Crop, Forage and Turfgrass Management最新文献

{"title":"Effect of biochar application on corn and soybean yield in Michigan and Ohio","authors":"Gabriela Silva-Pumarada, Raj K. Shrestha, Marília Chiavegato, Kristin Mercer, Benjamin K. Agyei, Maninder P. Singh, Laura E. Lindsey","doi":"10.1002/cft2.20245","DOIUrl":"https://doi.org/10.1002/cft2.20245","url":null,"abstract":"<p>Biochar soil amendment, a product of anoxic thermochemical conversion of biomass through a pyrolysis process, may help mitigate greenhouse gas (GHG) emissions from agricultural soils (Huang et al., <span>2023</span>; Verheijen et al., <span>2010</span>). Biochar application to field soils include improvements in pH of acidic soils, cation exchange capacity, and water holding capacity (Agegnehu et al., <span>2017</span>; Alkharabsheh et al., <span>2021</span>; Tokas et al., <span>2021</span>; Ye et al., <span>2020</span>).</p><p>Crop yield response to biochar application is variable but has been generally found as neutral or positive, with largest yield responses in acidic soils likely due to a liming effect of the biochar (Huang et al., <span>2023</span>). Although crop yield response to biochar application has been globally studied, there have been limited field studies conducted</p><p>under field conditions in the Midwestern United States. In growing environments similar to Ohio and Michigan, a meta-analysis and modeling approaches found crop yield response to biochar to be small (< 10% across crops and −2.6 to 0.6% for corn (<i>Zea mays</i> L.) (Aller et al., <span>2018</span>; Huang et al., <span>2023</span>).</p><p>Although there have been previous studies on biochar's effect on corn and soybean [<i>Glycine max</i> (L.) Merr.] yield, farmers in Ohio and Michigan need to understand the potential yield outcomes of biochar application using production practices and crop rotations representative of the region. The objective of this research was to evaluate biochar application on corn and soybean yield.</p><p>A field experiment was established at three locations in Fall 2020 with biochar application and continued in 2021 with corn planting and 2022 with soybean planting. Locations included The Ohio State University (OSU) Western Agricultural Research Station (WARS) near South Charleston, OH (39°51′41.40″ N, 83°40′30.36″ W), OSU Northwest Agricultural Research Station (NWARS) near Custar, OH (41°13′6.6″ N, 83°45′48.24″ W), and Michigan State University (MSU) Agronomy Farm in East Lansing, MI (42°42′52.41″ N, 84°27′42.40″ W). The soil series are Kokomo (fine, mixed, superactive, mesic Typic Argiaquolls), Hoytville (fine, illitic, mesic Mollic Epiaqualfs), and Riddles (fine-loamy, mixed, active, mesic Typic Hapludalfs)–Hillsdale (coarse-loamy, mixed, active, mesic Typic Hapludalfs) complex at WARS, NWARS, and MSU, respectively. Prior to experiment initiation, 20 soil samples were collected from the entire field area, homogenized, and tested for soil properties (Table 1). Based on state guidelines, P, K, Ca, and Mg levels were sufficient (Culman et al., <span>2020</span>).</p><p>The experiment was a randomized complete block design with two treatments (biochar and non-treated control) and four replications. At MSU, plots were 40 ft long by 20 ft wide, and the field was fallow in 2020 due to COVID-19 restrictions. At NWARS and WARS, each plot wa","PeriodicalId":10931,"journal":{"name":"Crop, Forage and Turfgrass Management","volume":"9 2","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cft2.20245","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50117097","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":"Conventional corn tolerance to drift-simulating rates of glyphosate at two growth stages","authors":"Amar S. Godar, Jason K. Norsworthy, L. Tom Barber","doi":"10.1002/cft2.20244","DOIUrl":"https://doi.org/10.1002/cft2.20244","url":null,"abstract":"","PeriodicalId":10931,"journal":{"name":"Crop, Forage and Turfgrass Management","volume":"9 2","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50138945","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 nitrogen rate on yield and profitability of rye grain production","authors":"Elżbieta Szuleta,&nbsp;Jordan M. Shockley,&nbsp;Carrie Knott,&nbsp;Timothy Phillips,&nbsp;David A. Van Sanford","doi":"10.1002/cft2.20243","DOIUrl":"https://doi.org/10.1002/cft2.20243","url":null,"abstract":"<p>Rye (<i>Secale cereale</i> L.) grain production in Kentucky is insufficient to meet the needs of distillers and bakers, in part because there is a knowledge gap about rye management that discourages farmers from choosing this crop. We conducted an economic study to develop recommendations for profitable rye grain production. The aim of this study was to determine the influence of two different nitrogen (N) rates (35 lb N acre⁻¹ and 70 lb N acre⁻¹) on yield and profitability of winter rye grain production. Experiments were conducted in 2020–2021 season at three Kentucky locations: Lexington, Princeton, and Adairville. Twenty-four rye entries were planted in a split plot design experiment and the two N rates (35 lb N acre⁻¹ and 70 lb N acre⁻¹) were assigned to main plots. There was no significant difference in mean yield between 35 and 70 lb N acre⁻¹. This indicates that less investment in N fertilizer will not adversely affect grain yield level, will enhance profitability of production, and will benefit distillers due to the higher alcohol yield associated with higher starch and lower protein levels.