Crop Science最新文献_第4页

Investigating the spatial associations between thatch and white grub populations in imidacloprid‐treated turfgrass 调查经吡虫啉处理过的草坪中茅草和白蛴螬数量之间的空间关系

IF 2.3 3区农林科学

Crop Science Pub Date : 2024-10-14 DOI: 10.1002/csc2.21382

Andrew Huling, Benjamin A. McGraw

{"title":"Investigating the spatial associations between thatch and white grub populations in imidacloprid‐treated turfgrass","authors":"Andrew Huling, Benjamin A. McGraw","doi":"10.1002/csc2.21382","DOIUrl":"https://doi.org/10.1002/csc2.21382","url":null,"abstract":"Field surveys were conducted on golf courses reporting the inability of imidacloprid to control white grubs (Coleoptera: Scarabaeidae) when applied preventively. Surveys of five sites with significant past imidacloprid use (>10 years) revealed significantly greater white grub populations in rough‐mown turf following imidacloprid treatment than that of adjacent short‐mown fairways. Additionally, spatial analysis by distance indicEs (SADIE) analyses demonstrated a positive correlation between white grub and thatch spatial patterns. To investigate the impact of thatch on imidacloprid efficacy and translocation throughout the turfgrass plant, greenhouse experiments were conducted using turf with differing thatch levels. Imidacloprid concentrations in soil and plant tissues were measured with high‐performance liquid chromatography (HPLC) and compared to values obtained through an enzyme‐linked immunosorbent assay (ELISA) kit to determine if the latter could be a cost‐effective alternative in future studies. ELISA provided reliable estimates of concentrations of imidacloprid compared to HPLC, with only minor discrepancies noted across different types of treatments and assessment timings. Despite finding higher imidacloprid levels in leaf tissues compared to roots and some differences in concentration across thatch treatments, there was no clear pattern showing that thatch thickness significantly affects imidacloprid penetration or accumulation in plant tissues or soil over time. These findings suggest that factors other than thatch thickness may contribute to the observed field failures of imidacloprid in controlling white grubs. Further research is necessary to identify these factors and optimize the use of imidacloprid in turfgrass pest management strategies.","PeriodicalId":10849,"journal":{"name":"Crop Science","volume":"17 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142431316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

FIELDimagePy: A tool to estimate zonal statistics from an image, bounded by one or multiple polygons FIELDimagePy：从一幅或多幅多边形图像中估算带状统计数据的工具

IF 2.3 3区农林科学

Crop Science Pub Date : 2024-10-13 DOI: 10.1002/csc2.21357

Sumantra Chatterjee, Seth C. Murray, Felipe Inacio Mattias, Noah Fahlgren

{"title":"FIELDimagePy: A tool to estimate zonal statistics from an image, bounded by one or multiple polygons","authors":"Sumantra Chatterjee, Seth C. Murray, Felipe Inacio Mattias, Noah Fahlgren","doi":"10.1002/csc2.21357","DOIUrl":"https://doi.org/10.1002/csc2.21357","url":null,"abstract":"Vegetation indices have become an indispensable tool in remote sensing-based agricultural research. A recent area of advancement in agricultural remote sensing research is in high-throughput phenotyping, often conducted on a plot by plot basis. FIELDimageR is a tool used extensively in high-throughput phenotyping that estimates zonal statistics of vegetation indices per plot. However, being written in R language, FIELDimageR requires high computing time. As a high-resolution image over a large area means a large number of pixels, FIELDimageR is incapable of using high-resolution orthomosaicked images without reducing image resolution by aggregating digital numbers of several pixels and treating them as one pixel. This research tool implements FIELDimageR in the Python language as FIELDimagePy. FIELDimagePy follows similar workflows as FIELDimageR and generates equivalent results for zonal statistics of vegetation indices per plot. FIELDimagePy is significantly and substantially faster than FIELDimageR. Computing time by FIELDimagePy are three to four times lower than computing times by FIELDimageR, even when using raw images with 16 times denser pixels. Moreover, FIELDimagePy is useful beyond plot by plot research in agriculture and capable of estimating zonal statistics of any raster bounded by any polygons. With slight modifications, FIELDimagePy can be useful for other disciplines of science, such as geophysics, geography, economics, medical sciences, among others. FIELDimagePy can be accessed from the GitHub repository: https://github.com/SumantraChatterjee/FIELDimagePy.","PeriodicalId":10849,"journal":{"name":"Crop Science","volume":"229 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142431271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Response of cool‐season turfgrass monocultures and two‐way mixtures to sequential acute drought periods 冷季型草坪草单一种植和双向混播对连续急性干旱期的反应

