Cade P. Cooper, James P. Muir, Kimberly B. Wellmann, Eunsung Kan, Lisandro J. Entio, Jeff A. Brady, Katherine Hays, Jaehak Jeong
Background
Biochar (BC) amendment to soils can affect crop yields negatively, especially during the first season following application, by binding essential nutrients; however, little data exist on its effects on warm-climate forage yields and nutritive values. We determined the effects of BC (0, 5, 10 Mg DM ha−1), dairy manure (0 and 10 Mg DM ha−1), soil type (loamy sand, sandy loam, clay loam), and tillage practices (till [incorporation of soil amendments with tillage] vs. no till [soil amendments surface application]) on the nutrient profile and dry matter yield (DMY) of Bermudagrass (Cynodon dactylon (L.) Pers.), maize (Zea mays L.), and sorghum-Sudan (Sorghum drummondii (Nees ex Steud.) Millsp. & Chase).
Methods
Bermudagrass was harvested at the boot stage, sorghum-Sudan when the canopy reached 90% light interception, and the maize 90–120 days after planting as silage. Samples were dried and analyzed for nutrients and DMY.
Results
BC and manure application were not detrimental to forage production or nutritive value to cattle in the first growing season.
Conclusions
Effects varied across tillage and soil type; thus, it is essential to consider soil texture and nutrient makeup before choosing the proper tillage and amendments. Longer study periods may produce different results since, over time, BC can act as a slow-release source of nutrients.
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Runze Wang, Huakun Zhou, Yayu Huang, Allan Degen, Xueyan Du, Muhammad Irfan Malik, Rongzhen Zhong, Binqiang Bai, Lizhuang Hao
Background
Yak (Poephagus grunniens) production on the Qinghai–Tibet Plateau is influenced heavily by the quality of the natural forage, which can vary significantly in both quality and quantity. Therefore, timely and accurate monitoring of forage variables is essential for optimizing livestock production in this region.
Methods
This study investigated the use of near-infrared spectroscopy (NIRS) as a tool for estimating the composition and quality of natural forage. A total of 301 natural forage samples were collected, and their spectral data were acquired using NIRS. Conventional methods were used to measure the forage composition, and predictive models were developed based on the spectral data.
Results
Our findings indicate that NIRS can accurately predict the contents of crude protein, acid detergent fiber, and neutral detergent fiber. However, it demonstrated less accuracy in predicting dry matter digestibility, gross energy yield, and methane production.
Conclusions
The application of NIRS for assessing the nutritional composition of forages on the Qinghai–Tibet Plateau is a key advancement for the livestock industry. Understanding forage nutrition enables informed feeding strategies and improvement of livestock production. Future research should refine predictive models to ensure sustainable forage management and enhance livestock productivity in this unique ecological environment.
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<p>It is common in agronomic experiments to have data on a range of plant traits across treatments comprising levels of one factor, combinations of two or more factors, and/or repeat measures across time or some other entity such as soil depth. In this case, traditional univariate ANOVA, which examines the measured traits one by one and is amenable to the development of complex statistical models, risks missing overarching patterns that might emerge if the data were analyzed as an interacting set where multivariate trait associations can be elucidated. Multivariate analyses, on the other hand, do consider multiple traits simultaneously but often struggle to accommodate complex treatment combinations. For more complex agronomic data sets, the writer has often used principal component analysis (PCA) as a data exploration and pattern detection tool, to identify the salient features of a data set from a multivariate perspective. This editorial aims to introduce PCA to readers unfamiliar with it, illustrate by example how PCA works, and to demonstrate the versatility of PCA by outlining some applications of PCA that the writer has developed for particular data sets during a 40-year research career. It is not possible in a brief editorial to provide a textbook-level and statistically robust coverage of the topic of PCA; detailed expositions of PCA have been produced by Joliffe (<span>1986</span>, <span>2002</span>) and many others. A motivation to write has been that I often see PCA results published in ways that reflect incomplete understanding of its mathematical properties and behavior. However, these notes are not intended as a substitute for consultation with a professional statistician.