</p>","PeriodicalId":10931,"journal":{"name":"Crop, Forage and Turfgrass Management","volume":"9 2","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50152067","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":"Corn and soybean planting order decisions impact farm gross revenue","authors":"Spyridon Mourtzinis,&nbsp;Shawn P. Conley","doi":"10.1002/cft2.20242","DOIUrl":"https://doi.org/10.1002/cft2.20242","url":null,"abstract":"<p>The inter-annual corn (<i>Zea mays</i> L.)–soybean [<i>Glycine max</i> (L.) Merr.] rotation field is a well-known management practice that increases the yield of both crops across the midwestern United States. Each spring, farmers must decide which crop will be planted first. Prioritizing the planting of one crop can delay planting of the other, which can result in substantial yield loss and reduced associated revenue. The objective of this work was to assess how gross farm revenue (corn + soybean acres) can be affected by crop planting order (corn first, soybean second, and vice versa). The impact of variable planting dates on the yield of each crop was simulated for 310 fields across the United States. Gross farm revenue was estimated as a function of crop planting date, order, input costs and crop prices. In a randomly chosen field in south central Wisconsin, 1 out of the 310, delaying planting after May 1 reduced yield of each crop and subsequently suppressed gross farm revenue. Crop planting order determined farm revenue due to a variable loss in per day yield rate within the nominal planting timeframe associated with the two crops. In addition, the degree to which management intensified for each crop relative to crop yield potential accruing with earlier planting varied by state and further impacted farm revenue. Overall results suggest that to determine planting order, US farmers need to be aware of the comparative yield trends associated with delayed planting of corn vs. soybean for their specific farms and cropping systems and should also account for projected crop selling prices.</p>","PeriodicalId":10931,"journal":{"name":"Crop, Forage and Turfgrass Management","volume":"9 2","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cft2.20242","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50132668","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":"Quantification of root lodging damage in corn using uncrewed aerial vehicle imagery","authors":"A. J. Lindsey,&nbsp;B. Allred,&nbsp;L. R. Martinez,&nbsp;Greg Rouse,&nbsp;P. R. Thomison","doi":"10.1002/cft2.20241","DOIUrl":"https://doi.org/10.1002/cft2.20241","url":null,"abstract":"<p>Accurate quantification of damage associated with root lodging events can help producers assess damage, predict potential yield losses, and help understand potential issues with grain quality that may arise post-harvest (i.e., kernel weight reductions, premature germination on the ear, or vivipary). The objective of this research was to utilize imagery from an uncrewed aerial vehicle (UAV) to accurately quantify crop canopy height, grain yield, and identify trends in imagery data associated with grain quality after root lodging was imposed at multiple growth stages. Simulated corn (<i>Zea mays</i> L.) root lodging experiments were conducted in 2018 and 2019 with lodging treatments applied at two vegetative or two reproductive growth stages (V10, V14, VT/R1, and R3). At dough stage (R4), visible-color and multispectral images were collected from each trial. Bare fields were also flown in February to obtain baseline elevation data. Imagery data were used to develop digital surface model (DSM) images and used to calculate indices of normalized difference red edge (NDRE) and normalized difference vegetation index (NDVI). Individual datapoints within each experimental plot were extracted from the imagery files and were compared to ground-truth measurements. The DSM height values were similar to actual measured heights for most lodging treatments (Adj. <i>R</i>² = .957). Both NDRE and NDVI exhibited linear trends with height and quality parameters (Adj. <i>R</i>² = .25–.54), though yield patterns were best described using a quadratic model (Adj. <i>R</i>² = .42–.60). These procedures hold utility in accurately quantifying canopy height following a root lodging event and hold promise in helping consultants identify yield and grain quality reductions associated with root lodging.