Agronomy Journal最新文献_第4页

Potato yield projections under climate change in Canada

IF 2 3区农林科学

Agronomy Journal Pub Date : 2025-02-06 DOI: 10.1002/agj2.70017

Guillaume Jégo, Marianne Crépeau, Qi Jing, Brian Grant, Ward Smith, Morteza Mesbah, Budong Qian

{"title":"Potato yield projections under climate change in Canada","authors":"Guillaume Jégo, Marianne Crépeau, Qi Jing, Brian Grant, Ward Smith, Morteza Mesbah, Budong Qian","doi":"10.1002/agj2.70017","DOIUrl":"https://doi.org/10.1002/agj2.70017","url":null,"abstract":"Potato (Solanum tuberosum L.) is an important staple crop in Canada. Past studies have forecasted future yield decreases under climate change, which could have major consequences for the economy of some regions. However, limitations in those studies suggest that further investigations are needed. In this study, we simulated the effect of 15 climate change scenarios (classified from low to moderate and high) on potato potential (no N and water stresses) and rainfed (no N stress) yields at 59 locations across Canada representing current and future potential production regions using three crop models (Decision Support System for Agrotechnology Transfer [DSSAT], DeNitrification and DeComposition [DNDC], and Simulateur mulTI-disciplinaire pour les Cultures Standard [STICS]). Simulation trends were generally consistent across all three crop models and suggested (1) an increase in potential and rainfed yields in the future (up to 4.4 t ha−1 dry matter in 2051–2080 compared with 1991–2020) in the northern regions where production is currently limited, if not impossible, due to a too short growing season; (2) a slight-to-moderate increase in potential and rainfed yields in the near future (2021–2050) for the remaining regions with greater increases for drier regions (0.7–3.1 t ha−1) than in wetter regions (0.5–1.4 t ha−1); and (3) stable or lower yields (up to −2.7 t ha−1) in the distant future (2051–2080), for most regions except the northern ones, due to excessively high temperatures, especially in the moderate and high-climate change scenarios. This study gave the first extensive projections of future potato yield in Canada, including northern locations where production may become possible.","PeriodicalId":7522,"journal":{"name":"Agronomy Journal","volume":"117 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/agj2.70017","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143362406","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

Peanut responds to K fertilization but not to K timing on low-K sandy soils

IF 2 3区农林科学

Agronomy Journal Pub Date : 2025-02-06 DOI: 10.1002/agj2.70022

Angel S. Zubieta, Aadil A. Rahman, George Hochmuth, Anthony Drew, Emma G. Matcham

{"title":"Peanut responds to K fertilization but not to K timing on low-K sandy soils","authors":"Angel S. Zubieta, Aadil A. Rahman, George Hochmuth, Anthony Drew, Emma G. Matcham","doi":"10.1002/agj2.70022","DOIUrl":"https://doi.org/10.1002/agj2.70022","url":null,"abstract":"Potassium (K) is necessary for plant growth, and insufficient K reduces peanut [Arachis hypogaea (L.)] yield and grade. Peanut production in Florida is on sandy soils with low cation exchange capacity. Minimizing K loss to leaching may be affected by the timing of fertilizer-K application. We evaluated the impact of K fertilization on pod yield and grade of peanut in sites with different soil test K (STK) levels. Treatments comprised a two-way factorial with five fertilizer rates (0, 46, 93, 140, and 186 kg ha−1 K) and four application timings (planting; planting plus early bloom; planting, early bloom, plus 60 days; early bloom plus 60 days). The study occurred at sites Hilltop, Citra, and Sesame with Mehlich-3 STK levels 2, 26, and 40 mg kg−1, respectively, at the University of Florida Plant Sciences Research and Education Unit in Citra, FL. In the low-STK sites (Hilltop, Citra), the relative yield increased quadratically until fertilizer rates reached 160 and 82 kg ha−1 K, respectively, after which there was no further increase in peanut pod yield. At Sesame, pod yield was not affected by K rate. Splitting K applications did not improve pod yield at any site in these seasons, which had few leaching rains. Proportion of sound mature kernels (TSMK) was affected only by site, averaging ≥75%. Fertilizing peanuts with 82–160 kg ha−1 K maximized pod yield in soils with Mehlich-3 STK ≤26 mg kg−1, and different responses to K fertilizer rate observed at fields with different STK levels within the low STK index category suggests justification for splitting this category. A single K application is sufficient in sites with low incidence of leaching rains.","PeriodicalId":7522,"journal":{"name":"Agronomy Journal","volume":"117 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143362407","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