IF 2.3 3区农林科学

Crop Science Pub Date : 2024-10-09 DOI: 10.1002/csc2.21385

Florence Breuillin‐Sessoms, Dominic Petrella, Gary Deters, Jillian Turberville, Eric Watkins

{"title":"Response of cool‐season turfgrass monocultures and two‐way mixtures to sequential acute drought periods","authors":"Florence Breuillin‐Sessoms, Dominic Petrella, Gary Deters, Jillian Turberville, Eric Watkins","doi":"10.1002/csc2.21385","DOIUrl":"https://doi.org/10.1002/csc2.21385","url":null,"abstract":"Turfgrass seeds are often sold as mixtures of several species to increase the probability of positive responses toward abiotic and biotic stresses, a response to drought being one of these. Several species of turfgrass are already thought to be better suited for drought, such as hard fescue (Festuca brevipila Tracey) and tall fescue [Schedonorus arundinaceus (Schreb.) Dumort]. However, little is known about the benefit of these species in mixtures with drought‐intolerant and/or drought‐avoiding species during drought. Understanding species mixture composition during establishment, before and after drought stress periods, could help develop more resilient mixtures for this stress condition. We compared monocultures and mixtures of hard fescue, Kentucky bluegrass (Poa pratensis L.), and perennial ryegrass (Lolium perenne L.) during sequential short drought and recovery periods in controlled conditions. We observed that the composition of most mixtures remained similar during drought and recovery periods; however, perennial ryegrass was often less prevalent after drought stress. We found that hard fescue monocultures had better green leaf coverage than Kentucky bluegrass and perennial ryegrass during drought stress. However, the presence of hard fescue in mixtures was not an indicator of greater drought tolerance, and variable fluorescence to maximal fluorescence data indicated that hard fescue was just as physiologically stressed as perennial ryegrass and Kentucky bluegrass during the drought periods. These results indicate that while hard fescue seems visually drought tolerant, it is still physiologically stressed and improved drought tolerance could be achieved through focusing on physiological indicators of stress in this species rather than visual indicators.","PeriodicalId":10849,"journal":{"name":"Crop Science","volume":"6 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142397794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Elite germplasm introduction, training set composition, and genetic optimization algorithms effect on genomic selection-based breeding programs 精英种质引进、训练集组成和遗传优化算法对基于基因组选择的育种计划的影响

IF 2 3区农林科学

Crop Science Pub Date : 2024-10-09 DOI: 10.1002/csc2.21384

Roberto Fritsche-Neto, Rafael Massahiro Yassue, Allison Vieira da Silva, Melina Prado, Júlio César DoVale

{"title":"Elite germplasm introduction, training set composition, and genetic optimization algorithms effect on genomic selection-based breeding programs","authors":"Roberto Fritsche-Neto, Rafael Massahiro Yassue, Allison Vieira da Silva, Melina Prado, Júlio César DoVale","doi":"10.1002/csc2.21384","DOIUrl":"10.1002/csc2.21384","url":null,"abstract":"In genomic selection (GS), the prediction accuracy is heavily influenced by the composition of the training set (TS). Currently, two primary strategies for building TS are used: one involves accumulating historical phenotypic records from multiple years, while the other is the “test-and-shelf” approach. Additionally, studies have suggested that optimizing TS composition using genetic algorithms can improve the accuracy of prediction models. Most breeders operate in open systems, introducing new genetic variability into their populations as needed. However, the impact of elite germplasm introduction in GS models remains unclear. Therefore, we conducted a case study in self-pollinated crops using stochastic simulations to understand the effects of elite germplasm introduction, TS composition, and its optimization in long-term breeding programs. Overall, introducing external elite germplasm reduces the prediction accuracy. In this context, test and shelf seem more stable regarding accuracy in dealing with introductions despite the origin and rate, being useful in programs where the introductions come from different sources over the years. Conversely, using historical data, if the introductions come from the same source over the cycles, this negative effect is reduced as long as the cycles and this approach become the best. Thus, it may support public breeding programs in establishing networks of collaborations where the exchange of germplasm will occur at a predefined rate and flow. In either case, the use of algorithms of optimization to trim the genetic variability does not bring a substantial advantage in the medium to long term.","PeriodicalId":10849,"journal":{"name":"Crop Science","volume":"64 6","pages":"3323-3338"},"PeriodicalIF":2.0,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/csc2.21384","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142405143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Why mow?: A review of the resulting ecosystem services and disservices from mowing turfgrass 为什么要割草？草坪修剪带来的生态系统服务和非服务回顾

