Peter J. A. Kleinman, Deanna L. Osmond, Laura E. Christianson, Don N. Flaten, James A. Ippolito, Helen P. Jarvie, Jason P. Kaye, Kevin W. King, April B. Leytem, Joshua M. McGrath, Nathan O. Nelson, Amy L. Shober, Douglas R. Smith, Kenneth W. Staver, Andrew N. Sharpley
Conservation practices that reduce nutrient and soil loss from agricultural lands to water are fundamental to watershed management programs. Avoiding trade-offs of conservation practices is essential to the successful mitigation of watershed phosphorus (P) losses. We review documented trade-offs associated with conservation practices, particularly those practices that are intended to control and trap P from agricultural sources. A regular theme is the trade-off between controlling P loss linked to sediment while increasing dissolved P losses (no-till, cover crops, vegetated buffers, constructed wetlands, sediment control basins). A variety of factors influence the degree to which these trade-offs occur, complicated by their interaction and uncertainties associated with climate change. However, acknowledging these trade-offs and anticipating their contribution to watershed outcomes are essential to the sustainability of conservation systems.
{"title":"Addressing conservation practice limitations and trade-offs for reducing phosphorus loss from agricultural fields","authors":"Peter J. A. Kleinman, Deanna L. Osmond, Laura E. Christianson, Don N. Flaten, James A. Ippolito, Helen P. Jarvie, Jason P. Kaye, Kevin W. King, April B. Leytem, Joshua M. McGrath, Nathan O. Nelson, Amy L. Shober, Douglas R. Smith, Kenneth W. Staver, Andrew N. Sharpley","doi":"10.1002/ael2.20084","DOIUrl":"10.1002/ael2.20084","url":null,"abstract":"<p>Conservation practices that reduce nutrient and soil loss from agricultural lands to water are fundamental to watershed management programs. Avoiding trade-offs of conservation practices is essential to the successful mitigation of watershed phosphorus (P) losses. We review documented trade-offs associated with conservation practices, particularly those practices that are intended to control and trap P from agricultural sources. A regular theme is the trade-off between controlling P loss linked to sediment while increasing dissolved P losses (no-till, cover crops, vegetated buffers, constructed wetlands, sediment control basins). A variety of factors influence the degree to which these trade-offs occur, complicated by their interaction and uncertainties associated with climate change. However, acknowledging these trade-offs and anticipating their contribution to watershed outcomes are essential to the sustainability of conservation systems.</p>","PeriodicalId":48502,"journal":{"name":"Agricultural & Environmental Letters","volume":"7 2","pages":""},"PeriodicalIF":2.6,"publicationDate":"2022-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://acsess.onlinelibrary.wiley.com/doi/epdf/10.1002/ael2.20084","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43408206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Prashant Waiker, Yener Ulus, Martin Tsz-Ki Tsui, Olav Rueppell
Urbanization has profound implications for associated ecosystems and organisms. Monitoring pollutants inform risk assessments for human and wildlife health. Honey bees (Apis mellifera) forage widely and collect food from many sources. Thus, they may be a robust integrator of environmental pollutants. Here, we collected honey bees from 10 different locations across the United States to quantify their content of total mercury (THg) and methylmercury (MeHg). Although our limited sample size prevented a meaningful statistical evaluation, we found that bees from urbanized areas had higher THg than those from rural areas, with suburban samples intermediate. The MeHg concentrations in all samples were below the detection limit. Despite its limited scope, this first preliminary dataset on Hg levels in honey bees across the United States suggests that urbanization may play a role in increasing Hg exposure to these pollinators, and that honey bees may be a useful biomonitor of the environmental presence of chemical pollutants.
