界定田间小气候导致的玉米田边缘效应

IF 0.8 Q3 AGRONOMY
Mark A. Licht, Tyler R. White
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Westgate and Vittetoe (<span>2017</span>) suggest weather patterns, field microclimates, herbicide drift, or even a combination of these factors may be to blame for low corn grain yields near the field edge.</p><p>We selected fields using five criteria: (1) field must be in a corn–soybean crop rotation with soybean planted adjacent to the southern or western field edge; (2) no tree line or roadway present between the selected cornfield and the adjacent soybean field; (3) cornfield row direction is parallel to the adjacent soybean field; (4) field contains one hybrid as selected by the cooperating farmer; and (5) cornfield has minimal slope with large contiguous areas of a single soil type to ensure transect placements contain consistent soil types across the transect length.</p><p>This selection resulted in four (Batavia, Eldon, Martinsburg, and Duncombe, Iowa) fields in 2019 and three fields (Batavia, Otho and Webster City, Iowa) in 2020. Abnormally dry conditions were experienced in 2019 with increasing intensity as the growing season progressed (NDMC, <span>2021</span>). However, in 2020 there was moderate to severe drought conditions in north central Iowa and abnormally dry to moderate drought conditions in southeast Iowa (NDMC, <span>2021</span>).</p><p>Farmer provided spatial yield data was used for grain yields and moistures and was extracted within 30 ft of each transect location. Grain yield was adjusted to 15% moisture. The SAS software (version 9.4, SAS Institute) was used to determine the means of the transect locations. A significance level of alpha = 0.10 was used. The statistical analysis performed was the SAS GLM procedure to assess the distance from field edge effect on grain yield and yield components. Transect was considered fixed while field and location were considered random. Means comparison was determined using a <i>T</i>-test at alpha = 0.10.</p><p>In 2019, yields increased by 38.4 bu/ac from 15 to 165 ft from the field edge at Duncombe (<i>p</i> = 0.0051) and 50.8 bu/ac at Martinsburg (p = 0.0507; Figure 1). In 2020, a field edge effect was only identified at Webster City (<i>p</i> ≤ 0.0001) where yields decreased 25.4 bu/ac from 15 to 45 ft but increased 46.1 bu/ac from 15 to 165 ft. While not statistically significant, numerical field edge effects were evident at Batavia and Eldon in 2019. Although field edge distance did not influence KR, KW increased with increased field edge distance at Batavia, Eldon, and Webster City (Table 1). Both Batavia and Eldon had KW increase as the distance increased from the field edge, however, both locations had KW decrease at 165 ft. Additionally, increased KNE was observed at Webster City. Interestingly, yield components were not significantly different at Duncombe and Martinsburg where yield differences were detected. As plant density was not different (data not shown), yield differences could be detectable through aggregate yield component differences that would be too small to detect individually. Additionally, the scale of data collection from spatial yield level (900 ft<sup>2</sup>) to the yield component level (10 consecutive plants) is certainly impacting yield component detection capabilities.</p><p>The 2019 growing season was considered normal to mild temperatures with adequate precipitation for much of Iowa. However, portions of southeast Iowa, where Batavia, Eldon, and Martinsburg are located, experienced drought stress in the latter part of the growing season. The lower KW at the field edge for both Batavia and Eldon correlates to stress during the grain fill period.</p><p>In Batavia 2020, KR was lower at the 15-ft field distance while the 45-, 105-, and 165-ft distances all had the same KR (<i>p</i> = 0.0772; Table 1). KNE was not influenced by distance from field edge at Batavia or Otho, but there was a strong effect at Webster City (<i>p</i> = 0.0029) with a 100 KNE increase from 45 to 105 ft and another 70 KNE increase to 165 ft. Individual KW at Webster City was increased by 0.005, 0.011, and 0.024 g at each field edge distance respectfully (<i>p</i> = 0.0088).</p><p>Cornfield edge effect is occurring in Iowa cornfields. This general trend is observed in other crops and is attributed to reaching maturity at different times (Cook &amp; Ingle, <span>1997</span>; Sparks et al., <span>1998</span>). 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Licht</b>: Conceptualization; funding acquisition; methodology; visualization; writing—review and editing. <b>Tyler R. White</b>: Data curation; investigation; visualization; writing—original draft.</p><p>The authors declare no conflicts of interest.</p>","PeriodicalId":10931,"journal":{"name":"Crop, Forage and Turfgrass Management","volume":null,"pages":null},"PeriodicalIF":0.8000,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cft2.20287","citationCount":"0","resultStr":"{\"title\":\"Defining cornfield edge effect due to field microclimates\",\"authors\":\"Mark A. Licht,&nbsp;Tyler R. 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引用次数: 0