IF 2.3 3区农林科学

Crop Science Pub Date : 2024-10-09 DOI: 10.1002/csc2.21376

Aaron J. Patton

引用次数: 0

Maximizing genetic gains across agronomic and consumer preference traits in St. Augustinegrass breeding 在圣奥古斯丁草育种中最大限度地提高农艺性状和消费者偏好性状的遗传收益

IF 2.3 3区农林科学

Crop Science Pub Date : 2024-10-09 DOI: 10.1002/csc2.21374

Susana R. Milla‐Lewis, Beatriz Tome Gouveia, Kevin Kenworthy, Jing Zhang, Ambika Chandra, Grady L. Miller, Esdras M. Carbajal, Brian Schwartz, Paul Raymer, Marta Pudzianowska, James H. Beard, J. Bryan Unruh

{"title":"Maximizing genetic gains across agronomic and consumer preference traits in St. Augustinegrass breeding","authors":"Susana R. Milla‐Lewis, Beatriz Tome Gouveia, Kevin Kenworthy, Jing Zhang, Ambika Chandra, Grady L. Miller, Esdras M. Carbajal, Brian Schwartz, Paul Raymer, Marta Pudzianowska, James H. Beard, J. Bryan Unruh","doi":"10.1002/csc2.21374","DOIUrl":"https://doi.org/10.1002/csc2.21374","url":null,"abstract":"Combining large multi‐environment trial (MET) datasets to decide which genotypes to move forward in the breeding process can be challenging, especially when dealing with negatively correlated traits. The use of a selection index has long been identified as an effective strategy in these situations. However, the method has found limited application in turfgrass breeding. The objective of this study was to use MET data for St. Augustinegrass [Stenotaphrum secundatum (Walt.) Kuntze] breeding lines evaluated across the southern United States to compare genetic gains achieved with the additive additive genetic index (AI) versus the turf performance index (TPI) incorporating agronomic as well as consumer preference traits. The use of either selection index produced more positive genetic gains across traits than direct selection even in the presence of negative correlations. However, the higher genetic gains obtained with AI versus TPI indicate that the use of an index that weighs traits according to their importance is a better approach for selection. Moreover, under a more stringent selection intensity, none of the best lines identified with AI would have been selected with TPI emphasizing the importance of choosing selection criteria that provide a more nuanced ranking of lines. Additionally, higher heritability values and gains from selection were obtained for turfgrass quality under stress (drought and shade) than under normal conditions indicating that selection under stress environments might be more efficient. Most of the evaluated St. Augustinegrass lines outperformed the checks, further supporting the value of cross‐institutional breeding collaborations.","PeriodicalId":10849,"journal":{"name":"Crop Science","volume":"1 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142385491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A method to spatially assess multipass spray deposition patterns via UV fluorescence and weed population shifts 通过紫外线荧光和杂草数量变化对多通道喷雾沉积模式进行空间评估的方法