</p>","PeriodicalId":10931,"journal":{"name":"Crop, Forage and Turfgrass Management","volume":"9 2","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cft2.20241","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50121354","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":"Maximizing winter wheat yield through planting date and seeding rate management","authors":"J. Patrick Copeland,&nbsp;Dennis Pennington,&nbsp;Maninder P. Singh","doi":"10.1002/cft2.20240","DOIUrl":"https://doi.org/10.1002/cft2.20240","url":null,"abstract":"<p>Planting date and seeding rate are two of the most basic and important factors in determining yield potential in winter wheat (<i>Triticum aestivum</i> L.) due to their impact on stand establishment. Timely planting of winter wheat (within a few days after the Hessian fly free date) ensures sufficient time for fall growth and tillering, which are critical for maximizing yield, while adequate seeding rate is necessary to optimize the number of heads per unit area. Field experiments were conducted in Mason, MI during three growing seasons (2020–2022) utilizing five planting dates, ranging from mid-September to mid-November, and five seeding rates ranging from 0.8 to 2.4 million seeds acre⁻¹. There was no interaction between planting date and seeding rate in determining yield. Yields declined by 22–48% from the earliest to the latest planting dates in response to a 33–47% reduction in the number of heads acre⁻¹. Seeding rate did not significantly impact yield except at low seeding rates under delayed planting. Maximum yield was achieved with a seeding rate of 0.93, 1.37, 1.47, 1.54, and 1.85 million seeds acre⁻¹ during the mid-September, late September, mid-October, late October, and mid-November plantings, respectively. Overall, results demonstrated that timely planting of wheat is critical for maximizing yield, with significant yield reductions occurring when planting is delayed, regardless of the seeding rate used. Furthermore, while low seeding rates may be used within the optimal planting window without yield penalty, seeding rates should be progressively increased as planting is delayed to diminish yield loss.</p>","PeriodicalId":10931,"journal":{"name":"Crop, Forage and Turfgrass Management","volume":"9 2","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cft2.20240","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50146726","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":"Evaluation of a handheld NIRS instrument for determining haylage dry matter","authors":"J. H. Cherney,&nbsp;D. J. R. Cherney,&nbsp;M. F. Digman","doi":"10.1002/cft2.20239","DOIUrl":"https://doi.org/10.1002/cft2.20239","url":null,"abstract":"<p>Accurate forage dry matter (DM) concentration estimation is essential for maximizing animal performance and minimizing feed costs. One possible method of estimating DM for rebalancing rations daily involves the use of hand-held near infrared reflectance spectrometer instruments. The SCiO Cup is one of the hand-held instruments that could be used to estimate forage DM, but a thorough evaluation of its effectiveness has not been conducted. Haylage samples (<i>n</i> = 600) from 143 bunker silos were collected across New York State over three years, and vacuum packed for eventual analysis using a SCiO Cup. Samples ranged from pure alfalfa (<i>Medicago</i> L.) to pure grass but were mostly from mixed species. All but one sample received a DM value estimated from several available calibrations pre-loaded in the device. Sixty samples (representing 10% of the sample population) were too wet or dry to generate a result using the mixed silage calibration. For the remaining 90% of samples, SCiO Cup DM estimates were within 3.22%units of oven DM 80% of the time. Precision of the instrument evaluated with multiple scanning of samples using the mixed silage calibration was very good, with the average standard deviation of three values of 0.40 (<i>n</i> = 200). The mixed silage calibration was more effective for predicting DM of this set of haylages than either legume or grass silage calibrations.</p>","PeriodicalId":10931,"journal":{"name":"Crop, Forage and Turfgrass Management","volume":"9 2","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cft2.20239","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50141108","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":"Tolerance of little bluestem to ACCase-inhibiting herbicides in Pennsylvania","authors":"Peter Landschoot","doi":"10.1002/cft2.20236","DOIUrl":"https://doi.org/10.1002/cft2.20236","url":null,"abstract":"&lt;p&gt;Little bluestem [&lt;i&gt;Schizachyrium scoparium&lt;/i&gt; (Michx.) Nash.] is a warm-season perennial grass that is sometimes planted with fine fescues (&lt;i&gt;Festuca&lt;/i&gt; spp.) in infrequently mowed rough areas on golf courses, commonly referred to as naturalized or native grass areas and minimal-mow rough. This native species is often used for its aesthetically pleasing reddish-gold culms and inflorescences during late summer and fall.