁻², produced a grain yield comparable to or greater than amounts produced at other seeding rates. The minimum EOPP across the six experiments ranged from 3 (2.8) to 7 (6.4) plants ft⁻², corresponding to a seeding rate of 3 to 7 PLS ft⁻². However, more weeds were observed when field pea was planted at 3 PLS ft⁻² than at higher rates in one of the experiments. A field pea density of 6 to 8 plants ft⁻² is sufficient to optimize grain yield and economic returns in Montana and similar dryland environments.</p>","PeriodicalId":10931,"journal":{"name":"Crop, Forage and Turfgrass Management","volume":"10 2","pages":""},"PeriodicalIF":0.8,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cft2.70009","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142642274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Crop sequence affects horseweed density and productivity in oats","authors":"Marty Schmer,&nbsp;Gary Varvel,&nbsp;Steve Swanson,&nbsp;Ben Fann","doi":"10.1002/cft2.70014","DOIUrl":"https://doi.org/10.1002/cft2.70014","url":null,"abstract":"","PeriodicalId":10931,"journal":{"name":"Crop, Forage and Turfgrass Management","volume":"10 2","pages":""},"PeriodicalIF":0.8,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142641163","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Influence of tillage and rotation sequence on corn response and planting pattern","authors":"M. Scott Tilley,&nbsp;David L. Jordan,&nbsp;Rachel A. Vann,&nbsp;Luke Gatiboni,&nbsp;Ronnie W. Heiniger","doi":"10.1002/cft2.70010","DOIUrl":"https://doi.org/10.1002/cft2.70010","url":null,"abstract":"","PeriodicalId":10931,"journal":{"name":"Crop, Forage and Turfgrass Management","volume":"10 2","pages":""},"PeriodicalIF":0.8,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142641868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating the agronomic and economic benefit of including spinosad with and without pyrethroid insecticides in bermudagrass stem maggot treatments","authors":"Justin C. Burt,&nbsp;Lisa L. Baxter,&nbsp;William F. Anderson,&nbsp;Guy A. Hancock,&nbsp;William G. Secor","doi":"10.1002/cft2.70011","DOIUrl":"https://doi.org/10.1002/cft2.70011","url":null,"abstract":"<p>The bermudagrass stem maggot (BSM; <i>Atherigona reversura</i> Villeneuve) is known to have a detrimental effect on bermudagrass (<i>Cynodon</i> spp.). Currently, two strategically timed pyrethroid applications are recommended for BSM suppression in each harvest cycle. However, producers are interested in applying spinosad because of its residual effects for other insects or reducing the number of pyrethroid applications to cut input costs. Therefore, the objective of this study was to determine the agronomic and economic implications of one or multiple pyrethroid (zeta-cypermethrin) and/or spinosad applications on ‘Alicia’ and ‘Tifton 85’ bermudagrasses. Generally, zeta-cypermethrin treatments resulted in a greater herbage accumulation compared to the untreated control in both cultivars. Regardless of cultivar, spinosad only treatments did not improve upon the herbage accumulation observed in the untreated control. Crude protein and total digestible nutrients were not affected by insecticide treatments in either cultivar. Finally, two zeta-cypermethrin applications resulted in greater net profit compared to other insecticide treatments. These data illustrate that there is not yet an alternative for two pyrethroid applications for BSM suppression. Ongoing research and breeding efforts are focused on BSM tolerance and reduced pyrethroid usage to prevent resistance to the insecticide.</p>","PeriodicalId":10931,"journal":{"name":"Crop, Forage and Turfgrass Management","volume":"10 2","pages":""},"PeriodicalIF":0.8,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cft2.70011","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142641867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Planting time and variety effects on biomass, harvest index, and yield of irrigated soybean in mid-Southern United States","authors":"Brian Pieralisi,&nbsp;Ramandeep Kumar Sharma,&nbsp;Bobby Golden,&nbsp;Jason Bond,&nbsp;Don Cook,&nbsp;Jon Irby,&nbsp;Mike Cox,&nbsp;Jagmandeep Dhillon","doi":"10.1002/cft2.70012","DOIUrl":"https://doi.org/10.1002/cft2.70012","url":null,"abstract":"<p>Soybean [<i>Glycine max</i> (L.) Merr.] biomass and grain yield has increased over the past several decades in the mid-southern United States. This is attributable to technological advances and improved management strategies. However, a better understanding of biomass accumulation and partitioning is needed to improve our