</p><p>A notable example of elucidation of trait associations in a large data set through PCA is the worldwide leaf economic spectrum (Wright et al., <span>2004</span>). These authors found that for a set of six leaf traits (leaf lifespan, mass per unit area, photosynthetic capacity, dark respiration rate, and N and P concentrations), PCA of data for 2548 species from 175 sites worldwide yielded a PC1, explaining 74.4% of data variation with loading coefficient absolute values ranging from 0.79 to 0.91 and associating high photosynthetic capacity and dark respiration with high leaf N and P concentrations, but lower mass per unit area and shorter longevity. This PC can be interpreted as defining an ecological resource trade-off across environments between high nutrient-resource investment for high productivity with high turnover and low investment for low productivity with slower turnover.</p><p>In a perennial ryegrass (<i>Lolium perenne</i> L.) quantitative trait loci (QTL) mapping population, Sartie et al. (<span>2011</span>) used PCA to elucidate functional associations between leaf formation traits contributing to plant yield. Remarkably, PCA was able to resolve independent contributions of the trait leaf elongation rate (LER) to plant development. For autumn da
在农艺试验中，在不同处理中获得一系列植物性状的数据是很常见的，包括一个因素的水平，两个或多个因素的组合，和/或跨时间或其他一些实体（如土壤深度）重复测量。在这种情况下，传统的单变量方差分析，一个接一个地检查测量的特征，并且适合复杂统计模型的发展，如果将数据作为一个相互作用的集合进行分析，可以阐明多变量特征关联，则可能会遗漏总体模式。另一方面，多变量分析确实同时考虑多种特征，但往往难以适应复杂的治疗组合。对于更复杂的农艺数据集，作者经常使用主成分分析（PCA）作为数据探索和模式检测工具，从多变量角度识别数据集的显著特征。这篇社论旨在向不熟悉PCA的读者介绍PCA，举例说明PCA是如何工作的，并通过概述作者在40年的研究生涯中为特定数据集开发的PCA的一些应用来展示PCA的多功能性。这是不可能在一个简短的社论提供一个教科书水平和统计稳健的覆盖PCA的主题；Joliffe（1986, 2002）和其他许多人对PCA进行了详细的阐述。写这篇文章的动机是，我经常看到发表的PCA结果反映了对其数学性质和行为的不完全理解。但是，这些说明并不打算代替与专业统计学家的咨询。通过PCA在大数据集中阐明性状关联的一个显著例子是全球叶片经济谱（Wright et al., 2004）。这些作者发现,一组六叶性状(叶寿命、单位面积上的质量、光合能力、暗呼吸速率,和N和P浓度),主成分分析的数据来自全世界175个网站的2548个物种产生PC1,解释74.4%的数据变化与载荷系数绝对值范围从0.79到0.91,将较高的光合能力和暗呼吸与高叶氮和磷的浓度,但较低的单位面积上的质量和较短的寿命。这个PC可以被解释为定义了一种跨环境的生态资源权衡：高营养资源投资以获得高周转率的高生产率，低投资以获得低周转率的低生产率。在一个多年生黑麦草（Lolium perenne L.）数量性状位点（QTL）作图群体中，Sartie等（2011）利用主成分分析法阐明了叶片形成性状对植物产量的功能关联。值得注意的是，主成分分析能够解决叶片伸长率（LER）性状对植物发育的独立贡献。对于秋季数据，PC1占数据变异的32%，高叶片伸长率与补偿性叶片伸长持续时间短、叶片出现频率高、分蘖数减少和分蘖重增加相关，而这种性状相关性与植株产量无关。在春季数据中观察到几乎相同的PC1占数据变化的33%。在秋季数据中，占数据变异量15%的PC3与叶片长、分蘖数和植株干重的增加独立相关。春季数据中PC2和PC3的性状关联相似但不相同，分别占数据变异的22%和15%（表S9）。因此，从植物育种的角度来看，PCA能够区分哪些基因型增加LER对植物产量是中性的，哪些基因型增加LER对植物产量有贡献。这些pca是利用202个基因型的3个植物克隆重复的平均性状数据生成的。在QTL研究中，当克隆重复的数据作为单独的列输入PCA时，每个性状的加载系数在不同的重复中通常是相似的，并且显著相同的频率比随机机会预期的要高（表S10）。这可能反映了基因相同的植物克隆复制的表型相似性。在同一QTL定位群体的单独实验中，鉴定出PC1中对单株种子产量贡献最大的性状之一（解释了24.5%的数据变异）是每小穗的小花数。同时，千粒重仅在PC4时对种子产量有贡献，解释了10.8%的数据变化，并且在很大程度上独立于种子产量的其他组成性状，让人想起表1中的右旋PC2 (Sartie et al., 2018；表S11)。这些都是其他数据分析方法无法轻易获得的见解。在Weerarathne（2021）对220种多年生黑麦草基因型抗旱性差异的研究中，PCA-PC3占13。 4%的变异被解释为产生高干重和减少土壤水分枯竭的植物基因型，这是一种与耐旱性育种相关的性状。选择该PC的20株高分株和15株低分株，所选性状关联提升至PC1，在后续实验中占数据变异的68.2%（表S12a，b）。这表明，PCA中由特定功能性状关联解释的方差比例取决于群体中表达该性状关联的个体数量。在少数个体表现出突出特征或许多个体表现出微妙特征的情况下，可以解释低比例的变异。特征值在这个意义上是模糊的。Sumanasena（2003）对三种土壤深度（0 - 50,50 - 100和100 - 200mm）的根系参数进行了实地研究，比较了多年生黑麦草（L. perenne L.）和白三叶草（Trifolium repens L.）在两种磷肥施用水平、三种灌溉处理、四次重复和12月、2月和4月的重复收获。由于该实验有两个“重复测量”因素，即土壤深度和时间，因此仅考虑一个重复测量因素（通常是时间）的标准“重复测量”方差分析程序无法有效地统计分析数据。在这种情况下，对每一种土壤深度的48组根长密度（cm根cm−3土壤）进行了分析，作为PCA中的三个变量，每个收获日期分别进行了分析。所得的PC1是一个“大小”PC，表明在特定处理下所有三种土壤深度的根长密度增加或减少（在收获日期平均解释了79.8%的数据变异）。PC2表示深根或浅根，平均占数据变化的12.7%。PC评分的方差分析显示，尽管特征值仅为0.42，但PC1在所有月份都有治疗效果，PC2在4月份也有治疗效果（表S13）。虽然在引用的研究中没有以这种方式呈现，但使用这种方法，一个包含所有三个收获日期的单一PCA，而不是每个收获日期的单独PCA，将产生144个PC分数集，用于土壤深度和深根性的总根长度密度。然后，可以将分数提交给重复测量的方差分析，分析物种、灌溉和肥料对总根质量（PC1）和深根质量（PC2）的影响及其相互作用，从而将所有实验设计因素纳入对PC1和PC2分数进行的单因素方差分析。作者对用主成分分析小数据集持谨慎态度，但在一个案例中，对来自14名农民的调查结果的12个农场系统描述符的数据进行主成分分析，发现了农民饲料供应决策与牛奶生产数据之间高度可信的关联(Ordóñez等人，2004；表S14系列)。上述PCA输出的解释示例与Liu等人（2023）采用的方法形成对比。本文收集了中国羊草（Leymus chinensis） 42个种质系的资料。来自中国北部和蒙古不同地理位置的Tzvelev。将抗旱性、根茎延伸、土壤改良和干草产量等26个性状的数据提交主成分分析，得到42个种质系8个特征值为>；1的负荷系数矩阵和PC得分。很少有人试图“解释”上述pc的功能特征关联。相反，个人电脑的分数被汇总成一个“综合”指数，称为“f”。F值高表明种质系具有“优良的生态功能性状”。对相同的数据进行聚类分析，将42个种质系划分为4组。给出了PC1-PC2双标图，这也表明了这些pc中的聚类分离。鉴定了F值数值最高的10个和数值最低的10个种质系。探讨了F与纬度、经度和海拔的相关性。最后，确定了最能代表耐旱性、根茎延伸和土壤改良的26个变量的子集，并进行了进一步的pca或隶属函数分析，以生成对这三种能力进行排名的种质系指数。通过评论，笔者发现Liu et al.（2023）给出的F值可以通过一个[A] × [B]矩阵乘法来再现，其中[A]为8个PC分数F1的集合。他们的表3和[B]中的F8是由他们的表2中的特征值形成的列向量，用1/0.8055的因子进行缩放，说明累积方差。 对于作者来说，像