Auxin injury on cotton, II: Effects on yield components

IF 2 3区农林科学

Agronomy Journal Pub Date : 2025-01-24 DOI: 10.1002/agj2.70014

Savana Denton, Tyson Raper, Darrin Dodds, Chris Main, Thomas Mueller

{"title":"Auxin injury on cotton, II: Effects on yield components","authors":"Savana Denton, Tyson Raper, Darrin Dodds, Chris Main, Thomas Mueller","doi":"10.1002/agj2.70014","DOIUrl":"https://doi.org/10.1002/agj2.70014","url":null,"abstract":"Auxin-tolerant cotton (Gossypium hirsutum, L.) cultivars are the latest tools producers use to combat herbicide-resistant weed species during the growing season. The widespread implementation of auxin-tolerant crops has led to an increase in in-season applications of auxins. Auxin drift has subsequently become a more prominent issue in the agricultural industry and causes producers to shift management tactics. Yield partitioning research based on auxin application timing has been conducted, but more information is needed concerning application rate and the interaction between application rate and timing. Experiments were conducted from 2019 to 2021 in Grand Junction, TN, to determine the effects of synthetic auxin exposure on boll positioning, development, and production. Applications of 2,4-dichlorophenoxyacetic acid (2,4-D) or dicamba were made to cotton cultivars of the opposite technology at either matchhead square or 2 weeks after first bloom (FB + 2WK). Nontreated experimental plots were also included. More severe impacts on overall lint yield, yield partitioning, and yield components were observed following exposure to 2,4-D than dicamba. Application rate and timing also impacted yield components and partitioning. Exposure to 2,4-D during vegetative growth caused increased partitioning to vegetative and aborted fruiting positions but decreased partitioning to position 1, zone 2 (nodes 9 through 12), and zone 3 (nodes 13 and above) as application rate increased. Exposure to these rates at FB + 2WK did not impact yield partitioning. Environmental conditions following applications of 2,4-D or dicamba play an important role in the recovery and growth of cotton and subsequent yield penalties.","PeriodicalId":7522,"journal":{"name":"Agronomy Journal","volume":"117 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/agj2.70014","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143118732","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

Soil test correlation of Olsen-P for corn and soybean in a subtropical humid region

IF 2 3区农林科学

Agronomy Journal Pub Date : 2025-01-20 DOI: 10.1002/agj2.70009

N. I. Reussi Calvo, D. Cortez, C. Crespo, N. Wyngaard, J. Terrazas, C. Paz, R. Trujillo, A. Correndo, F. O. Garcia

{"title":"Soil test correlation of Olsen-P for corn and soybean in a subtropical humid region","authors":"N. I. Reussi Calvo, D. Cortez, C. Crespo, N. Wyngaard, J. Terrazas, C. Paz, R. Trujillo, A. Correndo, F. O. Garcia","doi":"10.1002/agj2.70009","DOIUrl":"https://doi.org/10.1002/agj2.70009","url":null,"abstract":"Accurate phosphorus (P) fertilizer recommendations for soybean [Glycine max (L.) Merr.] and corn (Zea mays L.) are crucial for maximizing productivity and economic return while minimizing the environmental impact of fertilizer use. Currently, there are no calibrations for diagnosing P deficiencies in croplands of Bolivia. This study aimed to define and compare the P critical soil test value (CSTV) for corn and soybean using the Olsen method. Twenty fertilization field trials were conducted for corn and 75 for soybean in the Santa Cruz de la Sierra region, including treatments with and without P fertilization. Soil pre-planting (0–20 cm) organic matter, Olsen P, pH, as well as yield were determined. Relative yield (RY) was estimated as the ratio of grain yield between the control and P-fertilized treatments. The CSTV was calculated using the arcsine-logarithm method, with data resampling through bootstrapping. The average yield response to added P was 259 kg ha−1 (+11.0%) for soybean and 545 kg ha−1 (+13.7%) for corn. For soybean, CSTVs were determined as 6.1 and 11.0 mg kg−1 (r = 0.34, p = 0.002) for 90% and 95% of RY, respectively. For corn, the CSTVs were 8.1 and 13.9 mg kg−1 (r = 0.34, p = 0.14) for 90% and 95% of RY, respectively. The confidence intervals suggest no differences between crops. The Olsen-P is a promising tool for soil fertility recommendations in Bolivia. Yet, the modest goodness of fit obtained suggests the need for further research refining the performance of soil test P diagnosis in the region.","PeriodicalId":7522,"journal":{"name":"Agronomy Journal","volume":"117 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/agj2.70009","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143117304","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