knowledge base of varietal growth habits relative to yield, planting date, and harvest index (HI). Field experiments within a split plot arrangement in a randomized complete block design were established in 2017 and 2018 in Stoneville, MS. The study aimed to evaluate the effect of early (late-April or mid-May) and late (late-May) planting on biomass, HI, and yield amongst eight soybean varieties. Soybean total biomass accumulation was collected at multiple development stages, including V4, R2, mid R5, mid R6, and R8, and partitioned into senesced leaves, pods, and seeds. Overall, the planting date had no effect on yield, HI, and biomass accumulation at any of the growth stages. Yet, the interaction between planting date and variety significantly affected biomass accumulation at the mid R5 stage. Contrarily, the variety selection significantly affected yield, HI, and biomass accumulation at all growth stages except mid R6. The total biomass accumulation at R8 was greatest for Asgrow 46X6, Asgrow 4632, Terral 4857X, Terral 48A76, and Credenz 4748, when pooled over planting dates. Averaged across two planting dates, the greatest yield was produced by Terral 48A76, Asgrow 4632, and Asgrow 46X6. Furthermore, averaged across site-years, HI was greatest for Asgrow 4632 and Terral 48A76. Based on the results of this study, evaluating soybean HI rather than overall biomass accumulation may be more beneficial for variety selection decisions.</p>","PeriodicalId":10931,"journal":{"name":"Crop, Forage and Turfgrass Management","volume":"10 2","pages":""},"PeriodicalIF":0.8,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cft2.70012","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142641869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Response of forage sorghum cultivars to different water availability","authors":"Mahmoud Reza Ajoudani,&nbsp;Saeed Sayfzadeh,&nbsp;Seyed Alireza Valadabadi,&nbsp;Nasser Shahsavari,&nbsp;Hamidreza Zakerin","doi":"10.1002/cft2.70008","DOIUrl":"https://doi.org/10.1002/cft2.70008","url":null,"abstract":"<p>To explore the effects of varied irrigation regimes on different sorghum [<i>Sorghum bicolor</i> (L.) Moench] cultivars, a split-plot experiment adhering to a randomized complete block design with three replications was conducted in 2016 across the Khaveh and Varamin regions. The experimental treatments encompassed irrigation levels as the primary factor and four different sorghum cultivars as the secondary factor. Cultivars exhibiting larger leaf areas were associated with higher chlorophyll content, which enhanced biomass production and the quality of sorghum products. Notable variability in leaf area and crude fiber content was observed across irrigation regimes and cultivars, with 2121 cm² to 7153 cm² and 40.4% to 50.7%, respectively. Plant height, total dry weight, and water use efficiency were markedly higher under well-irrigated conditions than those under moderate and severe water deficit conditions. Specifically, the Pegah cultivar displayed the highest leaf area in the Varamin region, measuring 4612 cm² and 5911 cm², whereas the Thin Stem cultivar exhibited the lowest leaf area at both locations. Our findings suggest that the Pegah cultivar maintained a high leaf area without reducing total dry weight, indicating its stability across different environments. Therefore, to produce sorghums in similar climatic conditions, full irrigation is recommended. These results underscore the significance of ongoing research and breeding initiatives to leverage genetic diversity and improve sorghum cultivars.</p>","PeriodicalId":10931,"journal":{"name":"Crop, Forage and Turfgrass Management","volume":"10 2","pages":""},"PeriodicalIF":0.8,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142641221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Growers, consultants, and county agents perceive white-tailed deer to be the most economically impactful pest of Georgia cotton","authors":"Lavesta C. Hand,&nbsp;Phillip M. Roberts,&nbsp;Sally Taylor","doi":"10.1002/cft2.70007","DOIUrl":"https://doi.org/10.1002/cft2.70007","url":null,"abstract":"&lt;p&gt;White-tailed deer (&lt;i&gt;Odocoileus virginianus&lt;/i&gt; Zimmerman) are the predominant big game species pursued by hunters in North America. However, in the early 1900s, white-tailed deer were nearly hunted to extinction. Some of the earliest available data indicate that white-tailed deer populations ranged from 0 to 0.35 mi&lt;sup&gt;−2&lt;/sup&gt; in 1950 in the Southeastern United States (Alabama, Arkansas, Florida, Georgia, Kentucky, Louisiana, Mississippi, North Carolina, South Carolina, Tennessee, and Virginia), where populations had increased to 1.9 to 5.5 white-tailed deer mi&lt;sup&gt;−2&lt;/sup&gt; in 2001 to 2005 in the same area (Hanberry &amp; Hanberry, &lt;span&gt;2020&lt;/span&gt;). A major goal in the wildlife profession has been increasing wildlife populations, which has been achieved (Conover et al., &lt;span&gt;2018&lt;/span&gt;; Hanberry &amp; Hanberry, &lt;span&gt;2020&lt;/span&gt;). However, this can create issues for agricultural producers, with wildlife populations increasing to levels that have resulted in significant damage to crops (Conover et al., &lt;span&gt;2018&lt;/span&gt;).