{"title":"Mercury accumulation in honey bees trends upward with urbanization in the USA","authors":"Prashant Waiker, Yener Ulus, Martin Tsz-Ki Tsui, Olav Rueppell","doi":"10.1002/ael2.20083","DOIUrl":"10.1002/ael2.20083","url":null,"abstract":"<p>Urbanization has profound implications for associated ecosystems and organisms. Monitoring pollutants inform risk assessments for human and wildlife health. Honey bees (<i>Apis mellifera</i>) forage widely and collect food from many sources. Thus, they may be a robust integrator of environmental pollutants. Here, we collected honey bees from 10 different locations across the United States to quantify their content of total mercury (THg) and methylmercury (MeHg). Although our limited sample size prevented a meaningful statistical evaluation, we found that bees from urbanized areas had higher THg than those from rural areas, with suburban samples intermediate. The MeHg concentrations in all samples were below the detection limit. Despite its limited scope, this first preliminary dataset on Hg levels in honey bees across the United States suggests that urbanization may play a role in increasing Hg exposure to these pollinators, and that honey bees may be a useful biomonitor of the environmental presence of chemical pollutants.</p>","PeriodicalId":48502,"journal":{"name":"Agricultural & Environmental Letters","volume":"7 2","pages":""},"PeriodicalIF":2.6,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://acsess.onlinelibrary.wiley.com/doi/epdf/10.1002/ael2.20083","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45052836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<p>In a recent commentary article, Randall Jackson (<span>2022</span>) claims that U.S. maize croplands currently growing cattle feed can be converted to perennial pastures without incurring either a loss of beef production or agricultural expansion. Grass-finished cattle fatten up slower and reach lower slaughter weights than grain-finished cattle (Pelletier et al., <span>2010</span>). Therefore, to support present beef production using only pastures, more finishing cattle must be raised and slaughtered. The author recognizes this and attempts to quantify whether current maize production regions could instead grow sufficient perennial grasses and forages. He finds that an additional 7.6 million finishing cattle must be raised to produce exclusively grass-fed beef. He then calculates that 4.9 million ha of maize croplands growing cattle feed could, instead, grow sufficient grass to support these cattle.</p><p>However, the author makes a fundamental oversight—those 7.6 million additional finishing cattle must come from somewhere; they need mothers. Finishing cattle are supported on the “back end” by large cow-calf and stocker herds on pastures, who replace the current finishing cattle when they are slaughtered. Unlike pigs and chickens who can have many offspring per year, cows have long gestation periods of 9 mo, like humans, birthing at most one offspring each year. Cow gestation periods are so long and cattle maturity is so slow that cattle on pastures outnumber finishing cattle in feedlots by nearly five to one (Figure 1).</p><p>To raise 7.6 million more grass-finished cattle, U.S. ranchers would need to raise 7.7 million more cows, along with 7.8 million more calves and stocker cattle on pastures. Altogether, an exclusively grass-finished system requires 23.1 million (30%) more cattle to produce the same quantity of beef (Table 1), not 7.6 million (10%) more as the author models. We published these findings in a study that was cited by the author (Hayek & Garrett, <span>2018</span>), but he missed this central finding.</p><p>Larger grass-finished cattle herds require additional resources. Optimistically, a maximum of 71% of current production could be met if the United States shifted its maize feed crops for finishing cattle to perennial forages (Hayek & Garrett, <span>2018</span>). We assumed a similar potential forage yield on current maize croplands of 10.3 dry matter (DM) ha<sup>–1</sup> yr<sup>–1</sup>, which lies within the author's range of 8–12 DM ha<sup>–1</sup> yr<sup>–1</sup>. Maintaining these yields requires fertilizer inputs: we assumed forages were produced using conventional hay and alfalfa production, and the author's range of 8–12 DM ha<sup>–1</sup> yr<sup>–1</sup> is derived from a study of U.S. Upper Midwest pastures that applied fertilizer at a rate of 57 kg N ha<sup>–1</sup> yr<sup>–1</sup> (Oates et al., <span>2011</span>). These findings are consistent with multiple other studies, which demonstrate that grass-f