摘要

在过去十年中,爱荷华州的农民注意到玉米(Zea mays L.)田的边缘效应,即玉米田外围的产量较低,而玉米田中部的产量逐渐增加。这种边缘效应主要出现在种植大豆 [Glycine max (L.) Merr.]、牧草或紫花苜蓿(Medicago sativa L.)作物的田块南边和西边。边缘效应在大多数年份都很明显,似乎在比正常温度高和/或更干燥的生长季节更为普遍。干旱胁迫在美国中西部地区并不少见(Woloszyn 等人,2021 年)。干旱的严重程度和持续时间决定了谷物产量受影响的程度(Heiniger,2018 年)。Westgate 和 Vittetoe(2017 年)认为,天气模式、田间小气候、除草剂漂移,甚至是这些因素的组合,都可能是造成田边玉米谷物产量低的原因:(1) 田地必须是玉米-大豆轮作,大豆种植在田地南部或西部边缘附近;(2) 所选玉米田和相邻大豆田之间没有树线或道路;(3) 玉米田行向与相邻大豆田平行;(4) 田地中含有合作农户选择的一种杂交种;(5) 玉米田坡度最小,有大面积的单一土壤类型,以确保横断面长度上的横断面位置包含一致的土壤类型。这样选择的结果是,2019 年有四块田(爱荷华州的巴达维亚、埃尔登、马丁斯堡和邓科姆),2020 年有三块田(爱荷华州的巴达维亚、奥索和韦伯斯特城)。2019 年出现了异常干旱的情况,随着生长季节的到来,干旱强度不断增加(NDMC,2021 年)。然而,2020 年爱荷华州中北部出现中度到严重干旱,爱荷华州东南部出现异常干旱到中度干旱(NDMC,2021 年)。农民提供的空间产量数据用于谷物产量和湿度,并在每个横断面位置 30 英尺范围内提取。谷物产量调整为 15%的水分。使用 SAS 软件(9.4 版,SAS Institute)确定横断面位置的平均值。显著性水平为 alpha = 0.10。采用 SAS GLM 程序进行统计分析,以评估田边距离对谷物产量和产量成分的影响。横断面被认为是固定的,而田块和地点被认为是随机的。平均值比较采用 T 检验,α = 0.10。2019 年,在 Duncombe(p = 0.0051)和 Martinsburg(p = 0.0507;图 1),距离田边 15 至 165 英尺处的产量增加了 38.4 bu/ac(p = 0.0051)和 50.8 bu/ac(p = 0.0507)。2020 年,仅在韦伯斯特城发现了田边效应(p ≤ 0.0001),从 15 英 尺到 45 英 尺 的 产 量 下 降 了 25.4 蒲 / 英 尺 , 但 从 15 英 尺 到 165 英 尺 的 产 量 上 升 了 46.1 蒲 / 英 尺 。虽然田边距离对 KR 没有影响,但在巴达维亚、埃尔登和韦伯斯特城,KW 随着田边距离的增加而增加(表 1)。巴达维亚和埃尔登的 KW 都随着与田边距离的增加而增加,但在 165 英尺处,两地的 KW 都有所下降。有趣的是,在邓科姆和马丁斯堡检测到的产量差异中,产量成分没有显著差异。由于植株密度没有差异(数据未显示),因此产量差异可通过总产量成分差异来检测,但这些差异太小,无法单独检测。此外,从空间产量水平(900 平方英尺)到产量成分水平(10 株连续植株)的数据收集规模肯定会影响产量成分的检测能力。爱荷华州大部分地区在 2019 年的生长季节气温正常至温和,降水充足。然而,爱荷华州东南部的巴达维亚、埃尔登和马丁斯堡所在的部分地区在生长季节的后半期经历了干旱胁迫。巴达维亚和埃尔登田边较低的 KW 与谷粒灌浆期的压力有关。在 2020 年的巴达维亚,15 英尺田边距离的 KR 较低,而 45、105 和 165 英尺距离的 KR 相同(p = 0.0772;表 1)。在巴达维亚和奥索,KNE 不受田边距离的影响,但在韦伯斯特市(p = 0.0029),KNE 从 45 英尺增加到 105 英尺,增加了 100 KNE,再增加到 165 英尺,增加了 70 KNE。在韦伯斯特市,每个田边距离的单株 KW 分别增加了 0.005、0.011 和 0.024 g(p = 0.0088)。爱荷华州的玉米田出现了田边效应,在其他作物中也观察到了这种普遍趋势,其原因是玉米成熟的时间不同(Cook &amp; Ingle, 1997; Sparks 等人, 1998)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Defining cornfield edge effect due to field microclimates

Defining cornfield edge effect due to field microclimates

Over the last decade, Iowa farmers have noticed a corn (Zea mays L.) field edge effect where yields are lower near the outside of the field and gradually increase toward the middle of the field. This edge effect is mostly noticed along the southern and western field edges of fields where soybean [Glycine max (L.) Merr.], pasture, or alfalfa (Medicago sativa L.) crops are grown. The edge effect is noticeable most years and seems to be more prevalent in growing seasons that are warmer and/or drier than normal. It is not uncommon for drought stress to occur in the Midwestern U.S (Woloszyn et al., 2021). The severity and length of time drought conditions occur determines the extent to which grain yields are affected (Heiniger, 2018). Westgate and Vittetoe (2017) suggest weather patterns, field microclimates, herbicide drift, or even a combination of these factors may be to blame for low corn grain yields near the field edge.

