Affect Soybean Yield Research Articles

Sowing date, genotype choice, and water environment control soybean yields in central Argentina

AbstractSoybean [Glycine max (L.) Merr.] is one of the most important crops worldwide, and Argentina is the third largest global grain producer and the worlds´ largest meal exporter. Under the continuous challenge of increasing crop yields, especially in the central temperate region of the country, there is a growing need to optimize management in relation to the environment that each specific farm and paddock presents. Understanding the impact of available technologies and management options can help optimize crop design. Here, we identify and quantify the effect of the most relevant variables affecting soybean yield by analyzing a database that includes 53 field trials with four common commercial genotypes, reporting 50 management and environmental variables. Linear mixed‐effect models revealed that two management decisions (genotype and sowing date selection) and three environmental variables (rainfall during the reproductive crop period from R1 to R7, soil type [Hapludoll vs. Argiudoll], and water table presence above or below 2 m of depth from the surface) helped explain ∼40% of total yield variability, which ranged from 1,675 to 7,226 kg ha−1 and averaged 5,133 kg ha−1. Water table presence generated higher and more stable yields particularly in coarse‐textured Hapludolls and under low‐rainfall conditions. Results highlight specific management and environmental conditions that affect soybean crop yields in the region, pointing to effective pathways toward yield gap reductions.

Soil chemical properties affecting soybean yield on a nationwide scale in Japan

ABSTRACT Wide-area surveys have been conducted on a prefectural or regional scale in Japan for revealing soil chemical properties affecting soybean yield. However, they vary by region and thus, the common chemical factors through Japan remain unclear. This study aims to identify the soil chemical properties involved in soybean yield based on field data in various prefectures throughout Japan. We collected datasets of the topsoil chemical properties and soybean yields at 228 sampling points from 16 prefectures in Japan over the period of 2015–2017. The data sampling was conducted on two fields with different yield levels, namely high- and low-yield groups, which were managed by the same cooperating farmers in each point. We regarded the two fields at each point as a pair for a pairwise comparison. The average yield of the high- and low-yield groups was 3.1 t ha−1 and 2.5 t ha−1, respectively. The p-values of the pairwise comparison results were calculated via the Wilcoxon signed rank test. The differences of the exchangeable Mg (p= 0.040), and the Mg/K (p= 0.027) and Ca/Mg (p= 0.007) ratio between the high-yield and low-yield groups were statistically significant, whereas the other variables were not significant. The exchangeable Mg and Mg/K ratio were negatively related to yield, while the Ca/Mg ratio was positively related. The results suggested that excessive Mg for K or Ca adversely affects the soybean yield. As far as we know, there have been few reports focusing on the relation between the exchangeable cation, especially for the cation balance, and soybean yield. Our results may help researchers and producers deepen their understanding of the relationship between soil chemical properties and soybean yield.

Genomic Research Favoring Higher Soybean Production.

Interest in the efficient production of soybean, as one of the most important crop plants, is significantly increasing worldwide. Soybean symbioses, the most important biological process affecting soybean yield and protein content, were revitalized due to the need for sustainable agricultural practices. Similar to many crop species, soybean can establish symbiotic associations with the soil bacteria rhizobia, and with the soil fungi, arbuscular mycorrhizal fungi, and other beneficial rhizospheric microorganisms are often applied as biofertilizers. Microbial interactions may importantly affect soybean production and plant health by activating different genomic pathways in soybean. Genomic research is an important tool, which may be used to elucidate and enhance the mechanisms controlling such actions and interactions. This review presents the available details on the genomic research favoring higher soybean production. Accordingly, new technologies applied to plant rhizosphere and symbiotic microbiota, root-plant endophytes, and details about the genetic composition of soybean inoculant strains are highlighted. Such details may be effectively used to enhance soybean growth and yield, under different conditions, including stress, resulting in a more sustainable production.