{"title":"Missing the grassland for the cows: Scaling grass-finished beef production entails tradeoffs—Comment on “Grazed perennial grasslands can match current beef production while contributing to climate mitigation and adaptation”","authors":"Matthew Hayek","doi":"10.1002/ael2.20073","DOIUrl":"10.1002/ael2.20073","url":null,"abstract":"<p>In a recent commentary article, Randall Jackson (<span>2022</span>) claims that U.S. maize croplands currently growing cattle feed can be converted to perennial pastures without incurring either a loss of beef production or agricultural expansion. Grass-finished cattle fatten up slower and reach lower slaughter weights than grain-finished cattle (Pelletier et al., <span>2010</span>). Therefore, to support present beef production using only pastures, more finishing cattle must be raised and slaughtered. The author recognizes this and attempts to quantify whether current maize production regions could instead grow sufficient perennial grasses and forages. He finds that an additional 7.6 million finishing cattle must be raised to produce exclusively grass-fed beef. He then calculates that 4.9 million ha of maize croplands growing cattle feed could, instead, grow sufficient grass to support these cattle.</p><p>However, the author makes a fundamental oversight—those 7.6 million additional finishing cattle must come from somewhere; they need mothers. Finishing cattle are supported on the “back end” by large cow-calf and stocker herds on pastures, who replace the current finishing cattle when they are slaughtered. Unlike pigs and chickens who can have many offspring per year, cows have long gestation periods of 9 mo, like humans, birthing at most one offspring each year. Cow gestation periods are so long and cattle maturity is so slow that cattle on pastures outnumber finishing cattle in feedlots by nearly five to one (Figure 1).</p><p>To raise 7.6 million more grass-finished cattle, U.S. ranchers would need to raise 7.7 million more cows, along with 7.8 million more calves and stocker cattle on pastures. Altogether, an exclusively grass-finished system requires 23.1 million (30%) more cattle to produce the same quantity of beef (Table 1), not 7.6 million (10%) more as the author models. We published these findings in a study that was cited by the author (Hayek & Garrett, <span>2018</span>), but he missed this central finding.</p><p>Larger grass-finished cattle herds require additional resources. Optimistically, a maximum of 71% of current production could be met if the United States shifted its maize feed crops for finishing cattle to perennial forages (Hayek & Garrett, <span>2018</span>). We assumed a similar potential forage yield on current maize croplands of 10.3 dry matter (DM) ha<sup>–1</sup> yr<sup>–1</sup>, which lies within the author's range of 8–12 DM ha<sup>–1</sup> yr<sup>–1</sup>. Maintaining these yields requires fertilizer inputs: we assumed forages were produced using conventional hay and alfalfa production, and the author's range of 8–12 DM ha<sup>–1</sup> yr<sup>–1</sup> is derived from a study of U.S. Upper Midwest pastures that applied fertilizer at a rate of 57 kg N ha<sup>–1</sup> yr<sup>–1</sup> (Oates et al., <span>2011</span>). These findings are consistent with multiple other studies, which demonstrate that grass-f","PeriodicalId":48502,"journal":{"name":"Agricultural & Environmental Letters","volume":"7 2","pages":""},"PeriodicalIF":2.6,"publicationDate":"2022-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://acsess.onlinelibrary.wiley.com/doi/epdf/10.1002/ael2.20073","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43017128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<p>Matthew Hayek's response to my commentary (Jackson, <span>2022</span>) is a valuable contribution to an important conversation about how we can provide for our wants and needs while improving our environment. My commentary purposefully simplified a complex topic to encourage interrogation of whether we have the capacity to meet current beef supply (5.9 billion kg yr<sup>–1</sup>) by finishing cattle on grassland rather than grain in feedlots. Hayek and I agree that this would require 7.6 million additional finishing cattle because grass-finished cattle take longer to finish and grow less overall (Hayek & Garrett, <span>2018</span>). My assessment was that we would need ∼16.1 million ha for all 20 million finishing cattle and that we could use the 4.9 million ha currently growing maize for cattle in feedlots, plus ∼12 million ha growing maize for ethanol, which constitutes a net loss of energy coupled with devastating environmental outcomes (Lark, <span>2020</span>). We seem to agree that there's enough land for the finishing cattle, but Hayek encourages us to consider the upstream supply chain and its ramifications.