We selected fields using five criteria: (1) field must be in a corn–soybean crop rotation with soybean planted adjacent to the southern or western field edge; (2) no tree line or roadway present between the selected cornfield and the adjacent soybean field; (3) cornfield row direction is parallel to the adjacent soybean field; (4) field contains one hybrid as selected by the cooperating farmer; and (5) cornfield has minimal slope with large contiguous areas of a single soil type to ensure transect placements contain consistent soil types across the transect length.

This selection resulted in four (Batavia, Eldon, Martinsburg, and Duncombe, Iowa) fields in 2019 and three fields (Batavia, Otho and Webster City, Iowa) in 2020. Abnormally dry conditions were experienced in 2019 with increasing intensity as the growing season progressed (NDMC, 2021). However, in 2020 there was moderate to severe drought conditions in north central Iowa and abnormally dry to moderate drought conditions in southeast Iowa (NDMC, 2021).

Farmer provided spatial yield data was used for grain yields and moistures and was extracted within 30 ft of each transect location. Grain yield was adjusted to 15% moisture. The SAS software (version 9.4, SAS Institute) was used to determine the means of the transect locations. A significance level of alpha = 0.10 was used. The statistical analysis performed was the SAS GLM procedure to assess the distance from field edge effect on grain yield and yield components. Transect was considered fixed while field and location were considered random. Means comparison was determined using a T-test at alpha = 0.10.

In 2019, yields increased by 38.4 bu/ac from 15 to 165 ft from the field edge at Duncombe (p = 0.0051) and 50.8 bu/ac at Martinsburg (p = 0.0507; Figure 1). In 2020, a field edge effect was only identified at Webster City (p ≤ 0.0001) where yields decreased 25.4 bu/ac from 15 to 45 ft but increased 46.1 bu/ac from 15 to 165 ft. While not statistically significant, numerical field edge effects were evident at Batavia and Eldon in 2019. Although field edge distance did not influence KR, KW increased with increased field edge distance at Batavia, Eldon, and Webster City (Table 1). Both Batavia and Eldon had KW increase as the distance increased from the field edge, however, both locations had KW decrease at 165 ft. Additionally, increased KNE was observed at Webster City. Interestingly, yield components were not significantly different at Duncombe and Martinsburg where yield differences were detected. As plant density was not different (data not shown), yield differences could be detectable through aggregate yield component differences that would be too small to detect individually. Additionally, the scale of data collection from spatial yield level (900 ft2) to the yield component level (10 consecutive plants) is certainly impacting yield component detection capabilities.

The 2019 growing season was considered normal to mild temperatures with adequate precipitation for much of Iowa. However, portions of southeast Iowa, where Batavia, Eldon, and Martinsburg are located, experienced drought stress in the latter part of the growing season. The lower KW at the field edge for both Batavia and Eldon correlates to stress during the grain fill period.

In Batavia 2020, KR was lower at the 15-ft field distance while the 45-, 105-, and 165-ft distances all had the same KR (p = 0.0772; Table 1). KNE was not influenced by distance from field edge at Batavia or Otho, but there was a strong effect at Webster City (p = 0.0029) with a 100 KNE increase from 45 to 105 ft and another 70 KNE increase to 165 ft. Individual KW at Webster City was increased by 0.005, 0.011, and 0.024 g at each field edge distance respectfully (p = 0.0088).

Cornfield edge effect is occurring in Iowa cornfields. This general trend is observed in other crops and is attributed to reaching maturity at different times (Cook & Ingle, 1997; Sparks et al., 1998). However, we speculate cornfield edge effect to dry winds penetrating the field edge and disrupting the microclimate which relates more closely to Sklenicka and Salek (2004) in silage corn. We conclude grain yields are not affected until July or August when the stress is most severe and kernel number and kernel weight are being determined. We believe, as suggested by Westgate & Vittetoe (2017) microclimates are more likely to be disrupted, causing higher evapotranspiration rates and accelerating soil water usage compared to an area in the center of the field. This speculation is hardened as subsequent years have had more droughty conditions and more farmers noticing this phenomenon. Therefore, additional research is needed to draw stronger correlations between the field edge effect and air temperature, relative humidity, and soil moisture microclimates.

Mark A. Licht: Conceptualization; funding acquisition; methodology; visualization; writing—review and editing. Tyler R. White: Data curation; investigation; visualization; writing—original draft.

The authors declare no conflicts of interest.

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来源期刊
Crop, Forage and Turfgrass Management
Crop, Forage and Turfgrass Management Agricultural and Biological Sciences-Agronomy and Crop Science
CiteScore
1.30
自引率
16.70%
发文量
49
期刊介绍: Crop, Forage & Turfgrass Management is a peer-reviewed, international, electronic journal covering all aspects of applied crop, forage and grazinglands, and turfgrass management. The journal serves the professions related to the management of crops, forages and grazinglands, and turfgrass by publishing research, briefs, reviews, perspectives, and diagnostic and management guides that are beneficial to researchers, practitioners, educators, and industry representatives.
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