Background Zonal application maps are designed to represent field variability using key variables that can be translated into tailored management practices.For cotton,zonal maps for crop growth regulator(CGR)applicati...Background Zonal application maps are designed to represent field variability using key variables that can be translated into tailored management practices.For cotton,zonal maps for crop growth regulator(CGR)applications under variable-rate(VR)strategies are commonly based exclusively on vegetation indices(VIs)variability.However,VIs often saturate in dense crop vegetation areas,limiting their effectiveness in distinguishing variability in crop growth.This study aimed to compare unsupervised framework(UF)and supervised framework(SUF)approaches for generat-ing zonal application maps for CGR under VR conditions.During 2022-2023 agricultural seasons,an UF was employed to generate zonal maps based on locally collected field data on plant height of cotton,satellite imagery,soil texture,and phenology data.Subsequently,a SUF(based on historical data between 2020-2021 to 2022-2023 agricultural seasons)was developed to predict plant height using remote sensing and phenology data,aiming to replicate same zonal maps but without relying on direct field measurements of plant height.Both approaches were tested in three fields and on two different dates per field.Results The predictive model for plant height of SUF performed well,as indicated by the model metrics.However,when comparing zonal application maps for specific field-date combinations,the predicted plant height exhibited lower variability compared with field measurements.This led to variable compatibility between SUF maps,which utilized the model predictions,and the UF maps,which were based on the real field data.Fields characterized by much pronounced soil texture variability yielded the highest compatibility between the zonal application maps produced by both SUF and UF approaches.This was predominantly due to the greater consistency in estimating plant development patterns within these heterogeneous field environments.While VR application approach can facilitate product savings during the application operation,other key factors must be considered.These include the availability of specialized machinery required for this type of applications,as well as the inherent operational costs associated with applying a single CGR product which differs from the typical uniform rate applications that often integrate multi-ple inputs.Conclusion Predictive modeling shows promise for assisting in the creation of zonal application maps for VR of CGR applications.However,the degree of agreement with the actual variability in crop growth found in the field should be evaluated on a field-by-field basis.The SUF approach,which is based on plant heigh prediction,demonstrated potential for supporting the development of zonal application maps for VR of CGR applications.However,the degree to which this approach aligns itself with the actual variability in crop growth observed in the field may vary,necessi-tating field-by-field evaluation.展开更多
<span>Total crop load has an inverse relationship with fruit size, while larger fruit size is often demanded by the peach and nectarine markets. Hand-thinning is extremely expensive, and thus, crop load adjustme...<span>Total crop load has an inverse relationship with fruit size, while larger fruit size is often demanded by the peach and nectarine markets. Hand-thinning is extremely expensive, and thus, crop load adjustment, using blossom thinners is a crucial practice to ensure production of commercially acceptable fruit size and yield efficiency in stone fruit. In this study, the influence of branched secondary alcohol ethoxylate (Tergitol TMN-6) and/or ammonium thiosulfate (ATS), Crocker Fish Oil</span><span style="font-family:;" "=""> </span><span style="font-family:;" "=""><span>(FO), and a mixture of calcium polysulfides and thiosulfate (lime sulfur) on fruit set and quality attributes in peaches (</span><i><span>Prunus</span></i><span> <i>persica</i></span><span>) </span><span>and nectarines (</span><i><span>P</span></i><span><span>. </span><i><span>persica</span></i></span><span> var. </span><i><span>nectarina</span></i><span>) were studied. All blossom thinners reduced fruit set in “Summer Lady” peach in both 2016 and 2017. Fruit sets in “Summer Lady” peach trees </span><span>with a double application of </span><span><span>Tergitol TMN-6 at the rate of 7.5 or 10 mL</span><span></span> <span>·</span><span></span><span></span><span></span><span>L</span><span style="color:#4F4F4F;">¯</span><span></span></span><sup><span>1</span></sup><span><span>, each rate applied at 40% and 80% bloom, were lower than those receiving the same rates of this chemical only at 80% bloom, but they were similar to those receiving a single Tergitol TMN-6 spray at 15 mL</span><span>·</span><span>L</span><span style="color:#4F4F4F;">¯</span><span></span></span><sup><span>1</span></sup><span><span> at 80% or 100% bloom. “Summer Lady” peach trees receiving FO at 20 mL</span><span>·</span><span>L</span><span style="color:#4F4F4F;">¯</span><span></span></span><sup><span>1</span></sup><span><span> plus lime sulfur at 25 mL</span><span style="color:#4F4F4F;">·</span><span>L</span><span style="color:#4F4F4F;">¯</span><span></span></span><sup><span>1</span></sup><span><span>, once at 40% bloom and again at 80% bloom had lower fruit set as compared to Untreated Control but the fruit set was higher than those with any Tergitol-TMN-6 spray. Tergitol TMN-6 at 12 m</span><span style="color:#4F4F4F;">·</span><span>L</span><span style="color:#4F4F4F;">¯</span><span></span></span><sup><span>1</span></sup><span><span> at 100% bloom or 10 mL</span><span style="color:#4F4F4F;">·</span><span>L</span><span style="color:#4F4F4F;">¯</span><span></span></span><sup><span>1</span></sup><span> all stages of bloom reduced fruit set in “Zee Lady</span></span><span>”</span><span> and </span><span>“</span><span><span>Snow Giant” peaches. In “Snow Giant” peach, trees receiving Tergitol TMN-6 at all concentrations and blossom stages had significantly higher fruit weight as compared to the trees of Un-treated Control.</span><span> </span><span>Applications of Tergitol TMN-6 at all concentrations at 80% bloom reduced fruit set in “Red Globe” and “Elberta” peaches in Utah. ATS and FO slightly reduced fruit set in peaches but they were less effective than Tergitol TMN-6 in all cases. Overall, it is concluded that efficacy of blossom thinners depends on the rate of thinners, temperature, cultivar and stage of bloom development.</span></span>展开更多