</p><p>Hayek observes that these additional finishing cattle would require more cows, calves, and stocker cattle (∼23.1 million more animals) to reproduce and replace the finishing cattle (Hayek & Garrett, <span>2018</span>), resulting in ∼18.6 million more grassland ha needed for grazing these feeder cattle. I argue that we desperately <i>need</i> this increased demand for grassland, especially if it replaces cropping systems prone to soil, carbon, and nutrient loss to the atmosphere and waters, where conservation interventions such as no-till, cover crops, and semi-annual forages (e.g., alfalfa) improve, but do not stop, these losses (Lintern et al., <span>2020</span>; Osterholz et al., <span>2019</span>; Roland et al., <span>2022</span>). Inasmuch as most of this feeder-cattle rearing is currently done on rangelands of the West, nearly half of this could occur on the ∼9 million ha of Great Plains land growing corn, soybeans, and alfalfa irrigated with water that is drawing down the Ogallala Aquifer (Carnes & Sanderson, <span>2022</span>; Evett et al., <span>2020</span>). Much of these products are fed to livestock, but according to the Iowa Corn website (www.iowacorn.org), much of the corn grain in the United States is exported (11% or ∼4.4 million ha) and much of it is considered “surplus” for “residual use” (9% or ∼3.6 million ha). It is important to note that the exports are sold by aggregator corporations to relatively affluent countries to build corporate wealth and often the surplus corn grain is “dumped” on global markets to suppress prices elsewhere (Hansen-Kuhn & Murphy, <span>2017</span>).</p><p>In more humid regions where feeder cattle are raised on pastures, most of this is done with continuous grazing, which undermines the yield potential of the pastures compared with well-managed rotational grazing t
Matthew Hayek对我的评论（Jackson，2022）的回应是对一场关于我们如何在改善环境的同时满足我们的需求的重要对话的宝贵贡献。我的评论有目的地简化了一个复杂的话题，以鼓励人们质疑我们是否有能力通过在草地上饲养牛而不是在饲养场饲养谷物来满足目前的牛肉供应（59亿公斤年）。哈耶克和我一致认为，这将需要760万头额外的精加工牛，因为草精加工牛需要更长的时间来完成加工，整体生长更少（Hayek&Garrett，2018）。我的评估是，我们将需要约1610万公顷的土地来饲养所有2000万头牛，我们可以使用目前在饲养场种植的490万公顷玉米来饲养牛，再加上约1200万公顷种植的玉米来生产乙醇，这构成了能源的净损失，并带来了毁灭性的环境后果（Lark，2020）。我们似乎同意有足够的土地来饲养肥牛，但哈耶克鼓励我们考虑上游供应链及其后果。哈耶克观察到，这些额外的肥牛将需要更多的奶牛、小牛和饲养牛（约2310万只动物）来繁殖和取代肥牛（哈耶克和加勒特，2018），从而使放牧这些饲养牛所需的草原面积增加约1860万公顷。我认为，我们迫切需要对
{"title":"Reply to “Missing the grassland for the cows: Scaling grass-finished beef production entails tradeoffs—Comment on ‘Grazed perennial grasslands can match current beef production while contributing to climate mitigation and adaptation’ ”","authors":"Randall D. Jackson","doi":"10.1002/ael2.20082","DOIUrl":"10.1002/ael2.20082","url":null,"abstract":"<p>Matthew Hayek's response to my commentary (Jackson, <span>2022</span>) is a valuable contribution to an important conversation about how we can provide for our wants and needs while improving our environment. My commentary purposefully simplified a complex topic to encourage interrogation of whether we have the capacity to meet current beef supply (5.9 billion kg yr<sup>–1</sup>) by finishing cattle on grassland rather than grain in feedlots. Hayek and I agree that this would require 7.6 million additional finishing cattle because grass-finished cattle take longer to finish and grow less overall (Hayek & Garrett, <span>2018</span>). My assessment was that we would need ∼16.1 million ha for all 20 million finishing cattle and that we could use the 4.9 million ha currently growing maize for cattle in feedlots, plus ∼12 million ha growing maize for ethanol, which constitutes a net loss of energy coupled with devastating environmental outcomes (Lark, <span>2020</span>). We seem to agree that there's enough land for the finishing cattle, but Hayek encourages us to consider the upstream supply chain and its ramifications.</p><p>Hayek observes that these additional finishing cattle would require more cows, calves, and stocker cattle (∼23.1 million more animals) to reproduce and replace the finishing cattle (Hayek & Garrett, <span>2018</span>), resulting in ∼18.6 million more grassland ha needed for grazing these feeder cattle. I argue that we desperately <i>need</i> this increased demand for grassland, especially if it replaces cropping systems prone to soil, carbon, and nutrient loss to the atmosphere and waters, where conservation interventions such as no-till, cover crops, and semi-annual forages (e.g., alfalfa) improve, but do not stop, these losses (Lintern et al., <span>2020</span>; Osterholz et al., <span>2019</span>; Roland et al., <span>2022</span>). Inasmuch as most of this feeder-cattle rearing is currently done on rangelands of the West, nearly half of this could occur on the ∼9 million ha of Great Plains land growing corn, soybeans, and alfalfa irrigated with water that is drawing down the Ogallala Aquifer (Carnes & Sanderson, <span>2022</span>; Evett et al., <span>2020</span>). Much of these products are fed to livestock, but according to the Iowa Corn website (www.iowacorn.org), much of the corn grain in the United States is exported (11% or ∼4.4 million ha) and much of it is considered “surplus” for “residual use” (9% or ∼3.6 million ha). It is important to note that the exports are sold by aggregator corporations to relatively affluent countries to build corporate wealth and often the surplus corn grain is “dumped” on global markets to suppress prices elsewhere (Hansen-Kuhn & Murphy, <span>2017</span>).