IF 2.3 3区农林科学

Crop Science Pub Date : 2024-10-09 DOI: 10.1002/csc2.21377

Daewon Koo, Navdeep Godara, Juan R. Romero Cubas, Shawn D. Askew

{"title":"A method to spatially assess multipass spray deposition patterns via UV fluorescence and weed population shifts","authors":"Daewon Koo, Navdeep Godara, Juan R. Romero Cubas, Shawn D. Askew","doi":"10.1002/csc2.21377","DOIUrl":"https://doi.org/10.1002/csc2.21377","url":null,"abstract":"Spray deposition patterns from agricultural sprayers are traditionally sampled discretely along a field transect accounting for 0.5% or less of the treated area. Such methods may not fully capture the dimensional variability inherent in large‐scale, multiple‐pass spray applications, especially evident from an agricultural spray drone (ASD). This study investigated the utilization of UV‐fluorescent dye and nighttime aerial imaging techniques to assess large‐scale, multipass spray deposition patterns. Accuracy of digital hue from UV‐fluorescent photography to predict deposition of proxy dye was confirmed via fluorometry assessed intensity levels of extracted UV‐fluorescent dye from 384 Petri dishes placed prior to treatment. Results showed that ASD applications, regardless of nozzle type, exhibited greater spatial variability within the target area compared to ride‐on sprayer applications, primarily due to overapplication. Additionally, the ASD generated spray drift to adjacent nontarget areas that was at least three times more than that of ride‐on and spray‐gun sprayers. Multipass deposition was further assessed via in situ smooth crabgrass infestation following treatment with quinclorac or topramezone by multipass ASD or hand‐held, four‐nozzle spray boom. Weed infestation annotated from overlaid grids with 9.3‐dm2 ground resolution inconsistently detected spatial heterogeneity between transects assessed along the center and edge of each sprayer pass. The ASD controlled smooth crabgrass 11% more than the hand‐held sprayer, albeit with an 18% increase in spray drift to nontarget areas, similar to the UV‐fluorescence study. Digitally assessed average hue of fluorescence photography appears to be a viable method to assess multidimensional and continuous spatial relationships of spray deposition.","PeriodicalId":10849,"journal":{"name":"Crop Science","volume":"13 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142385488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Accelerating genetic gain through strategic speed breeding in spring wheat 通过春小麦战略速育加快遗传增益

IF 2 3区农林科学

Crop Science Pub Date : 2024-10-08 DOI: 10.1002/csc2.21380

Lucas Alexandre Batista, Nonoy Bandillo, Andrew Friskop, Andrew Green

{"title":"Accelerating genetic gain through strategic speed breeding in spring wheat","authors":"Lucas Alexandre Batista, Nonoy Bandillo, Andrew Friskop, Andrew Green","doi":"10.1002/csc2.21380","DOIUrl":"10.1002/csc2.21380","url":null,"abstract":"Spring wheat (Triticum aestivum L.) is a popular bread wheat with high milling and baking requirements. Vernalization is not required for spring wheat, which allows for fast growth under manipulated conditions. This experiment's objective was rapid development of inbred lines of hard red spring wheat throughout the off-season and preserve enough genetic variability to perform selection. A total of 1575 F2 heads from three distinct populations were randomly harvested in the field-season 2021. To break seed dormancy, seeds were held for 2 days at 0°C. Three breeding cycles were performed through single seed descent under manipulated growth condition during the off-season 2021–2022. We were able to harvest plant materials as quickly as 54 days after planting in comparison to 110 days average field season. We lost a total of 36.4% during the three off-season fast advancement generations and 711 genotypes reached the F5:6 generation with enough seed to perform a partially replicated small plot yield trial at two locations during the 2022 field-season. Response traits collected included grain yield, grain protein, plant height, days to heading, and bacterial leaf streak (Xanthomonas transluens) disease severity. Heritability of collected traits varied between 0.61 and 0.92. Although we had considerable loss during the speed breeding, we were able to identify superior genotypes compared to the parents.","PeriodicalId":10849,"journal":{"name":"Crop Science","volume":"64 6","pages":"3311-3322"},"PeriodicalIF":2.0,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142385490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Spring nitrogen and plant growth regulator effects on seed yield of orchardgrass 春季氮和植物生长调节剂对果园草种子产量的影响