Interseeding cover crop into an irrigated sandy loam for 6 years: Soil, crop, and economic response

IF 2 3区农林科学

Agronomy Journal Pub Date : 2025-01-19 DOI: 10.1002/agj2.70013

Humberto Blanco-Canqui, Sabrina J. Ruis, Mitiku Mamo, Charles A. Shapiro, Christopher Proctor, Jay Parsons, Laura Thompson

{"title":"Interseeding cover crop into an irrigated sandy loam for 6 years: Soil, crop, and economic response","authors":"Humberto Blanco-Canqui, Sabrina J. Ruis, Mitiku Mamo, Charles A. Shapiro, Christopher Proctor, Jay Parsons, Laura Thompson","doi":"10.1002/agj2.70013","DOIUrl":"https://doi.org/10.1002/agj2.70013","url":null,"abstract":"Interseeding cover crops (CCs) may be a potential strategy to manage sandy soils, which are highly prone to degradation. However, how this practice affects CC biomass production and other ecosystem services in sandy soils over the traditional CC planting system (post-harvest drilling) is still unclear. We studied how broadcast interseeded (32–67 days before crop harvest) winter rye (Secale cereale L.) CC affected CC biomass production, nitrate leaching potential, soil properties, crop yields, and farm income compared with post-harvest drilled CC in an on-farm irrigated no-till corn (Zea mays L.)–soybean (Glycine max L.) experiment in a sandy loam in the western US Corn Belt for 6 years. Across the 6 years, interseeded CC produced 0.57 Mg ha−1 of biomass, while post-harvest drilled CC produced 0.37 Mg ha−1. Nitrate leaching is a concern in sandy soils, but interseeded CC had mixed effects on soil nitrate concentration. Interseeded CC did not affect soil properties (particulate organic matter and organic C concentrations, and wet aggregate stability) and crop yields. Further, interseeded CC did not reduce farm income more than post-harvest drilled CC. The limited effect of interseeded CCs is likely due to the relatively small increase in CC biomass production over the traditional CC planting system. Additional strategies including irrigation, drill interseeding, and planting green may boost interseeded CC biomass production and thus soil services in sandy soils. After 6 years, interseeded CC slightly boosted CC biomass production but minimally affected soils and crops, and both interseeded and post-harvest-drilled CCs reduced net income.","PeriodicalId":7522,"journal":{"name":"Agronomy Journal","volume":"117 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/agj2.70013","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143116707","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

Performance and legacy effect of crop rotations on eastern Canadian dairy farms

IF 2 3区农林科学

Agronomy Journal Pub Date : 2025-01-19 DOI: 10.1002/agj2.70007

Mohamed Taher Khechine, Marie-Noëlle Thivierge, Martin H. Chantigny, Gilles Bélanger, Fadi Hassanat, Édith Charbonneau, Annie Brégard, Anne Vanasse, Isabelle Royer, Guillaume Jégo, Émilie Maillard, Gaëtan F. Tremblay, Denis A. Angers, Caroline Halde

{"title":"Performance and legacy effect of crop rotations on eastern Canadian dairy farms","authors":"Mohamed Taher Khechine, Marie-Noëlle Thivierge, Martin H. Chantigny, Gilles Bélanger, Fadi Hassanat, Édith Charbonneau, Annie Brégard, Anne Vanasse, Isabelle Royer, Guillaume Jégo, Émilie Maillard, Gaëtan F. Tremblay, Denis A. Angers, Caroline Halde","doi":"10.1002/agj2.70007","DOIUrl":"https://doi.org/10.1002/agj2.70007","url":null,"abstract":"Crop rotations on dairy farms in eastern Canada nowadays include fewer perennial crops and more nitrogen-demanding annual crops. This study compared, over a 7-year rotation cycle, the agronomic performance and the legacy effect of six crop rotations that varied in crop types (perennial or annual) and nutrient sources (mineral or organic). Crop yield and nutritive value were determined on a yearly basis and cumulated over the rotation cycle. The legacy effect was assessed by growing forage corn (Zea mays L.) in year 6 and soybean [Glycine max (L.) Merr.] in year 7 in all rotations. The legacy effect of perennial forage crops manifested with a 78% lower weed biomass at harvest of forage corn in year 6 and a 14% greater soybean yield in year 7. A greater soil-derived corn nitrogen uptake in year 6 after repeated slurry applications indicated a modest legacy effect of organic fertilization on soil N supply capacity. The presence of perennial forage crops or the use of organic fertilization did not affect cumulative dry matter or crude protein production over the 7-year rotation cycle. The addition of alfalfa (Medicago sativa L.) in mixture with perennial grasses improved forage yield (+26%) and nutritive value (greater digestible energy and crude protein concentration) in post-seeding years. In perennial-based rotations, adding alfalfa to grasses resulted in greater dry matter (+22%) and crude protein (+46%) productions over the 7-year cycle despite a fourfold reduction in N fertilizer input, attesting to the high N use efficiency of perennial legume-based cropping systems.","PeriodicalId":7522,"journal":{"name":"Agronomy Journal","volume":"117 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/agj2.70007","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143116708","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