</p><p>In more humid regions where feeder cattle are raised on pastures, most of this is done with continuous grazing, which undermines the yield potential of the pastures compared with well-managed rotational grazing t","PeriodicalId":48502,"journal":{"name":"Agricultural & Environmental Letters","volume":"7 2","pages":""},"PeriodicalIF":2.6,"publicationDate":"2022-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://acsess.onlinelibrary.wiley.com/doi/epdf/10.1002/ael2.20082","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43789109","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jarrod O. Miller, Amy L. Shober, Mark J. VanGessel
Drone flights are often only performed during the growing season, with no data collected once harvest has been completed, although they could be used to measure winter annual weed growth. Using a drone mounted with a multispectral sensor, we flew small plot corn (Zea mays L.) fertility, cover crop, and population studies at black layer and 0–14 d after harvest (DAH). Yields had positive correlations to normalized difference vegetation index (NDVI) at black layer but often had negative correlations to corn yields 0–14 DAH. After harvest, NDVI could be associated with weed growth, and negative correlations to yield could point to reduced corn canopy allowing light to reach late-season weeds. In fertility studies, excess nitrogen appears to increase weed biomass after harvest, which can be easily identified through drone imagery. Flights should be performed after corn harvest as weed growth may provide additional insight into management decisions.
无人机飞行通常只在生长季节进行，在收获完成后没有收集数据，尽管它们可以用来测量冬季的年度杂草生长情况。利用安装有多光谱传感器的无人机，对小块玉米(Zea mays L.)的肥力、覆盖作物和种群在黑层和收获后0-14 d (DAH)进行了研究。玉米产量与黑色层归一化植被指数(NDVI)呈显著正相关，与0 ~ 14 DAH呈显著负相关。收获后，NDVI可能与杂草生长有关，而与产量的负相关可能表明玉米冠层减少，使光照能够照射到晚季杂草。在生育力研究中，过量的氮似乎会增加收获后的杂草生物量，这可以通过无人机图像很容易地识别出来。飞行应在玉米收获后进行，因为杂草的生长可能为管理决策提供额外的见解。
{"title":"Post-harvest drone flights to measure weed growth and yield associations","authors":"Jarrod O. Miller, Amy L. Shober, Mark J. VanGessel","doi":"10.1002/ael2.20081","DOIUrl":"10.1002/ael2.20081","url":null,"abstract":"<p>Drone flights are often only performed during the growing season, with no data collected once harvest has been completed, although they could be used to measure winter annual weed growth. Using a drone mounted with a multispectral sensor, we flew small plot corn (<i>Zea mays</i> L.) fertility, cover crop, and population studies at black layer and 0–14 d after harvest (DAH). Yields had positive correlations to normalized difference vegetation index (NDVI) at black layer but often had negative correlations to corn yields 0–14 DAH. After harvest, NDVI could be associated with weed growth, and negative correlations to yield could point to reduced corn canopy allowing light to reach late-season weeds. In fertility studies, excess nitrogen appears to increase weed biomass after harvest, which can be easily identified through drone imagery. Flights should be performed after corn harvest as weed growth may provide additional insight into management decisions.</p>","PeriodicalId":48502,"journal":{"name":"Agricultural & Environmental Letters","volume":"7 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2022-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://acsess.onlinelibrary.wiley.com/doi/epdf/10.1002/ael2.20081","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43995427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Aminopeptidases are one of the extracellular hydrolytic enzymes that catalyze organic nitrogen (N) depolymerization and are commonly assayed using fluorogenic substrates. However, chromogenic substrates based on para-nitroaniline (pNA) developed for the study of aminopeptidases in the 1960s have been underutilized. To gauge the use of pNA substrates to assay soil aminopeptidases, a systematic literature review was conducted. We identified 61 studies that were nearly all limited to measuring leucine and/or glycine aminopeptidases, despite the commercial availability of at least six other aminopeptidase-specific pNA substrates. Assay parameters of scale (slurry vs. direct incubations), matrix type, buffer pH, substrate concentration, assay duration and temperature, termination, and colorimetry indicated a lack of standardization and a confusion of pNA with pNP substrates despite important differences in abiotic hydrolysis and absorbance maxima. Future studies should systematically evaluate and standardize these parameters and assess the sensitivity of other amino acid-specific aminopeptidases to carbon (C), N, and sulfur (S) cycling.