{"title":"Notes on the use of principal component analysis in agronomic research","authors":"Cory Matthew","doi":"10.1002/glr2.70003","DOIUrl":"https://doi.org/10.1002/glr2.70003","url":null,"abstract":"<p>It is common in agronomic experiments to have data on a range of plant traits across treatments comprising levels of one factor, combinations of two or more factors, and/or repeat measures across time or some other entity such as soil depth. In this case, traditional univariate ANOVA, which examines the measured traits one by one and is amenable to the development of complex statistical models, risks missing overarching patterns that might emerge if the data were analyzed as an interacting set where multivariate trait associations can be elucidated. Multivariate analyses, on the other hand, do consider multiple traits simultaneously but often struggle to accommodate complex treatment combinations. For more complex agronomic data sets, the writer has often used principal component analysis (PCA) as a data exploration and pattern detection tool, to identify the salient features of a data set from a multivariate perspective. This editorial aims to introduce PCA to readers unfamiliar with it, illustrate by example how PCA works, and to demonstrate the versatility of PCA by outlining some applications of PCA that the writer has developed for particular data sets during a 40-year research career. It is not possible in a brief editorial to provide a textbook-level and statistically robust coverage of the topic of PCA; detailed expositions of PCA have been produced by Joliffe (<span>1986</span>, <span>2002</span>) and many others. A motivation to write has been that I often see PCA results published in ways that reflect incomplete understanding of its mathematical properties and behavior. However, these notes are not intended as a substitute for consultation with a professional statistician.</p><p>A notable example of elucidation of trait associations in a large data set through PCA is the worldwide leaf economic spectrum (Wright et al., <span>2004</span>). These authors found that for a set of six leaf traits (leaf lifespan, mass per unit area, photosynthetic capacity, dark respiration rate, and N and P concentrations), PCA of data for 2548 species from 175 sites worldwide yielded a PC1, explaining 74.4% of data variation with loading coefficient absolute values ranging from 0.79 to 0.91 and associating high photosynthetic capacity and dark respiration with high leaf N and P concentrations, but lower mass per unit area and shorter longevity. This PC can be interpreted as defining an ecological resource trade-off across environments between high nutrient-resource investment for high productivity with high turnover and low investment for low productivity with slower turnover.</p><p>In a perennial ryegrass (<i>Lolium perenne</i> L.) quantitative trait loci (QTL) mapping population, Sartie et al. (<span>2011</span>) used PCA to elucidate functional associations between leaf formation traits contributing to plant yield. Remarkably, PCA was able to resolve independent contributions of the trait leaf elongation rate (LER) to plant development. For autumn da","PeriodicalId":100593,"journal":{"name":"Grassland Research","volume":"4 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/glr2.70003","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143749918","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}
María José Beribe, Pablo Barletta, Jorge Omar Scheneiter
Background
Tall fescue is sensitive to sowing depth and, in the Pampas region of Argentina, its sowing is often delayed from autumn (average air temperature 18.5°C) to winter (average air temperature 10.0°C). Since tall fescue is sensitive to the sowing depth, and temperature determines the emergence period, this study aimed to evaluate the effect of sowing depth at different times on seedling emergence and herbage yield.
Methods
Two field experiments were carried out in Pergamino, Buenos Aires province, Argentina, to evaluate a summer-active tall fescue at two sowing times and five sowing depths. The emergence of seedlings and the herbage yield in the year of sowing were determined.
Results
Seedling emergence was maximal when sown at 1.2–1.5 cm depth and at 230 growing degree days (GDD) in early autumn and 257 GDD in winter. In both years and sowing seasons, herbage yield was positively related to the number of seedlings at maximum emergence.
Conclusions
No differences in seedling emergence were observed between the autumn and winter sowings, and the emergence of tall fescue was well explained by the thermal time. The concept of “critical depth” was determined as the sowing depth at which the greatest seedling emergence and forage yield are achieved.