A comparison of physics-based, data-driven, and hybrid modeling approaches for rice phenology prediction

IF 2 3区农林科学

Agronomy Journal Pub Date : 2025-01-16 DOI: 10.1002/agj2.70010

Jin Yu, Yifan Zhao, Guoqing Lei, Wenzhi Zeng

{"title":"A comparison of physics-based, data-driven, and hybrid modeling approaches for rice phenology prediction","authors":"Jin Yu, Yifan Zhao, Guoqing Lei, Wenzhi Zeng","doi":"10.1002/agj2.70010","DOIUrl":"https://doi.org/10.1002/agj2.70010","url":null,"abstract":"Accurate prediction of paddy rice (Oryza sativa L.) phenology is necessary for informing field management and improving yield. There exist different ways, including physics-based, data-driven, and hybrid approaches, to make rice phenology prediction. However, few studies have investigated the performance of the above three modeling approaches. This study compared the performance of a physics-based model (ORYZA), a data-driven model (using the distributed random forest [DRF] technique), and a hybrid model (an integration of the ORYZA model and DRF-based rice development rate parameter estimates) for rice panicle initiation and flowering date prediction. The feature importance analysis method was introduced to quantify the relative importance of input variables for rice phenology prediction. The results showed the following: (1) Rice genotypes and cultivation patterns resulted in poor performance of the ORYZA model for phenology prediction, whose root mean square error (RMSE) ranged from 6.01 to 8.12 days, and the coefficient of determination (R2) ranged from 0.06 to 0.24. (2) The hybrid model, whose RMSE ranged from 3.11 to 3.66 days, improved the ORYZA model but still underperformed the data-driven model, whose RMSE ranged from 2.44 to 2.57 days. The worse performance might be attributed to the poor prediction accuracy of the model parameter, development rate in the juvenile phase, where the mean absolute percentage error was 0.286. (3) Satellite-based vegetation indices, leaf area index, and evapotranspiration played an important role in determining the predictive capacity of the DRF technique for ORYZA model parameters and rice phenology. Overall, we suggested using data-driven models for accurate rice phenology prediction.","PeriodicalId":7522,"journal":{"name":"Agronomy Journal","volume":"117 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143115615","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

High-throughput phenotyping and machine learning techniques in soybean breeding: Exploring the potential of aerial imaging and vegetation indices 大豆育种中的高通量表型和机器学习技术：探索航空成像和植被指数的潜力

IF 2 3区农林科学

Agronomy Journal Pub Date : 2025-01-16 DOI: 10.1002/agj2.70012

Melissa Cristina de Carvalho Miranda, Alexandre Hild Aono, Talieisse Gomes Fagundes, Giovanni Michelan Arduini, José Baldin Pinheiro

{"title":"High-throughput phenotyping and machine learning techniques in soybean breeding: Exploring the potential of aerial imaging and vegetation indices","authors":"Melissa Cristina de Carvalho Miranda, Alexandre Hild Aono, Talieisse Gomes Fagundes, Giovanni Michelan Arduini, José Baldin Pinheiro","doi":"10.1002/agj2.70012","DOIUrl":"https://doi.org/10.1002/agj2.70012","url":null,"abstract":"Soybean (Glycine max (L.) Merr.) breeding programs face challenges in evaluating large progeny populations, which is labor- and resource-intensive. This study addresses these challenges using high-throughput phenotyping and machine learning (ML) models to predict phenotypic traits in soybeans. We developed and validated ML models using vegetation indices and canopy images from aerial imagery. A total of 275 soybean genotypes were characterized across two environments and management practices. A total of 11 classical traits were measured, and five vegetation indices were calculated from aerial images at different growth stages. ML algorithms, including support vector machine for regression, random forest (RF), multilayer perceptron (MLP), and adaptive boosting, were employed. Additionally, convolutional neural networks with transfer learning were used to extract features from the images. Significant correlations were found between agronomic traits, vegetation indices, and canopy characteristics. The high heritability of the red–green–blue vegetation index and green leaf index (mean broad-sense heritability of 0.56) compared to other RGB-based indices indicates their potential usefulness in genetic evaluations. Advanced ML techniques, particularly transfer learning with ResNet 50, enhanced the prediction of phenotypic traits such as days to the R7 growth stage (DR7) and plant height at maturation (PHM). The integration of ResNet 50 with RF achieved a prediction accuracy of 0.64 for DR7, while ResNet 50 with MLP reached an accuracy of 0.68 for PHM. These findings highlight the potential of these techniques to improve decision-making in soybean breeding. Lastly, principal component analysis identified genotypes with desirable trait combinations, advancing soybean development.","PeriodicalId":7522,"journal":{"name":"Agronomy Journal","volume":"117 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/agj2.70012","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143115616","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