IF 2 3区农林科学

Crop Science Pub Date : 2024-10-08 DOI: 10.1002/csc2.21349

Nicole P. Anderson, Mohammed M. Morad, Thomas G. Chastain

{"title":"Spring nitrogen and plant growth regulator effects on seed yield of orchardgrass","authors":"Nicole P. Anderson, Mohammed M. Morad, Thomas G. Chastain","doi":"10.1002/csc2.21349","DOIUrl":"10.1002/csc2.21349","url":null,"abstract":"Orchardgrass (Dactylis glomerata L.) is an important forage seed crop, but unlike other cool-season grasses, seed yields have not increased over time. Seed yield increases in orchardgrass may be possible with plant growth regulators (PGRs) such as trinexapac-ethyl (TE) and chlormequat chloride (CCC). Field trials were conducted at Hyslop Experimental Farm near Corvallis, Oregon, over three crop years (2017–2019) to examine the effects of spring nitrogen (N) and PGRs on seed production characteristics in orchardgrass. Spring N treatments included 0, 112, 157, and 202 kg N ha−1 and PGR applications were timed using the BBCH (Biologische Bundesanstalt, Bundessortenamt und Chemische Industrie) scale. Four PGR treatments included an untreated control, 210 g TE ha−1 at BBCH 32, 210 g TE ha−1 at BBCH 51, and 105 g TE ha−1 + 1500 g CCC ha−1 at BBCH 32. An interaction of spring N and PGR increased seed yields in 2 years, while spring N and PGR increased seed yield independently in the other year. The combination of TE and CCC PGRs did not increase seed yield over TE alone. Seed yield increases from spring N were due to an increase in seed number m−2, while increases in seed yield attributable to PGRs were the result of increased seed number m−2 and harvest index. This study suggests that the combination of 112 kg ha−1 spring N and 210 g ha−1 TE PGR is the best practice to maximize seed yield in orchardgrass.","PeriodicalId":10849,"journal":{"name":"Crop Science","volume":"64 6","pages":"3533-3540"},"PeriodicalIF":2.0,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/csc2.21349","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142385494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Non-destructive characterization of pearl millet [Pennisetum glaucum (L.) R. Br.] composition using single-kernel NIR spectroscopy 利用单核近红外光谱对珍珠粟[Pennisetum glaucum (L.) R. Br.]成分进行非破坏性鉴定

IF 2 3区农林科学

Crop Science Pub Date : 2024-10-08 DOI: 10.1002/csc2.21375

Princess Tiffany D. Mendoza, Paul R. Armstrong, Kaliramesh Siliveru, Manoj Kumar Pulivarthi, Ajay Prasanth Ramalingam, P. V. Vara Prasad, Ramasamy Perumal

{"title":"Non-destructive characterization of pearl millet [Pennisetum glaucum (L.) R. Br.] composition using single-kernel NIR spectroscopy","authors":"Princess Tiffany D. Mendoza, Paul R. Armstrong, Kaliramesh Siliveru, Manoj Kumar Pulivarthi, Ajay Prasanth Ramalingam, P. V. Vara Prasad, Ramasamy Perumal","doi":"10.1002/csc2.21375","DOIUrl":"10.1002/csc2.21375","url":null,"abstract":"As a gluten-free cereal with high nutritional properties, pearl millet [Pennisetum glaucum (L.) R. Br.] has been increasingly regarded as an alternative dryland resilient food crop with enriched grain nutritional value. This paper explores the potential of single-kernel near-infrared (SKNIR) spectroscopy combined with multivariate analysis for rapid and non-destructive evaluation of protein, moisture, fat, fiber, and ash contents of pearl millet grains. Samples harvested from two consecutive years (2021 and 2022) were evaluated under dryland and irrigated conditions in Kansas State University, Agricultural Research Center, Hays (ARCH), KS and were analyzed using SKNIR and conventional laboratory methods. Model calibrations were developed using partial least squares regression. Results showed satisfactory performance of models with standard errors cross-validation of 1.04%, 0.17%, 0.39%, 0.21%, and 0.16%, respectively, for protein, moisture, fat, fiber, and ash content. The findings suggest that SKNIR can be a potential tool for high-throughput pearl millet composition screening efficiently, which will assist breeders and grain processors to optimize grain properties and enhance the grain quality and products.","PeriodicalId":10849,"journal":{"name":"Crop Science","volume":"64 6","pages":"3043-3051"},"PeriodicalIF":2.0,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142385489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0