{"title":"Overlooked tools for studying soil nitrogen depolymerization: Aminopeptidase assays using nitroanilide substrates","authors":"Andrew J Margenot, Rachel C Daughtridge","doi":"10.1002/ael2.20079","DOIUrl":"10.1002/ael2.20079","url":null,"abstract":"<p>Aminopeptidases are one of the extracellular hydrolytic enzymes that catalyze organic nitrogen (N) depolymerization and are commonly assayed using fluorogenic substrates. However, chromogenic substrates based on <i>para</i>-nitroaniline (<i>p</i>NA) developed for the study of aminopeptidases in the 1960s have been underutilized. To gauge the use of <i>p</i>NA substrates to assay soil aminopeptidases, a systematic literature review was conducted. We identified 61 studies that were nearly all limited to measuring leucine and/or glycine aminopeptidases, despite the commercial availability of at least six other aminopeptidase-specific <i>p</i>NA substrates. Assay parameters of scale (slurry vs. direct incubations), matrix type, buffer pH, substrate concentration, assay duration and temperature, termination, and colorimetry indicated a lack of standardization and a confusion of <i>p</i>NA with <i>p</i>NP substrates despite important differences in abiotic hydrolysis and absorbance maxima. Future studies should systematically evaluate and standardize these parameters and assess the sensitivity of other amino acid-specific aminopeptidases to carbon (C), N, and sulfur (S) cycling.</p>","PeriodicalId":48502,"journal":{"name":"Agricultural & Environmental Letters","volume":"7 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2022-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://acsess.onlinelibrary.wiley.com/doi/epdf/10.1002/ael2.20079","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42447096","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
For decades, agronomists have invested time and resources to identify the optimum nitrogen (N) rates for cereal crops. The most common method for estimating the agronomic optimum N rate (AONR) is to design a field experiment with several N fertilizer rates and fit a regression model to the yield observations. Here, we concentrate on its accuracy and precision given choices of experimental design and statistical analysis. Our first finding is that the choice of functional form has a large agronomic effect on the estimate of the AONR, and this depends on the data-generating model. Our second finding is that improving the precision and accuracy of AONR estimates will demand an increase in the number of N rates and replications. Finally, we propose that using either the best-fitting model or a weighted model is preferable to always choosing either the linear-plateau (negative bias) or quadratic-plateau (positive bias) models.