{"title":"Seedling emergence and herbage yield of summer-active tall fescue sown at different times and sowing depths","authors":"María José Beribe, Pablo Barletta, Jorge Omar Scheneiter","doi":"10.1002/glr2.12109","DOIUrl":"https://doi.org/10.1002/glr2.12109","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Tall fescue is sensitive to sowing depth and, in the Pampas region of Argentina, its sowing is often delayed from autumn (average air temperature 18.5°C) to winter (average air temperature 10.0°C). Since tall fescue is sensitive to the sowing depth, and temperature determines the emergence period, this study aimed to evaluate the effect of sowing depth at different times on seedling emergence and herbage yield.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Two field experiments were carried out in Pergamino, Buenos Aires province, Argentina, to evaluate a summer-active tall fescue at two sowing times and five sowing depths. The emergence of seedlings and the herbage yield in the year of sowing were determined.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Seedling emergence was maximal when sown at 1.2–1.5 cm depth and at 230 growing degree days (GDD) in early autumn and 257 GDD in winter. In both years and sowing seasons, herbage yield was positively related to the number of seedlings at maximum emergence.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>No differences in seedling emergence were observed between the autumn and winter sowings, and the emergence of tall fescue was well explained by the thermal time. The concept of “critical depth” was determined as the sowing depth at which the greatest seedling emergence and forage yield are achieved.</p>\u0000 </section>\u0000 </div>","PeriodicalId":100593,"journal":{"name":"Grassland Research","volume":"4 1","pages":"57-65"},"PeriodicalIF":0.0,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/glr2.12109","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143749479","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}
Sultan Begna, Brenda Perez, Abdelmoneim Z. Mohamed, Katherine Swanson, E. Charles Brummer, Dong Wang, Khaled Bali, Daniel H. Putnam
Background
The development of alfalfa cultivars with improved digestibility may minimize the yield-quality tradeoff, enabling higher quality with late-harvested forage and possibly higher yields.
Methods
An irrigated experiment conducted over 4 years compared 28-d harvest schedules with 35-d harvest schedules and an alternating 21-d and 35-d schedule. Four conventional cultivars and four cultivars developed for higher digestibility were grown under each schedule.
Results
Delayed cutting (35-d) yields were 16% greater and the staggered treatments were 6% higher than the 28-d strategy. The nutritive value decreased significantly with the 35-d schedule, but a “staggered” system provided nutritive value similar to the 28-d schedule while achieving higher yields. The nutritive value of cultivars was in the order of HarvXtra>Hi-Gest> conventional cultivars. The HarvXtra but not Hi-Gest cultivars achieved similar digestibility under the 35-d cutting schedule compared with conventional cultivars on a 28-d schedule.
Conclusions
This study clearly demonstrates that higher nutritive value cultivars of fall dormancy 6–9 grown with staggered or late cutting schedules can increase yields while maintaining higher nutritive value. The combination of staggered or late schedules with improved cultivars can maximize yields while maintaining the nutritive value of alfalfa, potentially breaking the alfalfa yield-quality tradeoff.
{"title":"Impact of novel harvest strategies and improved cultivars on alfalfa yield and nutritive value in a Mediterranean environment","authors":"Sultan Begna, Brenda Perez, Abdelmoneim Z. Mohamed, Katherine Swanson, E. Charles Brummer, Dong Wang, Khaled Bali, Daniel H. Putnam","doi":"10.1002/glr2.12112","DOIUrl":"https://doi.org/10.1002/glr2.12112","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The development of alfalfa cultivars with improved digestibility may minimize the yield-quality tradeoff, enabling higher quality with late-harvested forage and possibly higher yields.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>An irrigated experiment conducted over 4 years compared 28-d harvest schedules with 35-d harvest schedules and an alternating 21-d and 35-d schedule. Four conventional cultivars and four cultivars developed for higher digestibility were grown under each schedule.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Delayed cutting (35-d) yields were 16% greater and the staggered treatments were 6% higher than the 28-d strategy. The nutritive value decreased significantly with the 35-d schedule, but a “staggered” system provided nutritive value similar to the 28-d schedule while achieving higher yields. The nutritive value of cultivars was in the order of HarvXtra>Hi-Gest> conventional cultivars. The HarvXtra but not Hi-Gest cultivars achieved similar digestibility under the 35-d cutting schedule compared with conventional cultivars on a 28-d schedule.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>This study clearly demonstrates that higher nutritive value cultivars of fall dormancy 6–9 grown with staggered or late cutting schedules can increase yields while maintaining higher nutritive value. The combination of staggered or late schedules with improved cultivars can maximize yields while maintaining the nutritive value of alfalfa, potentially breaking the alfalfa yield-quality tradeoff.</p>\u0000 </section>\u0000 </div>","PeriodicalId":100593,"journal":{"name":"Grassland Research","volume":"4 1","pages":"79-87"},"PeriodicalIF":0.0,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/glr2.12112","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143749480","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}
Michael B. Dodd, Ina B. Pinxterhuis, H. Glenn Judson
Forage plantain (Plantago lanceolata L.) has emerged as a valuable agronomic species within grazing systems in New Zealand. The release of two cultivars in New Zealand in the mid-1990s led to on-farm use and research. Subsequent identification of the potential of plantain for reducing nitrogen losses from intensive grazing systems led to an expansion of research and extension over the last decade. This review summarises key aspects of the agronomic use of modern forage plantain from mainly New Zealand-based research, including environmental tolerance, forage productivity, feed quality, cultivar development, weed and pest management, grazing management and measurement of herbage mass. The agronomic advantages of including modern plantain cultivars in pastures include seasonal growth complementarity with grasses and clovers, greater summer-drought resilience and improved forage quality. On-farm use of plantain in New Zealand has grown to about 20% of new pastures over three decades, a modest level which can be attributed to unmet farmer expectations of plantain persistence as a substantive contributor to perennial grass-based swards and the limitations for controlling dicot weeds. These are key areas of future research priority, along with the potential for complementarity with forage grasses other than perennial ryegrass.
