Agronomy Journal最新文献

{"title":"On-farm foliar application of a humic biostimulant increases the yield of rice","authors":"Juan Izquierdo,&nbsp;Osvin Arriagada,&nbsp;Gustavo García-Pintos,&nbsp;Rodomiro Ortiz,&nbsp;Martín García-Pintos,&nbsp;Marcelo García-Pintos","doi":"10.1002/agj2.21641","DOIUrl":"10.1002/agj2.21641","url":null,"abstract":"<p>Biostimulants play a crucial role in enhancing crop yields while promoting sustainability and environmental responsibility. Evaluating the efficacy of biostimulants on-farm requires rigorous, multiyear trials conducted across various locations and with different cultivars. This study was conducted in Uruguay from 2015 to 2023 to assess the impact of a single application of a humic biostimulant (HB) during the R3 phenological stage on irrigated rice (<i>Oryza sativa</i> L.). The study encompassed 103 farms situated in diverse cropping zones, each characterized by distinct cultivars, soil qualities, radiation, and temperature conditions across the East and North regions. Results revealed that the HB treatment elicited an average yield increase of 7.4% across all sites. Notably, 93% (97) of the trials exhibited a positive yield response, with an average increase of 8.5%, while only six trials (all in the eastern zone) showed a negative response to the HB treatment. A combined analysis of variance indicated that the biostimulant's effect did not significantly differ between production zones, years, or rice cultivars when negative responses were excluded. Furthermore, relationships with environmental variables were nonsignificant, underscoring the positive effect of the biostimulant regardless of location. These findings hold significant implications for Uruguay's rice sector, that is, integrating HBs into standard management practices could substantially boost irrigated rice yields in rice-producing areas.</p>","PeriodicalId":7522,"journal":{"name":"Agronomy Journal","volume":"116 5","pages":"2551-2563"},"PeriodicalIF":2.0,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/agj2.21641","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141611370","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}

{"title":"Machine learning models for classifying coffee fruits detachment force","authors":"Mariana D. Meneses,&nbsp;Vinicius dos Santos Carreira,&nbsp;Bruno Rafael de Almeida Moreira,&nbsp;Welington Gonzaga do Vale,&nbsp;Glauco de Souza Rolim,&nbsp;Rouverson Pereira da Silva","doi":"10.1002/agj2.21633","DOIUrl":"10.1002/agj2.21633","url":null,"abstract":"<p>The maturation process of coffee (<i>Coffea arabica</i>) trees exhibits inherent variability, producing fruits at various physiological maturity stages. This variability affects the resistance between the fruit and its peduncle, posing a challenge in mechanized harvesting: non-selective harvesting. A precise classification of coffee fruit detachment force is essential to address this challenge, ensuring coffee's quality and producer's profitability. This study assesses the efficacy of machine learning (ML) models in determining the detachment force across various coffee cultivars under drip-irrigated and rainfed conditions. The dataset included detachment force measurements from 24 cultivars—13 drip-irrigated and 11 rainfed—yielding 1152 data points. Variance analysis compared irrigation methods and three maturity stages: green, cherry, and dry. Detachment force was categorized into four classes based on the dataset's quartile distribution. The ML models utilized were random forest (RF), support vector machine (SVM), K-nearest neighbors, and artificial neural networks. The SVM model was notably effective in classifying detachment force for rainfed cultivars, with a Matthews correlation coefficient (MCC) of 0.78. In contrast, the RF model was particularly adept for drip-irrigated cultivars, with an MCC of 0.75. The highest classification accuracies were recorded for the extreme force classes I and IV, with precision values of 0.93 and 0.8, respectively, while classes II and III had lower precision at 0.57 and 0.69. Implementing these ML models for detachment force classification has been beneficial, improving decision-making in mechanized harvesting systems.</p>","PeriodicalId":7522,"journal":{"name":"Agronomy Journal","volume":"116 5","pages":"2362-2369"},"PeriodicalIF":2.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141587111","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}