{"title":"How can we estimate optimum fertilizer rates with accuracy and precision?","authors":"Fernando E. Miguez, Hanna Poffenbarger","doi":"10.1002/ael2.20075","DOIUrl":"10.1002/ael2.20075","url":null,"abstract":"<p>For decades, agronomists have invested time and resources to identify the optimum nitrogen (N) rates for cereal crops. The most common method for estimating the agronomic optimum N rate (AONR) is to design a field experiment with several N fertilizer rates and fit a regression model to the yield observations. Here, we concentrate on its accuracy and precision given choices of experimental design and statistical analysis. Our first finding is that the choice of functional form has a large agronomic effect on the estimate of the AONR, and this depends on the data-generating model. Our second finding is that improving the precision and accuracy of AONR estimates will demand an increase in the number of N rates and replications. Finally, we propose that using either the best-fitting model or a weighted model is preferable to always choosing either the linear-plateau (negative bias) or quadratic-plateau (positive bias) models.</p>","PeriodicalId":48502,"journal":{"name":"Agricultural & Environmental Letters","volume":"7 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2022-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://acsess.onlinelibrary.wiley.com/doi/epdf/10.1002/ael2.20075","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46443744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Natalie P. Lounsbury, Nicholas D. Warren, Julia Hobbie, Heather Darby, Matthew R. Ryan, David A. Mortensen, Richard G. Smith
It is common to use mass-based units (e.g., kg ha–1) to describe cover crop seeding rates. However, this convention obscures important information about seed size and resulting plant density in the field, which may be linked to cover crop performance and ecosystem services. Seed counts of 27 lots of commercially available winter rye (Secale cereale L.) spanned a wide range from 28,000 to 50,000 seeds kg–1. If the lots with the lowest and highest seed counts were seeded at a common mass-based seeding rate of 125 kg ha–1, it would result in a nearly twofold difference in density-based seeding rate, or 3.0 and 5.6 million live seeds ha–1. Including density-based metrics such as live seeds per area and resulting in-field plant density in research will help advance our understanding of cover crop management, and these efforts will make it easier for farmers and policymakers to tailor cover cropping practices for specific goals.
通常使用以质量为基础的单位(例如，kg ha-1)来描述覆盖作物的播种率。然而，这种惯例掩盖了种子大小和由此产生的田间植物密度的重要信息，这些信息可能与覆盖作物的生产性能和生态系统服务有关。27批市售的冬季黑麦(Secale cereale L.)种子数量从28,000到50,000粒/ kg不等。如果种子数量最少和最高的地块以125 kg ha-1的共同质量播种率播种，则基于密度的播种率相差近两倍，即300万和560万粒活种子ha-1。在研究中纳入基于密度的指标，如每面积活种和由此产生的田间植物密度，将有助于增进我们对覆盖作物管理的理解，这些努力将使农民和决策者更容易为特定目标量身定制覆盖作物实践。
{"title":"Seed size variability has implications for achieving cover cropping goals","authors":"Natalie P. Lounsbury, Nicholas D. Warren, Julia Hobbie, Heather Darby, Matthew R. Ryan, David A. Mortensen, Richard G. Smith","doi":"10.1002/ael2.20080","DOIUrl":"10.1002/ael2.20080","url":null,"abstract":"<p>It is common to use mass-based units (e.g., kg ha<sup>–1</sup>) to describe cover crop seeding rates. However, this convention obscures important information about seed size and resulting plant density in the field, which may be linked to cover crop performance and ecosystem services. Seed counts of 27 lots of commercially available winter rye (<i>Secale cereale</i> L.) spanned a wide range from 28,000 to 50,000 seeds kg<sup>–1</sup>. If the lots with the lowest and highest seed counts were seeded at a common mass-based seeding rate of 125 kg ha<sup>–1</sup>, it would result in a nearly twofold difference in density-based seeding rate, or 3.0 and 5.6 million live seeds ha<sup>–1</sup>. Including density-based metrics such as live seeds per area and resulting in-field plant density in research will help advance our understanding of cover crop management, and these efforts will make it easier for farmers and policymakers to tailor cover cropping practices for specific goals.</p>","PeriodicalId":48502,"journal":{"name":"Agricultural & Environmental Letters","volume":"7 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2022-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://acsess.onlinelibrary.wiley.com/doi/epdf/10.1002/ael2.20080","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"51338370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kabindra Adhikari, Douglas R. Smith, Chad Hajda, Phillip R. Owens
Studies show a strong relationship between soil health and crop yield, but those relating soil health and grain quality are limited. We studied the relationship between soil health and grain protein and oil content from a corn (Zea mays L.) field in Texas. Protein and oil content data were collected in the field with a CropScan monitor. Soil health values were measured at 202 locations using the Haney Soil Health Tool. We first mapped protein and oil content using apparent electrical conductivity (ECa) and 14 terrain attributes as predictors, and we then quantified the relationship with data from sample locations. Soil health was positively correlated with protein and oil content, but the relationship was rather weak. Soil health accounted for up to 13% of the variability in protein (p < .001) and between 2 and 17% in oil content (p < .1) depending on soil map unit. Their spatial distribution was mostly influenced by elevation, ECa, and wetness index. We do not recommend estimating grain protein and oil content with the Haney Soil Health Tool; however, we suggest investigating such relationship across different soil and agronomic conditions for further verification.