文摘Background Zonal application maps are designed to represent field variability using key variables that can be translated into tailored management practices.For cotton,zonal maps for crop growth regulator(CGR)applications under variable-rate(VR)strategies are commonly based exclusively on vegetation indices(VIs)variability.However,VIs often saturate in dense crop vegetation areas,limiting their effectiveness in distinguishing variability in crop growth.This study aimed to compare unsupervised framework(UF)and supervised framework(SUF)approaches for generat-ing zonal application maps for CGR under VR conditions.During 2022-2023 agricultural seasons,an UF was employed to generate zonal maps based on locally collected field data on plant height of cotton,satellite imagery,soil texture,and phenology data.Subsequently,a SUF(based on historical data between 2020-2021 to 2022-2023 agricultural seasons)was developed to predict plant height using remote sensing and phenology data,aiming to replicate same zonal maps but without relying on direct field measurements of plant height.Both approaches were tested in three fields and on two different dates per field.Results The predictive model for plant height of SUF performed well,as indicated by the model metrics.However,when comparing zonal application maps for specific field-date combinations,the predicted plant height exhibited lower variability compared with field measurements.This led to variable compatibility between SUF maps,which utilized the model predictions,and the UF maps,which were based on the real field data.Fields characterized by much pronounced soil texture variability yielded the highest compatibility between the zonal application maps produced by both SUF and UF approaches.This was predominantly due to the greater consistency in estimating plant development patterns within these heterogeneous field environments.While VR application approach can facilitate product savings during the application operation,other key factors must be considered.These include the availability of specialized machinery required for this type of applications,as well as the inherent operational costs associated with applying a single CGR product which differs from the typical uniform rate applications that often integrate multi-ple inputs.Conclusion Predictive modeling shows promise for assisting in the creation of zonal application maps for VR of CGR applications.However,the degree of agreement with the actual variability in crop growth found in the field should be evaluated on a field-by-field basis.The SUF approach,which is based on plant heigh prediction,demonstrated potential for supporting the development of zonal application maps for VR of CGR applications.However,the degree to which this approach aligns itself with the actual variability in crop growth observed in the field may vary,necessi-tating field-by-field evaluation.
文摘<span>Total crop load has an inverse relationship with fruit size, while larger fruit size is often demanded by the peach and nectarine markets. Hand-thinning is extremely expensive, and thus, crop load adjustment, using blossom thinners is a crucial practice to ensure production of commercially acceptable fruit size and yield efficiency in stone fruit. In this study, the influence of branched secondary alcohol ethoxylate (Tergitol TMN-6) and/or ammonium thiosulfate (ATS), Crocker Fish Oil</span><span style="font-family:;" "=""> </span><span style="font-family:;" "=""><span>(FO), and a mixture of calcium polysulfides and thiosulfate (lime sulfur) on fruit set and quality attributes in peaches (</span><i><span>Prunus</span></i><span> <i>persica</i></span><span>) </span><span>and nectarines (</span><i><span>P</span></i><span><span>. </span><i><span>persica</span></i></span><span> var. </span><i><span>nectarina</span></i><span>) were studied. All blossom thinners reduced fruit set in “Summer Lady” peach in both 2016 and 2017. Fruit sets in “Summer Lady” peach trees </span><span>with a double application of </span><span><span>Tergitol TMN-6 at the rate of 7.5 or 10 mL</span><span></span> <span>·</span><span></span><span></span><span></span><span>L</span><span style="color:#4F4F4F;">¯</span><span></span></span><sup><span>1</span></sup><span><span>, each rate applied at 40% and 80% bloom, were lower than those receiving the same rates of this chemical only at 80% bloom, but they were similar to those receiving a single Tergitol TMN-6 spray at 15 mL</span><span>·</span><span>L</span><span style="color:#4F4F4F;">¯</span><span></span></span><sup><span>1</span></sup><span><span> at 80% or 100% bloom. “Summer Lady” peach trees receiving FO at 20 mL</span><span>·</span><span>L</span><span style="color:#4F4F4F;">¯</span><span></span></span><sup><span>1</span></sup><span><span> plus lime sulfur at 25 mL</span><span style="color:#4F4F4F;">·</span><span>L</span><span style="color:#4F4F4F;">¯</span><span></span></span><sup><span>1</span></sup><span><span>, once at 40% bloom and again at 80% bloom had lower fruit set as compared to Untreated Control but the fruit set was higher than those with any Tergitol-TMN-6 spray. Tergitol TMN-6 at 12 m</span><span style="color:#4F4F4F;">·</span><span>L</span><span style="color:#4F4F4F;">¯</span><span></span></span><sup><span>1</span></sup><span><span> at 100% bloom or 10 mL</span><span style="color:#4F4F4F;">·</span><span>L</span><span style="color:#4F4F4F;">¯</span><span></span></span><sup><span>1</span></sup><span> all stages of bloom reduced fruit set in “Zee Lady</span></span><span>”</span><span> and </span><span>“</span><span><span>Snow Giant” peaches. In “Snow Giant” peach, trees receiving Tergitol TMN-6 at all concentrations and blossom stages had significantly higher fruit weight as compared to the trees of Un-treated Control.</span><span> </span><span>Applications of Tergitol TMN-6 at all concentrations at 80% bloom reduced fruit set in “Red Globe” and “Elberta” peaches in Utah. ATS and FO slightly reduced fruit set in peaches but they were less effective than Tergitol TMN-6 in all cases. Overall, it is concluded that efficacy of blossom thinners depends on the rate of thinners, temperature, cultivar and stage of bloom development.</span></span>