{"title":"Narrow-leaved plantain (Plantago lanceolata L.): A review of research on forage management within temperate grazing systems","authors":"Michael B. Dodd, Ina B. Pinxterhuis, H. Glenn Judson","doi":"10.1002/glr2.12107","DOIUrl":"https://doi.org/10.1002/glr2.12107","url":null,"abstract":"<p>Forage plantain (<i>Plantago lanceolata</i> L.) has emerged as a valuable agronomic species within grazing systems in New Zealand. The release of two cultivars in New Zealand in the mid-1990s led to on-farm use and research. Subsequent identification of the potential of plantain for reducing nitrogen losses from intensive grazing systems led to an expansion of research and extension over the last decade. This review summarises key aspects of the agronomic use of modern forage plantain from mainly New Zealand-based research, including environmental tolerance, forage productivity, feed quality, cultivar development, weed and pest management, grazing management and measurement of herbage mass. The agronomic advantages of including modern plantain cultivars in pastures include seasonal growth complementarity with grasses and clovers, greater summer-drought resilience and improved forage quality. On-farm use of plantain in New Zealand has grown to about 20% of new pastures over three decades, a modest level which can be attributed to unmet farmer expectations of plantain persistence as a substantive contributor to perennial grass-based swards and the limitations for controlling dicot weeds. These are key areas of future research priority, along with the potential for complementarity with forage grasses other than perennial ryegrass.</p>","PeriodicalId":100593,"journal":{"name":"Grassland Research","volume":"4 1","pages":"41-56"},"PeriodicalIF":0.0,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/glr2.12107","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143749660","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}
Feed is the most costly input for US ruminant livestock production systems, and increasing the utilization efficiency of irrigated forage systems can improve system profitability. This study assessed the production, utilization, and quality of 22 intensively managed perennial grasses and legumes.
Methods
Forages were cultivated as monocultures under irrigation and subjected to mob stocking or similarly frequent and intense mowing for 2 years at 6-week intervals between May and September. Twenty-two grasses and legumes were randomly assigned to adjacent 1.5-m-wide × 9-m-long split subplots within each whole plot of eight replications, and the eight replications were grouped into four pairs, with the two replications per pair randomly assigned to defoliation either by grazing or mowing.
Results
Seven mostly warm-season grasses did not persist following the first defoliation, and accumulation for three legume species could be evaluated only twice in Year 1. For the 12 remaining forage species defoliated four times in both years, defoliation management did not affect dry matter accumulation or removal, but utilization was 10% greater under grazing than mowing (p = 0.0031).
Conclusions
Under 6-week-long rest periods, numerous irrigated cool-season grasses and temperate legumes were tolerant of repeated mob grazing.
{"title":"Production, utilization, and quality of irrigated grasses and legumes in the Mountain West USA under mob stocking or mowing at the same defoliation frequency and intensity","authors":"Jennifer W. MacAdam, Brody Maughan, Xin Dai","doi":"10.1002/glr2.12106","DOIUrl":"https://doi.org/10.1002/glr2.12106","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Feed is the most costly input for US ruminant livestock production systems, and increasing the utilization efficiency of irrigated forage systems can improve system profitability. This study assessed the production, utilization, and quality of 22 intensively managed perennial grasses and legumes.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Forages were cultivated as monocultures under irrigation and subjected to mob stocking or similarly frequent and intense mowing for 2 years at 6-week intervals between May and September. Twenty-two grasses and legumes were randomly assigned to adjacent 1.5-m-wide × 9-m-long split subplots within each whole plot of eight replications, and the eight replications were grouped into four pairs, with the two replications per pair randomly assigned to defoliation either by grazing or mowing.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Seven mostly warm-season grasses did not persist following the first defoliation, and accumulation for three legume species could be evaluated only twice in Year 1. For the 12 remaining forage species defoliated four times in both years, defoliation management did not affect dry matter accumulation or removal, but utilization was 10% greater under grazing than mowing (<i>p</i> = 0.0031).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Under 6-week-long rest periods, numerous irrigated cool-season grasses and temperate legumes were tolerant of repeated mob grazing.</p>\u0000 </section>\u0000 </div>","PeriodicalId":100593,"journal":{"name":"Grassland Research","volume":"4 1","pages":"31-40"},"PeriodicalIF":0.0,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/glr2.12106","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143749810","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}
Agnieszka Konkolewska, Michael Dineen, Rachel Keirse, Patrick Conaghan, Dan Milbourne, Susanne Barth, Aonghus Lawlor, Stephen Byrne
Background
Despite its importance to animal production potential, genetic gain for forage nutritive value has been limited in perennial ryegrass (Lolium perenne L.) breeding. The objective of this study was to phenotype a training population and develop prediction models to assess the potential of predicting organic matter digestibility (OMD) and neutral detergent fiber (NDF) with genotyping-by-sequencing data.
Methods
Near infra-red reflectance spectroscopy calibrations for OMD and NDF were developed and used to phenotype a spaced plant training population of n = 1606, with matching genotype-by-sequencing data, for developing genomic selection models. families derived from the training population were also evaluated for OMD and NDF in sward plots and used to empirically validate prediction models.