&lt;/p&gt;&lt;p&gt;Upland cotton (&lt;i&gt;Gossypium hirsutum&lt;/i&gt; L.), on average, is planted on 11.7 million acres across the United States (USDA-NASS, &lt;span&gt;2024&lt;/span&gt;). In the same 10-year span, Georgia consistently ranked second in cotton acreage, with approximately 1.2 million planted acres annually, which makes it the most widely planted row crop in Georgia (USDA-NASS, &lt;span&gt;2024&lt;/span&gt;). Growers and extension personnel alike noted that deer damage to cotton was uniquely high in the 2023 growing season, particularly in southeastern states (Bain, &lt;span&gt;2023&lt;/span&gt;; Gratas, &lt;span&gt;2023&lt;/span&gt;). Reports in the literature of perceived impact of white-tailed deer on crop production are limited. Thus, a survey was distributed from September 2023 to March 2024 in Georgia to determine the perceived impact of white-tailed deer on cotton.&lt;/p&gt;&lt;p&gt;This survey was distributed to growers, University of Georgia County Extension Agents, and crop consultants, and they were asked about the following information: i) if deer are an economic problem in cotton; ii) annual cotton acreage (used to calculate acres represented in responses); iii) percent of cotton acres affected by deer; iv) percent yield loss observed on affected acres; v) dollars spent per affected acre on mitigation measures for deer damage on cotton; and vi) mitigation measures utilized (growers only). In total, 525 growers at 47 grower meetings responded representing approximately 449,821 acres (Table 1), 27 consultants responded representing approximately 352,625 acres, and 16 University of Georgia County Agents responded representing approximately 259,000 acres. Where appropriate, responses were compared to determine if perception was similar across groups utilizing two-tailed &lt;i&gt;t&lt;/i&gt;-tests assuming equal variances, graphs were built, and standard errors were calculated using Sigmaplot 15.0 (Systat Software). Proportion data were analyzed using a beta distribution.&lt;/p&gt;&lt;p&gt;With respect","PeriodicalId":10931,"journal":{"name":"Crop, Forage and Turfgrass Management","volume":"10 2","pages":""},"PeriodicalIF":0.8,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cft2.70007","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142439105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving nutritional values and yield in common bean (Phaseolus vulgaris L.) cultivars via foliar application of zinc and iron fertilizers","authors":"Fitsum Merkeb,&nbsp;Tarekegn Yoseph,&nbsp;Berhanu Amsalu","doi":"10.1002/cft2.70004","DOIUrl":"https://doi.org/10.1002/cft2.70004","url":null,"abstract":"<p>Developing countries struggle to achieve food security due to a lack of superior crop cultivars, limited inputs, and environmental degradation. One way to deal with these issues is to biofortify with zinc- (Zn) and iron (Fe)-containing fertilizers to improve nutrient content and productivity. Thus, this study aims to assess the effect of foliar application of Zn and Fe fertilizers on various bean cultivars. Three cultivars (SAB-632, DAB-197, and BZ-2) combined with nine Zn- and Fe-containing fertilizers (T1 = 0, T2 = 0+1.5%, T3 = 0+3%, T4 = 0.5%+0, T5 = 0.5%+1.5%, T6 = 0.5%+3%, T7 = 1%+0, T8 = 1%+1.5%, and T9 = 1%+3%) were used as experimental treatments. The study utilized a split-plot design with a factorial arrangement and three replications, with cultivars on the main plot and fertilizer treatments on the sub-plots. The result revealed that T8 with the cultivar SAB-632 had a significantly higher (17.2%) grain Zn concentration than the control. The cultivar SAB-632 exhibited significantly higher Zn and Fe accumulations. Grain Zn and Fe accumulation were significantly enhanced by the foliar application of treatments, either individually or combined. T6 showed the highest accumulation of Zn and Fe, followed by T9. These values were increased by 33.4% and 29.2%, respectively, due to T6 compared to the control treatment. Additionally, applying these treatments to the leaves improved most agronomic parameters. Therefore, using foliar Zn + Fe fertilizers in bean cultivation can increase essential nutrient contents in grains and improve productivity, ensuring food security and nutrition for small-scale farmers.