{"title":"Soil health indicators for predicting corn nitrogen requirement in long-term cover cropping","authors":"Sapana Pokhrel,&nbsp;Rory O. Maguire,&nbsp;Wade E. Thomason,&nbsp;Ryan Stewart,&nbsp;Michael Flessner,&nbsp;Mark Reiter","doi":"10.1002/agj2.21628","DOIUrl":"10.1002/agj2.21628","url":null,"abstract":"<p>Efforts to address economic and environmental concerns surrounding nitrogen (N) have motivated attempts to improve estimates of plant-available N in soil. Several soil health indicators, including CO₂ burst, permanganate oxidizable carbon (C) (POXC), and autoclaved-citrate extractable (ACE) soil protein, assess labile C and N, and therefore may help to estimate soil N mineralization in long-term cover cropping systems (&gt;3 years). This study evaluated the relationship of CO₂ burst, POXC, ACE-soil protein, and pre-sidedress nitrate test (PSNT) with agronomic optimum N rate (AONR) in corn (<i>Zea mays</i> L.). The study also looked at relationship between other soil test and corn yield parameters, relative yield (RY) and yield without N sidedress at 25 long-term cover crop sites across Virginia. Results showed relatively weak correlations between AONR and CO₂ burst, POXC, ACE-soil protein, and NO₃-N (<i>r</i> = 0.00 to −0.48), which indicates that these soil health tests may not reliably predict soil N availability and corn yield. Corn yield with zero-sidedress N rate had a negative relationship with cover crop C:N ratio (<i>r</i> = −0.66) and a positive relationship with cover crop N content (<i>r</i> = 0.59), and NO₃-N at pre-planting (<i>r</i> = 0.54) and sidedress (PSNT) (<i>r</i> = 0.63). The PSNT showed a better relationship (<i>r</i> = 0.65) compared to 72-h CO₂ burst (<i>r</i> = 0.48) with RY. Soil health indicators (CO₂ burst, POXC and ACE-soil protein) resulted in a poor or no relationship with AONR. Our results indicate that the PSNT was a more reliable indicator of the sidedress N rate in corn.</p>","PeriodicalId":7522,"journal":{"name":"Agronomy Journal","volume":"116 5","pages":"2186-2199"},"PeriodicalIF":2.0,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/agj2.21628","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141547061","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}

{"title":"The determination of desired plant density in soils with different fertility in a region for mechanized rice cultivation","authors":"Hamid Reza Mobasser,&nbsp;Seyyed Ali Sadeghi,&nbsp;Farshid Alipour Abookheili","doi":"10.1002/agj2.21631","DOIUrl":"10.1002/agj2.21631","url":null,"abstract":"<p>Physicochemical characteristics of soil, especially organic matter and soil texture, affect the optimal plant density in rice (<i>Oryza sativa</i> L.). A split-plot field experiment was done based on a randomized complete block design (RCBD) in four replications in Amol (Northern Iran) on the coastal strip of the Caspian Sea. The experimental treatments, that is, soil fertility (infertile, semi-fertile, and fertile) as the whole-plot factor and plant density (low, medium, and high by 15.2, 19.6, and 27.8 plants m⁻², respectively) as the split-plot factor, were studied over 2 years (2022 and 2023). The results indicated the greatest and smallest number of days from planting to tillering and from tillering to flowering for infertile soil, respectively. The maximum root fresh weight was measured during the tillering stage for infertile soil, whereas for fertile soil, the highest root fresh weight was recorded throughout the phases of panicle initiation and flowering. The greatest root length was measured at the tillering stage for 2022 in high-density infertile soil. The lowest number of panicles m⁻² and the percentage of full spikelets were obtained from infertile soil. The highest grain yield was obtained from high-density fertile soil. In mechanized rice cultivation, high density is suggested for fertile and semi-fertile soils and low density for infertile soil.</p>","PeriodicalId":7522,"journal":{"name":"Agronomy Journal","volume":"116 5","pages":"2217-2228"},"PeriodicalIF":2.0,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141577725","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}