Results
Sufficient genotypic variation exists in breeding populations to improve forage nutritive value, and spectral bands contributing to calibrations were identified. OMD and NDF can be predicted from genomic data with moderate accuracy (predictive ability in the range of 0.51–0.59 and 0.33–0.57, respectively) and models developed on individual plants outperform those developed from family means. Encouragingly, genomic prediction models developed on parental plants can predict OMD in subsequent generations grown as competitive swards.
Conclusions
These findings suggest that genetic improvement in forage nutritive value can be accelerated through the application of genomic prediction models.
{"title":"Genomic prediction of forage nutritive value in perennial ryegrass","authors":"Agnieszka Konkolewska, Michael Dineen, Rachel Keirse, Patrick Conaghan, Dan Milbourne, Susanne Barth, Aonghus Lawlor, Stephen Byrne","doi":"10.1002/glr2.12104","DOIUrl":"https://doi.org/10.1002/glr2.12104","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Despite its importance to animal production potential, genetic gain for forage nutritive value has been limited in perennial ryegrass (<i>Lolium perenne</i> L.) breeding. The objective of this study was to phenotype a training population and develop prediction models to assess the potential of predicting organic matter digestibility (OMD) and neutral detergent fiber (NDF) with genotyping-by-sequencing data.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Near infra-red reflectance spectroscopy calibrations for OMD and NDF were developed and used to phenotype a spaced plant training population of <i>n</i> = 1606, with matching genotype-by-sequencing data, for developing genomic selection models. <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msub>\u0000 <mi>F</mi>\u0000 \u0000 <mn>2</mn>\u0000 </msub>\u0000 </mrow>\u0000 </semantics></math> families derived from the training population were also evaluated for OMD and NDF in sward plots and used to empirically validate prediction models.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Sufficient genotypic variation exists in breeding populations to improve forage nutritive value, and spectral bands contributing to calibrations were identified. OMD and NDF can be predicted from genomic data with moderate accuracy (predictive ability in the range of 0.51–0.59 and 0.33–0.57, respectively) and models developed on individual plants outperform those developed from family means. Encouragingly, genomic prediction models developed on parental plants can predict OMD in subsequent generations grown as competitive swards.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>These findings suggest that genetic improvement in forage nutritive value can be accelerated through the application of genomic prediction models.</p>\u0000 </section>\u0000 </div>","PeriodicalId":100593,"journal":{"name":"Grassland Research","volume":"3 4","pages":"331-346"},"PeriodicalIF":0.0,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/glr2.12104","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143248740","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}
The regional species pool and local community assembly processes shape the biogeographic patterns of soil bacterial community diversity. However, how community assembly mechanisms regulate biogeographic patterns in rare and abundant bacterial communities remains unclear.
Methods
Soil samples of 16 grassland habitats across the Inner Mongolian Plateau and Qinghai-Tibet Plateau (QTP) transects were collected to investigate the variation of β-diversity in rare taxa (RT) and abundant taxa (AT). High-throughput sequencing analysis of 16S rRNA gene amplicons was implemented on an Illumina MiSeq platform.
Results
Significant distance-decay relationships of β-diversity in RT and AT were observed at transect and habitat scales, and the turnover rate increased from desert to meadow steppe in both taxa. For variations of β-diversity along environmental gradient, the regional species pool had a limited effect on both taxa except RT in QTP. Deterministic processes, including homogeneous selection (85.1%–97.3%) and heterogenous selection (48.1%–64.2%), dominated the assembly of RT at both the transect and habitat scales. In contrast, the assembly of AT exhibited habitat specificity and was dominated by homogeneous selection (47.2%–80.6%), heterogenous selection (42.1%–54.2%), and dispersal limitation (41.8%) in different transects and habitats. Moreover, the local assembly processes of the AT community were more stochastic than those of the RT community. Mean annual precipitation (MAP) was the dominant driver of community assembly at the transect scale, with extreme MAP (<200 or >400 mm) resulting in more deterministic processes and a moderate level of MAP (200–400 mm) leading to more stochastic processes. However, the effects of geographical distance and soil properties on different grassland habitats cannot be ignored.
Conclusions
Although both bacterial taxa exhibited significant distance-decay patterns, different assembly mechanisms shaped the β-diversity of AT and RT communities in grassland soils. Our results suggested that MAP can mediate community assembly of soil bacteria on a large scale.