</p>","PeriodicalId":10931,"journal":{"name":"Crop, Forage and Turfgrass Management","volume":"10 2","pages":""},"PeriodicalIF":0.8,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142429918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Soybean production and net revenue variability in an integrated crop–livestock system","authors":"J. Brett Rushing,&nbsp;Joshua G. Maples,&nbsp;Kelsey M. Harvey,&nbsp;Johnson C. Lyles","doi":"10.1002/cft2.70006","DOIUrl":"https://doi.org/10.1002/cft2.70006","url":null,"abstract":"<p>The integration of grazing cover crops in combination with soybean [<i>Glycine max</i> (L.) Merr.] production has the potential to increase total farm revenue. The objectives of this research were to determine the effect grazing had on subsequent soybean production and the economic implications of this practice. A field trial was conducted at the Coastal Plain Branch Experiment Station (CPBES) in Newton, MS, and the Prairie Research Unit (PRU) in Prairie, MS, from 2021 to 2023 to compare three cropping systems on two distinct soil types. Cropping systems included: conventional soybean (CS); no-till soybean + cereal rye (<i>Secale cereale</i> L.) cover crop (CC); and no-till soybean + grazed cereal rye cover crop (GC). Treatments were applied in a randomized complete block design with three replications at each location. Analysis was separated by location. Cover crop, soybean production, animal performance, and economic analysis were evaluated for each treatment. Soybean grain yield varied by treatment; GC (54.6 bu acre⁻¹) was greater than CS (52.3 bu acre⁻¹) at CPBES. At PRU, CS (68.5 bu acre⁻¹) had greater soybean yield than all other treatments. Cover crop forage mass (FM) was 5077 lb acre⁻¹ at CPBES, compared to 3094 lb acre⁻¹ at PRU, resulting in subsequent cattle revenue of $593.64 and $160.29 acre⁻¹ for CPBES and PRU, respectively. Soybean revenue was greatest for GC at CPBES ($691.78 acre⁻¹) and CS at PRU ($867.89 acre⁻¹). Net returns above production costs were greatest for GC at CPBES ($811.59 acre⁻¹) and CS at PRU ($528.58 acre⁻¹). Findings suggest grazing cereal rye cover crop has the potential to increase net returns in a no-till soybean system on coarse textured soils, but reduces soybean grain yield on heavy, poorly drained sites.</p>","PeriodicalId":10931,"journal":{"name":"Crop, Forage and Turfgrass Management","volume":"10 2","pages":""},"PeriodicalIF":0.8,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142429275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"North Dakota corn efficiency frontier: Stochastic frontier analysis","authors":"Bayarbat Badarch,&nbsp;David C. Roberts,&nbsp;Michael P. Popp","doi":"10.1002/cft2.70005","DOIUrl":"https://doi.org/10.1002/cft2.70005","url":null,"abstract":"<p>According to climate studies in North Dakota, the state's crop-growing season has been extended. In addition, many studies have shown technological advances in crop production. However, the state has not addressed how crop yield has been affected by weather changes. Thus, this paper investigates the state's corn (<i>Zea mays</i>) yield potential and efficiency measures based on agricultural input use and weather variables from 1994 to 2018. We found that the effects of temperature and precipitation on the state's corn yield frontier (potential) were greater than those of changing agricultural input variables. The stochastic frontier model indicates that the proportion of the total variance attributable to inefficiencies or unexpected shifts in the corn yield frontier were primarily (81%) caused by favorable or unfavorable temperature and precipitation variations each year. At least half of the corn-producing districts were technically efficient, reaching at least 85% of yield potential from 1994 to 2018. Thus, better interannual weather forecasting and input use management taking weather risk management into account will bring higher corn yields for North Dakota farmers.</p>","PeriodicalId":10931,"journal":{"name":"Crop, Forage and Turfgrass Management","volume":"10 2","pages":""},"PeriodicalIF":0.8,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cft2.70005","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142429418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}