{"title":"Achieving higher grain yield in hybrid rice through the promotion of individual growth and development","authors":"Min Huang,&nbsp;Ruichun Zhang,&nbsp;Ge Chen,&nbsp;Longsheng Liu,&nbsp;Zhongxi Li,&nbsp;Jiana Chen,&nbsp;Fangbo Cao","doi":"10.1002/agj2.21632","DOIUrl":"10.1002/agj2.21632","url":null,"abstract":"<p>Ensuring rice (<i>Oryza sativa</i>) self-sufficiency in China relies significantly on achieving high grain yields in hybrid rice production. This study conducted field experiments across two site-years, comparing grain yield per unit of land area, grain yield generated per seedling, and associated yield traits for a hybrid rice variety under two combinations of hill spacing and the number of seedlings per hill. The combinations included a hill spacing of 30 cm × 14 cm with one seedling per hill (H14S1) and a hill spacing of 30 cm × 24 cm with three seedlings per hill (H24S3). The results revealed that H14S1 consistently outperformed H24S3, demonstrating a 7%–16% increase in grain yield per unit of land area and an impressive 88%–104% higher grain yield generated per seedling. H14S1 exhibited 56%–77% more panicles formed per seedling and 10%–15% more spikelets per panicle compared to H24S3. H14S1 produced 78%–115% higher biomass at heading and maturity per seedling and 8%–25% higher biomass at heading and maturity per tiller than H24S3. This study underscores the importance of promoting the individual growth and development of seedlings as a crucial strategy for achieving higher grain yield in hybrid rice production.</p>","PeriodicalId":7522,"journal":{"name":"Agronomy Journal","volume":"116 5","pages":"2427-2434"},"PeriodicalIF":2.0,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141547062","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}

{"title":"Rice breeding for multi-canopy system: Estimations of genetic parameters and response to selection","authors":"Ma'rifatus Sholehah,&nbsp;Willy Bayuardi Suwarno,&nbsp;Vany Putri Hapsari,&nbsp;Nisfia Nurfirdausy Sulistyo,&nbsp;Siti Marwiyah,&nbsp;Hajrial Aswidinnoor","doi":"10.1002/agj2.21629","DOIUrl":"10.1002/agj2.21629","url":null,"abstract":"<p>One strategy currently being developed to increase rice (<i>Oryza sativa</i> L.) productivity is using a multi-canopy cropping system in rice cultivation. This method involves planting tall and short rice genotypes in the same hill. The objective of this experiment was to estimate the genetic parameters and response to selection in multi-canopy rice. Each experiment was arranged in an augmented randomized complete block design with five replications for the checks. In the first planting season, 200 F₃ families from IPB196 and IPB197 populations were planted in monoculture and multi-canopy as the short genotypes. IPB187-F-40-1-1 was used in multi-canopy as the tall genotype. Selection of 25% based on grain weight per hill of short genotype in multi-canopy was performed, and 50 families were selected and their F₄ seeds were planted in the second season along with the same tall genotype. The results indicated the genotype × cropping system was significant for grain weight per hill in the F₃ and F₄ generations. Grain weight per hill has a similar realized <i>h</i>²_ns in the multi-canopy (0.58) with monoculture (0.54). Meanwhile, the response to selection in multi-canopy (3.60) was higher compared to monoculture (2.09), and therefore the selection of rice lines for a multi-canopy system should be conducted in the multi-canopy environment. A selection percentage of 5% resulted in a higher response to selection. These findings may provide insight into the acceleration of breeding rice varieties for the multi-canopy system.</p>","PeriodicalId":7522,"journal":{"name":"Agronomy Journal","volume":"116 5","pages":"2129-2140"},"PeriodicalIF":2.0,"publicationDate":"2024-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/agj2.21629","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141531304","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}