{"title":"Similar biogeographic patterns of abundant and rare bacterial communities are driven by distinct assembly mechanisms in grassland soils","authors":"Sihao Zhu, Bai Yue, Kun Liu, Ning Zhao","doi":"10.1002/glr2.12108","DOIUrl":"https://doi.org/10.1002/glr2.12108","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The regional species pool and local community assembly processes shape the biogeographic patterns of soil bacterial community diversity. However, how community assembly mechanisms regulate biogeographic patterns in rare and abundant bacterial communities remains unclear.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Soil samples of 16 grassland habitats across the Inner Mongolian Plateau and Qinghai-Tibet Plateau (QTP) transects were collected to investigate the variation of β-diversity in rare taxa (RT) and abundant taxa (AT). High-throughput sequencing analysis of 16S rRNA gene amplicons was implemented on an Illumina MiSeq platform.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Significant distance-decay relationships of β-diversity in RT and AT were observed at transect and habitat scales, and the turnover rate increased from desert to meadow steppe in both taxa. For variations of β-diversity along environmental gradient, the regional species pool had a limited effect on both taxa except RT in QTP. Deterministic processes, including homogeneous selection (85.1%–97.3%) and heterogenous selection (48.1%–64.2%), dominated the assembly of RT at both the transect and habitat scales. In contrast, the assembly of AT exhibited habitat specificity and was dominated by homogeneous selection (47.2%–80.6%), heterogenous selection (42.1%–54.2%), and dispersal limitation (41.8%) in different transects and habitats. Moreover, the local assembly processes of the AT community were more stochastic than those of the RT community. Mean annual precipitation (MAP) was the dominant driver of community assembly at the transect scale, with extreme MAP (<200 or >400 mm) resulting in more deterministic processes and a moderate level of MAP (200–400 mm) leading to more stochastic processes. However, the effects of geographical distance and soil properties on different grassland habitats cannot be ignored.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Although both bacterial taxa exhibited significant distance-decay patterns, different assembly mechanisms shaped the β-diversity of AT and RT communities in grassland soils. Our results suggested that MAP can mediate community assembly of soil bacteria on a large scale.</p>\u0000 </section>\u0000 </div>","PeriodicalId":100593,"journal":{"name":"Grassland Research","volume":"3 4","pages":"373-384"},"PeriodicalIF":0.0,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/glr2.12108","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143248741","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}
<p>It has been an observation of mine over the last few years that in articles dealing with animal allocation to pasture or rangeland in various countries, there are differences between authors in the units used for some common terms such as stocking rate, stocking density or grazing intensity when reporting experiment treatments and data. Some authors are using units incorrectly, in my opinion. Hence, I thought that it would be useful to write an editorial for <i>Grassland Research</i>, setting out a logical framework and units for authors' consideration when preparing manuscripts on this topic. This is neither an in-depth review nor an attempt to redefine terms and concepts, but simply a call for authors to use units correctly within the currently accepted framework and definitions.</p><p>To begin, the authoritative reference is Allen et al. (<span>2011</span>). Here, <b>stocking rate</b> is defined as “the relationship between the number of animals and the total area of the land in one or more units utilized over a specified time,” with a note, “where needed, it may be expressed as animal units or forage intake units per unit of land area over time (animal units over a described time, per total system land area).” Meanwhile, <b>stocking density</b> is defined as “the relationship between the number of animals and the specific unit of land being grazed at any one time; an instantaneous measurement of the animal-to-land area relationship” and <b>grazing pressure</b> is defined as “the relationship between animal live weight and forage mass