{"title":"Can soil health explain grain quality? A case study of a corn field in Texas","authors":"Kabindra Adhikari, Douglas R. Smith, Chad Hajda, Phillip R. Owens","doi":"10.1002/ael2.20078","DOIUrl":"10.1002/ael2.20078","url":null,"abstract":"<p>Studies show a strong relationship between soil health and crop yield, but those relating soil health and grain quality are limited. We studied the relationship between soil health and grain protein and oil content from a corn (<i>Zea mays</i> L.) field in Texas. Protein and oil content data were collected in the field with a CropScan monitor. Soil health values were measured at 202 locations using the Haney Soil Health Tool. We first mapped protein and oil content using apparent electrical conductivity (ECa) and 14 terrain attributes as predictors, and we then quantified the relationship with data from sample locations. Soil health was positively correlated with protein and oil content, but the relationship was rather weak. Soil health accounted for up to 13% of the variability in protein (<i>p</i> < .001) and between 2 and 17% in oil content (<i>p</i> < .1) depending on soil map unit. Their spatial distribution was mostly influenced by elevation, ECa, and wetness index. We do not recommend estimating grain protein and oil content with the Haney Soil Health Tool; however, we suggest investigating such relationship across different soil and agronomic conditions for further verification.</p>","PeriodicalId":48502,"journal":{"name":"Agricultural & Environmental Letters","volume":"7 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2022-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://acsess.onlinelibrary.wiley.com/doi/epdf/10.1002/ael2.20078","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44917131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Krishna B. Bhandari, Veronica Acosta-Martínez, Lumarie Pérez-Guzmán, Charles P. West
The decline in groundwater supply in the Texas High Plains is forcing some growers to convert center-pivot irrigated cropland to dryland production. Transitioning toward reduced water input can lead to declines in soil health. We assessed short-term changes in soil health indicators in two transition scenarios: (a) from high irrigation method to low irrigation method (center pivot to subsurface drip) and (b) from high irrigation method to dryland (center pivot to dryland), in comparison to continuous center-pivot management. We monitored changes in chemical and biological indicators in four fields for each transition scenario and in three pivot-irrigated fields. There were declines in soil water content, potassium (K), sodium (Na), and soil organic carbon with transition from irrigation to reduced irrigation and dryland. Severe drought in the final year revealed reduced amounts of multi-enzyme activities, total ester-linked fatty acid methyl ester (EL-FAME), and total fungi. Transitioning to low water-input management in this environment complicates efforts to maintain microbial components of soil health. Longer-term comparisons are needed to detect slow changes in soil health indicators on producers’ fields.
{"title":"Soil health within transitions from irrigation to limited irrigation and dryland management","authors":"Krishna B. Bhandari, Veronica Acosta-Martínez, Lumarie Pérez-Guzmán, Charles P. West","doi":"10.1002/ael2.20077","DOIUrl":"10.1002/ael2.20077","url":null,"abstract":"<p>The decline in groundwater supply in the Texas High Plains is forcing some growers to convert center-pivot irrigated cropland to dryland production. Transitioning toward reduced water input can lead to declines in soil health. We assessed short-term changes in soil health indicators in two transition scenarios: (a) from high irrigation method to low irrigation method (center pivot to subsurface drip) and (b) from high irrigation method to dryland (center pivot to dryland), in comparison to continuous center-pivot management. We monitored changes in chemical and biological indicators in four fields for each transition scenario and in three pivot-irrigated fields. There were declines in soil water content, potassium (K), sodium (Na), and soil organic carbon with transition from irrigation to reduced irrigation and dryland. Severe drought in the final year revealed reduced amounts of multi-enzyme activities, total ester-linked fatty acid methyl ester (EL-FAME), and total fungi. Transitioning to low water-input management in this environment complicates efforts to maintain microbial components of soil health. Longer-term comparisons are needed to detect slow changes in soil health indicators on producers’ fields.</p>","PeriodicalId":48502,"journal":{"name":"Agricultural & Environmental Letters","volume":"7 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2022-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://acsess.onlinelibrary.wiley.com/doi/epdf/10.1002/ael2.20077","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46874839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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