Evaluating the performance of drought indices for assessing agricultural droughts in Argentina

IF 2 3区农林科学

Agronomy Journal Pub Date : 2025-01-10 DOI: 10.1002/agj2.70008

G. Sosa, M. E. Fernández-Long, S. M Vicente-Serrano

{"title":"Evaluating the performance of drought indices for assessing agricultural droughts in Argentina","authors":"G. Sosa, M. E. Fernández-Long, S. M Vicente-Serrano","doi":"10.1002/agj2.70008","DOIUrl":"https://doi.org/10.1002/agj2.70008","url":null,"abstract":"This article presents an analysis of the response of the annual yield of rainfed maize crops in the Argentine Pampas Region to five drought indices (standardized precipitation index [SPI], standardized soil moisture index [SSMI], standardized evapotranspiration deficit index [SEDI], standardized precipitation-evapotranspiration index [SPEI], and standardized precipitation actual evapotranspiration index [SPET]) at different time scales (from 1 to 12 months). The idea of this work was to find the drought indices that best correspond to the interannual variability of maize yield and to use them in monitoring agricultural droughts. For this purpose, we correlated maize yields with different indices across all their time-scales. We selected the indices with the best overall response to yields and then performed a principal component analysis. The findings revealed that the SEDI and the SPEI displayed the highest correlations with maize yields, followed by SPI, while SPET exhibited the lowest correlations. Principal component analysis demonstrated a heightened predictive capacity of drought indices between February and March, particularly at 7–8-month scales, alongside the widely used 3-month temporal scale for monitoring agricultural droughts. The stronger correlations exhibited by SEDI and SPEI, which incorporate atmospheric evaporative demand into their calculations, suggest that water availability is not the sole meteorological factor influencing drought impacts. Atmospheric demand considers temperature and air humidity, factors that intensify plant stress conditions. These findings supported the importance of considering flexible drought indices adapted to different time-scales for accurate monitor of agricultural droughts, which can enhance planning and risk mitigation in crop production in the Pampas Region and beyond.","PeriodicalId":7522,"journal":{"name":"Agronomy Journal","volume":"117 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143113764","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 brief history of remote sensing of soybean 大豆遥感简史

IF 2 3区农林科学

Agronomy Journal Pub Date : 2025-01-09 DOI: 10.1002/agj2.70004

Joby M. Prince Czarnecki, Sathishkumar Samiappan, Raju Bheemanahalli, Yanbo Huang, Sadia Alam Shammi

{"title":"A brief history of remote sensing of soybean","authors":"Joby M. Prince Czarnecki, Sathishkumar Samiappan, Raju Bheemanahalli, Yanbo Huang, Sadia Alam Shammi","doi":"10.1002/agj2.70004","DOIUrl":"https://doi.org/10.1002/agj2.70004","url":null,"abstract":"The last 20 years have been a period of significant advancement in the tools available for remote sensing of soybean [Glycine max (L.) Merr.] in terms of price, ease of use, quality of information provided, and range of available research applications. This review article posits that now is an appropriate time to reflect on the previous two decades of research effort devoted to remote sensing of soybean to gain an appreciation for how far the field has come, while also acknowledging how much work remains to be performed. Structured by field management activities, this review is based on selected works culled from a broad search. These works contributed meaningful knowledge specific to soybean or elucidated key points not presented in those more intentionally focused on soybean. While there were many successes in the varied applications of remote sensing in soybean research, taking this 20-year perspective also exposed areas of unmet expectations. Advances in knowledge are hampered by systemic challenges with inconsistent results and confounding factors imposed by research settings. There is potential to address these challenges by tempering expectations for what is possible and addressing reporting standards and data needs, specifically related to machine learning. The future is bright, but a concerted community effort is needed to continue to advance the state of knowledge into the next 20 years.","PeriodicalId":7522,"journal":{"name":"Agronomy Journal","volume":"117 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/agj2.70004","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143113827","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