{"title":"Representing cropping systems with the MEMS 2 ecosystem model","authors":"Yao Zhang,&nbsp;Alison E. King,&nbsp;Emma Hamilton,&nbsp;M. Francesca Cotrufo","doi":"10.1002/agj2.21611","DOIUrl":"10.1002/agj2.21611","url":null,"abstract":"<p>Croplands have been the focus of substantial investigation due to their considerable potential for sequestering carbon. Understanding the potential for soil organic carbon (SOC) sequestration and necessary management strategies will be enabled with accurate process-based models. Accurately representing crop growth and agricultural practices will be critical for realistic SOC modeling. The MEMS 2 model incorporates a current understanding of SOC formation and stabilization, measurable SOC pools, and deep SOC dynamics and is seen as a highly promising tool to inform management intervention for SOC sequestration. Thus far, MEMS 2 has been developed to represent grasslands. In this study, we further developed MEMS 2 to model annual grain crops and common agricultural practices, such as irrigation, fertilization, harvesting, and tillage. Using four Ameriflux sites, we demonstrated an accurate simulation of crop growth and development. Model performance was strong for simulating aboveground biomass (index of agreement [<i>d</i>] range of 0.89–0.98) and green leaf area index (<i>d</i> from 0.90 to 0.96) across corn, soybean, and winter wheat. Good agreement with observations was also achieved for net ecosystem CO₂ exchange (<i>d</i> from 0.90 to 0.96), evapotranspiration (<i>d</i> from 0.91 to 0.94), and soil temperature (<i>d</i> of 0.96), while discrepancy with the available soil water content data remain (<i>d</i> from 0.14 to 0.81 at four depths to 100 cm). While we will continue model testing and improvement, MEMS 2 (version 2.14) has now demonstrated its ability to effectively simulate the growth of common grain crops and practices.</p>","PeriodicalId":7522,"journal":{"name":"Agronomy Journal","volume":"116 5","pages":"2328-2345"},"PeriodicalIF":2.0,"publicationDate":"2024-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/agj2.21611","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141518204","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}

{"title":"Reformulation of dicamba herbicide: Impacts on offsite transport and soybean damage","authors":"Caleb R. Hammer,&nbsp;Timothy J. Griffis,&nbsp;John M. Baker,&nbsp;Pamela J. Rice,&nbsp;Lara E. Frankson,&nbsp;Jeffrey L. Gunsolus,&nbsp;Matthew D. Erickson,&nbsp;Ke Xiao,&nbsp;Aarti P. Mistry,&nbsp;Debalin Sarangi","doi":"10.1002/agj2.21630","DOIUrl":"10.1002/agj2.21630","url":null,"abstract":"<p>The herbicide dicamba (3,6-dichloro-2-methoxybenzoic acid) is commonly used to control broadleaf weeds in soybeans. Dicamba, however, is susceptible to volatilization and drift, thereby causing significant plant damage to nontarget crops downwind. Dicamba was reformulated to reduce volatility and off-target movement. The effectiveness of the dicamba reformulation was assessed by quantifying dicamba emissions following spray application and investigated how meteorological factors influenced the off-target movement. The experiments were conducted at the University of Minnesota Agricultural Experiment Station (UMORE Park) during the growing season of 2018, 2019, 2021, and 2022. Multiple high-flow polyurethane foam air samplers were used to measure dicamba concentrations downwind from a 4-ha soybean field sprayed with dicamba. Dicamba emissions were estimated using backward Lagrangian modeling constrained by the air sample observations. The results indicate that dicamba emissions and downwind transport were significant for several days following application. Further, non-traited soybeans located within 15–45 m showed substantial dicamba-related damage. In warmer, drier seasons, increased dicamba emissions caused more severe damage to downwind soybeans, likely worsened by drought stress preventing recovery. Favorable atmospheric conditions that reduced potential drift can be difficult to achieve in terms of the typical weather experienced over agricultural sites in the Upper Midwest. These results indicate that the dicamba reformulation has not adequately prevented significant post-spray volatilization losses and downwind transport.</p>","PeriodicalId":7522,"journal":{"name":"Agronomy Journal","volume":"116 5","pages":"2200-2216"},"PeriodicalIF":2.0,"publicationDate":"2024-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/agj2.21630","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141505795","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}