per unit area of the specific unit of land being grazed at any one time; an instantaneous measurement of the animal-to-forage relationship.” Extrapolating from these definitions, relevant units for stocking rate would be animals (of a specified species and class) per ha, and for grazing pressure, it would be kg animal body weight per kg of forage mass. Grazing pressure and its reciprocal, forage allowance (Allen et al., <span>2011</span>; Sollenberger et al., <span>2005</span>), are unitless ratios, with both animal live weight (kg) and forage mass (kg) expressed for the same land area. Considering stocking rate, nine sheep on 2 ha for 6 months of a year with 6 months with plots ungrazed is not the same as nine sheep on 2 ha continuously throughout the year. This distinction could only be represented in the units if time were included in both the numerator and the denominator (e.g., animal. years per ha. year) in which case, time (years) would cancel out. Hence, especially where animals graze a pasture for only a part of a year or other time period, as in extreme environments such as the Qinghai-Tibet Plateau, it should be explicitly stated over what period of time the animals are allocated to the land area and how any fluctuation in animal number, body weight or land area over the reporting period is dealt with.</p><p>Accordingly, in the writer's home country, New Zealand, stocking rate has been historically
根据我过去几年的观察，在各国关于动物分配到牧场或牧场的文章中，在报告实验处理和数据时，作者之间在一些常用术语（如放养率、放养密度或放牧强度）使用的单位上存在差异。在我看来，一些作者不正确地使用了单位。因此，我认为在《草原研究》上写一篇社论，为作者在准备这一主题的稿件时提出一个逻辑框架和单位，是很有用的。这既不是深入的回顾，也不是重新定义术语和概念的尝试，而只是呼吁作者在当前公认的框架和定义内正确使用单位。首先，权威参考是Allen et al.（2011）。在这里，放养率被定义为“在指定时间内使用的一个或多个单位的动物数量与土地总面积之间的关系”，并附有注释，“如果需要，它可以表示为每单位土地面积随时间推移的动物单位或饲料摄入量单位（在所述时间内的动物单位，每总系统土地面积）。”同时，放养密度被定义为“动物数量与任何时间被放牧的特定土地单位之间的关系；对“动物与土地面积关系”和放牧压力的瞬时测量定义为“任一时刻被放牧的特定单位土地的单位面积动物活重与饲料质量的关系”；对动物与饲料关系的即时测量。”从这些定义推断，放养率的相关单位是每公顷动物（特定物种和类别），放牧压力的相关单位是每公斤饲料质量的公斤动物体重。放牧压力及其倒数，草料余量(Allen et al., 2011；Sollenberger et al., 2005)是无单位比，动物活重（kg）和饲料质量（kg）均表示为同一土地面积。考虑放养率，每年6个月在2公顷土地上饲养9只羊，其中6个月未放牧与全年连续在2公顷土地上饲养9只羊是不一样的。只有在分子和分母都包含时间的情况下，这种区别才能用单位来表示(例如，动物。每公顷年数。年)，在这种情况下，时间（年）可以消掉。因此，特别是在动物仅在一年中的一部分时间或其他时间段内放牧的情况下，如在青藏高原等极端环境中，应明确说明动物在哪个时间段被分配到陆地区域，以及如何处理报告期内动物数量、体重或土地面积的波动。因此，在作者的祖国新西兰，绵羊和牛肉养殖场的放养率历来以每公顷羊的存栏数为单位，奶牛场以每公顷牛的存栏数为单位。对于绵羊和牛肉养殖场，50多年前定义的1只羊的存栏单位为饲养一只羔羊并每年消耗550千克DM的母羊(Hoogendoorn et al., 2011；帕克,1998)。公羊、猪、鹿和牛按其预期的年饲料消耗量按比例分配羊存量单位价值。由于羔羊和小牛在春天出生，秋天出售，为了使动物数量的变化标准化，报告的放养率通常是整个冬季农场携带的动物数量。多年来，随着产羔比例的增加，一只母羊现在平均产1.3-1.5只羔羊（而不是一只羔羊），每年消耗约620公斤干DM。由于以这种方式计算动物体重，以及新西兰特别强调的系统管理，放牧压力指标是不需要的，也从未发展过，尽管它可以用于跨环境或管理实践的比较（Sollenberger et al., 2005）。在新西兰的奶牛场，一些奶牛在产犊时死亡，由于夏季饲料供应减少，土壤水分不足加剧，奶牛数量在整个挤奶季节都在下降，因此，第二年不会留在农场的奶牛通常会被逐步淘汰。计算放养率的奶牛数通常是指挤奶季节高峰期农场的奶牛数。以前，从饲料供应的角度来看，新西兰奶牛场在很大程度上是自给自足的，因此在推广圈中，放养率被用作农场绩效的比较单位。近几十年来，从农场外大量进口棕榈仁或玉米青贮饲料等饲料补充剂，各农场进口饲料的数量各不相同。 为了在农场层面得出动物与饲料关系的标准化衡量标准，出现了一种称为比较放养率的衡量标准，其定义为每吨牧草的公斤牛体重加上农场每年补充的饲料供应量（Macdonald et al., 2008）。例如，一个农场的放养率为3头牛/公顷- 1，奶牛平均体重500公斤，年牧草产量为12吨干DM，饲料为3吨/公顷- 1年- 1玉米青贮干DM，则其相对放养率为每吨饲料100公斤牛体重。比较放养率已被证明是帮助农民提高饲料转化效率的有用指标。在相对放养率过低的情况下，饲料供应过剩，饲料利用率相应较低；在相对放养率过高的情况下，饲料能量在奶牛身体维持和产奶量之间的代谢分配会向身体维持倾斜，两者都会降低饲料转化效率。在新西兰以牧场为基础的乳制品系统中，每吨饲料80公斤牛体重附近的比较放养率已被证明是最佳的，令人惊讶的是，当对沙巴州以牧场为基础的热带牛肉生产系统进行计算时，最佳比较放养率值与此相似（Gobilik, 2017）。农民、推广人员和研究人员在报告放牧研究（特别是涉及轮流放养或群众性放养的研究）方面的需求是定义如何将动物分配到放牧事件（不同于将动物分配到土地面积或饲料数量）。这是动物与土地面积的关系，但它既不是放养率，也不是瞬时测量；放牧事件可能发生在几个小时内（例如，半天）或几天内（例如，两天），因此涉及到时间维度。此外，与饲料量或放牧压力不同，放牧期间的可用饲料不被考虑。Allen等人（2011）定义的术语似乎都不完全符合这一实体，按照新西兰的用法，我们将其称为放牧强度——在放牧事件的时间过程中动物对饲料的潜在需求，单位为动物·每公顷（动物数量×放牧事件持续时间/放牧面积）。这里使用潜在的动物需求，因为轮流放养和群聚放养都利用动物之间对可用饲料（即饥饿）的竞争来抑制动物的选择性，并产生“割草机”效应。因此，每只动物的实际饲料消耗量不是由动物数量来定义的，因为在这样的放牧事件中，动物的采食量随着动物数量的增加而减少。在新西兰，如上定义的放牧强度通常与采食量一起考虑，因为采食量与放牧强度之比等于采食量（kg DM ha−1/动物·天ha−1 = kg DM动物−1天−1）。通过改变轮作长度，可以在相同的放养率下改变同一农场的放养密度和放牧强度。与较低的放牧强度（较短的轮作）相比，高放牧强度（较长的轮作）减少了动物的摄入量，新西兰农民在冬季使用高放牧强度（较短的轮作）来定量配给秋季储存的饲料。例如，在0.8公顷的小型示范农场上，饲养16只羊（20只羊公顷），每2天放牧0.10公顷，放牧强度为320只羊·天公顷，轮换16天，动物摄取量高。相比之下，每3天放牧0.05公顷，每次放牧事件的放牧强度为960只羊·天ha - 1，轮换时间为48天，动物采食量有限（Matthew et al., 2017）。在Tracy和Bauer（2019）的实验中，作为定义放牧事件的指标，放养密度和放牧强度之间的差异是显而易见的。这些作者在相同的放养率为11.5头/小时（尽管他们错误地使用了动物·月/小时/小时的放养率单位，只将时间作为分子——见下文进一步评论）的情况下，比较了群居放养、轮流放养和连续放养的牛。在本试验中，放牧和轮牧处理的放养密度分别为109头和14头ha - 1。然而，由于放牧时间不同，放牧强度（如果经过计算的话）仅相差2倍，即放牧8只动物× 1天/0.1公顷= 80动物日ha - 1，而轮牧8只动物× 4天/ 0.8公顷= 40动物日ha - 1。 最后，就放养率理论而言，如果打算从生态系统的角度（从阳光到植物再到动物的能量流）创建放牧事件中动物饲料需求的度量，那么将生态系统的动物组成部分作为千克体重来计算是不理想的，因为动物身体维持能量与（体重）0.75成正比(Nicol &；布鲁克斯,2007)。例如，如果我们以动物身体维持能量
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