&lt;/p&gt;&lt;p&gt;In Pennsylvania, perennial and annual grass weeds invade fine fescue/little bluestem rough, and golf course managers occasionally use postemergence herbicides as control options (Landschoot, &lt;span&gt;2018&lt;/span&gt;). ACCase-inhibiting herbicides control a variety of grass weeds, but relatively few studies have examined the effects of these herbicides on little bluestem (Patton et al., &lt;span&gt;2021&lt;/span&gt;).&lt;/p&gt;&lt;p&gt;The objective of this study was to evaluate the tolerance of little bluestem to four ACCase-inhibiting herbicides: fenoxaprop, fluazifop, quizalofop, and sethoxydim. Experiments were conducted in 2021 and 2022 in adjacent areas at the Landscape Management Research Center in University Park, PA. Both experiments were performed in an eight-year-old non-irrigated and non-fertilized stand of strong creeping red fescue (&lt;i&gt;Festuca rubra&lt;/i&gt; ssp. &lt;i&gt;rubra&lt;/i&gt; Gaudin) ‘Garnet’ and little bluestem ‘Ft. Indiantown Gap-PA Ecotype’ (Ernst Conservation Seed). Little bluestem visual cover in the experiment areas at the time of treatment applications was approximately 50-60%. The stand was mowed once per year in October at 5 inches. Soil at the experiment site is a Hagerstown silt loam (fine, mixed, mesic, Typic Hapludalf), with a pH of 6.4, 38 mg/kg Mehlich-3 P, and 186 mg/kg Mehlich-3 K.&lt;/p&gt;&lt;p&gt;Herbicide treatments included fenoxaprop (Acclaim Extra, 0.57 lb fenoxaprop/gal; Bayer Environmental Science) at 28 fl oz product/acre with 0.25% v/v non-ionic surfactant (Lesco 90/10 Nonionic Surfactant; Lesco Inc.); sethoxydim (Segment II, 1.5 lb sethoxydim/gal; BASF) at 16 fl oz product/acre with methylated seed oil at 1.5 pints/acre (Lesco Methylated Seed Oil; Lesco Inc.); fluazifop (Fusilade II T/O, 2 lb fluazifop/gal; Syngenta Crop Protection LLC) at 16 fl oz product/acre with 0.25% v/v non-ionic surfactant; and quizalofop (Assure II, 0.88 lb quizalofop/gal; Amvac Chemical Corp.) at 12 fl oz product/acre with 0.25% v/v non-ionic surfactant. A non-treated control was included in each experiment. Herbicide treatment rates were based on maximum product label rates for control of grass weeds in fine fescue. All treatments were applied once on June 17, 2021, and June 8, 2022. Application dates coincide with preferred timing for control of grass weeds in central Pennsylvania. Total precipitation during the 2021 and 2022 evaluation periods was 19.7 and 9.7 inches, respectively.&lt;/p&gt;&lt;p&gt;All herbicide treatments were applied using a backpack sprayer equipped with a boom fitted with a 9504E flat fan nozzle (TeeJet Technologies) at 40 psi with a wa","PeriodicalId":10931,"journal":{"name":"Crop, Forage and Turfgrass Management","volume":"9 2","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cft2.20236","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50119643","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":"Ancient spring wheat production in Wyoming","authors":"Raksha K. Thapa,&nbsp;Carrie Eberle,&nbsp;Caitlin Youngquist","doi":"10.1002/cft2.20237","DOIUrl":"https://doi.org/10.1002/cft2.20237","url":null,"abstract":"<p>The ancient wheats einkorn (<i>Triticum monococcum</i> L.), emmer (<i>Triticum turgidum</i> L.), and spelt (<i>Triticum spelta</i> L.) are currently attracting renewed consumer interest due to their unique flavor profiles and high nutritional quality compared with modern bread (<i>Triticum aestivum</i> L.) and durum (<i>Triticum durum</i> L.) wheat. Ancient wheats are well suited for production in marginal lands and may be well adapted to Wyoming growing conditions. A 2-year study was conducted in three locations in Wyoming (Powell, Sheridan, and Lingle, WY) under irrigated and rainfed conditions to identify the agronomic potential of spring planted spelt, emmer, and einkorn in Wyoming. Across locations, grain yields averaged 832 lbs acre⁻¹ for einkorn, 1,492 lbs acre⁻¹ for emmer, and 1064 lbs acre⁻¹ for spelt with 14.7–15.9% protein. In 2017, irrigated spring wheat yield in Wyoming averaged 3642 lbs acre⁻¹ and dryland yield averaged 1020 lbs acre⁻¹. The Powell irrigated location was the highest yielding and perhaps the best suited for ancient wheat production. Continued research on variety selection and management is needed to further improve the yield and profitability of ancient wheats in Wyoming.</p>","PeriodicalId":10931,"journal":{"name":"Crop, Forage and Turfgrass Management","volume":"9 2","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50118260","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":"Thanks to reviewers, Crop, Forage & Turfgrass Management, 2022","authors":"","doi":"10.1002/cft2.20226","DOIUrl":"https://doi.org/10.1002/cft2.20226","url":null,"abstract":"","PeriodicalId":10931,"journal":{"name":"Crop, Forage and Turfgrass Management","volume":"9 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50155612","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}