{"title":"Developing statistical models of aflatoxin risk in peanuts using historical weather data","authors":"Da-Young Kim,&nbsp;Fikadu Getachew,&nbsp;Barry L. Tillman,&nbsp;Brendan Zurweller,&nbsp;William M. Hammond,&nbsp;Alina Zare,&nbsp;Raegan Holton,&nbsp;Zachary Brym","doi":"10.1002/agj2.21627","DOIUrl":"10.1002/agj2.21627","url":null,"abstract":"<p>Aflatoxin contamination in peanuts (<i>Arachis hypogaea</i> L.) is a significant public health risk. Aflatoxin is detected postharvest after inspection of loads associated with grading at peanut buying points, leaving growers and shellers in a precarious position. Stricter limits on aflatoxin contamination could restrict the United States access to international markets. Predicting aflatoxin risk remains challenging, but improved tools could help inform postharvest storage segregation decisions and alert industry stakeholders to seasonal threats. This study aimed to develop and evaluate multiple statistical models that estimate the regional status of peanut aflatoxin contamination based on preharvest weather conditions. Our approach expanded on an existing peanut aflatoxin model for which a new geographic area and time period were tested. Weather variables served as independent variables to predict the risk of aflatoxin as the proportion of samples with greater than 20 ppb and 4 ppb aflatoxin (PGT20 [the proportion of samples with greater than 20 ppb aflatoxin] and PGT4 [the proportion of samples with greater than 4 ppb aflatoxin], respectively) across 10 counties in Georgia for 2018–2022. Best-performing models were developed through multiple linear stepwise regression explaining more than 72% and 41% of the variability in PGT20 and PGT4, respectively. Model performance further varied whether it was a year of low or high aflatoxin incidence, with temperature observed as a key influencing factor across best-performing models. This study established an adaptive approach to monitoring and managing aflatoxin risk through statistical predictive modeling, with output targeting farmers, industry, regulators, and public health officials. Future model development will aim to improve interpretation and confidence with in-season aflatoxin prediction and efficacy testing of this approach across space and time.</p>","PeriodicalId":7522,"journal":{"name":"Agronomy Journal","volume":"116 5","pages":"2346-2361"},"PeriodicalIF":2.0,"publicationDate":"2024-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/agj2.21627","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141518203","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}

{"title":"Soybean planting dates and maturity groups: Maximizing yield potential and decreasing risk in Louisiana","authors":"David Moseley,&nbsp;Andre Reis,&nbsp;Thanos Gentimis,&nbsp;Priscila Campos,&nbsp;Josh Copes,&nbsp;Melanie Netterville,&nbsp;Peters Egbedi,&nbsp;Dustin Harrell,&nbsp;Manoch Kongchum,&nbsp;Ronnie Levy,&nbsp;Boyd Padgett,&nbsp;Samuel Soignier,&nbsp;Derek Scroggs,&nbsp;Jason Sanders,&nbsp;Joe Pankey,&nbsp;Katarzyna Fic","doi":"10.1002/agj2.21626","DOIUrl":"10.1002/agj2.21626","url":null,"abstract":"<p>Soybean [<i>Glycine max</i> (L.) Merr.] producers in Louisiana began shifting to an early soybean production system (ESPS) in the early 2000s by planting earlier maturing varieties in April and May. Although this shift in planting practices has been supported by research elsewhere beginning in the mid-1990s, there is minimum data focusing on the ESPS across Louisiana. The overall objective of this research was to evaluate the effect of planting date, maturity group (MG), and their combination across a comprehensive set of yield environments in the state of Louisiana to determine the combination of optimum planting date and MG for soybean production. We gathered field data from the 2013 to 2020 seasons originated from three Louisiana State University AgCenter research stations and four seed companies. A total of 428, 926, and 331 observations were analyzed from the Northeast, Central, and Southwest Louisiana regions, respectively. When including all data from across Louisiana, the optimum planting date was April 30. Breaking by regions, the average optimum planting date for the Northeast Louisiana region was April 9. The Central and Southwest results were divided by MG section, and the approximate optimum planting dates were April 15 and May 15, respectively. These results support the ESPS for the Northeast and Central Louisiana regions, but not for the Southwest Louisiana region. Optimizing planting recommendation is a critical component for supporting the development of varieties suitable for the southern production systems of the United States.</p>","PeriodicalId":7522,"journal":{"name":"Agronomy Journal","volume":"116 5","pages":"2174-2185"},"PeriodicalIF":2.0,"publicationDate":"2024-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/agj2.21626","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141505794","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}