Seeding rates in late sowing affect soybean yield in Southern Brazil

Soybean seeding rate (SR) is commonly subject to genotype x environment interactions, and characterization of this interaction is necessary to improve yield potential of future cultivars, especially in late sowing. The objectives of this study were to evaluate yield and yield components of three soybean cultivars in different SR under late sowing in Southern Brazil. We observed an interaction between SR and cultivars under late sowing, in which the increase from 25 to 45 seeds m-2 increased yield by 12% and 23% for cultivars BMX Energia and TMG 7262, respectively, while for cultivar AFS 110 there was no SR effect. The cultivars used in this study can be classified from more to less responsive to SR in late sowing as follows: TMG 7262 > BMX Energia > AFS 110. Also, the cultivars used in this study can be classified from higher to lower yield potential in late sowing as follows: TMG 7262 > AFS 110 > BMX Energia. The yield components most correlated to yield were as follows: seeds per area, plant height, 100-seed weight and nodes in main stem, mainly. The increase in SR increased seeds per area and pods per area, while decreased seeds per pod, stem diameter and node number in branches. The identified plant attributes related to yield increase will contribute for developing future cultivars with greater yield potential under late sowing.

Effect of sowing season on soybean performance

The soybean presents great economic expression and high impact in the Brazilian agribusiness. The productive potential of a cultivar is expressed according to the genetic constitution and the environment. The sowing time exerts influence on the agronomic traits of the soybean, impacting the yield of grains. The objective of this study was to evaluate the influence of the sowing season on the productive potential and the agronomic traits of soybean. The work was conducted at the Capim Branco experimental farm, belonging to the Federal University of Uberlândia. Twelve cultivars (UFUS 6901, UFUS 7415, BRSMG 68, TMG 801, TMG 7062 IPRO, TMG 2158 IPRO, BRS 7270 IPRO, NA 5909 RR, NS 6909 RR, CD 2737 RR, P98Y30 RR e BRASMAX Desafio RR) and four sowing seasons (October 22, November 5, December 22, 2016 and January 5, 2017) were used. The experimental design was a randomized block design with four replicates. The evaluated characters were: number of days for flowering and maturity, plant height at maturity, insertion height for the first pod, number of nodes at maturity, total number of pods, number of tainted pods and productivity. The sowing carried out in October and November contributed to obtain a larger number of nodes and a greater height of plants at maturity, which are agronomic traits favorable to higher productivity. Sowing delay seriously affected soybean yield and in the Uberlândia MG region the ideal sowing time was October 22, before the beginning of November. In the late sowing in December and January, the cultivars that had their productions less affected were the conventional cultivars BRSMG 68 and TMG 801.

Indirect effects of deer on insect pests and soybean plants

Abstract White‐tailed deer (Odocoileus virginianus Zimmermann) and insect pests negatively affect soybean production; however, little is known about how these herbivores potentially interact to affect soybean yield. Previous studies have shown deer browse on non‐crop plants affects insect density and insect‐mediated leaf damage, which together reduce plant reproductive output. In soybeans, reproductive output is influenced by direct and indirect interactions of different herbivores. Here, we quantified indirect interactions between two groups of herbivores (mammals and insects) and their effects on soybean growth and yield. We examined responses of insect pest communities along a gradient of deer herbivory (29% to 49% browsed stems) in soybean monocultures. Structural equation models showed that deer browse had direct negative effects on soybean plant height and yield. Deer browse indirectly decreased insect‐mediated leaf damage by reducing plant height. Deer browse also indirectly increased pest insect abundance through reductions in plant height. Similarly, deer herbivory had an indirect positive effect on leaf carbon: nitrogen ratios through changes in plant height, thereby decreasing leaf nutrition. These results suggest that pest insect abundance may be greater on soybean plants in areas of higher deer browse, but deer browse may reduce insect herbivory through reduced leaf nutrition.

Harvest-aid herbicides influence soybean seed yield, quality and oxidative metabolism

Harvest-aid herbicides are used to anticipate soybean harvest and make the field available for next crop during the growing season. However, this anticipation can interrupt the transport of photoassimilates and reduce seed yield, as well as affect the seed quality. It is also not well known if cultivars with earlier growth cycle are more sensitive to harvest-aid herbicides. This work evaluated how different moments of harvest-aid herbicides application affect soybean yield, seed physiological quality, and oxidative metabolism. Two cultivars were used, one early and another medium growth cycle. The herbicide used was paraquat. Experiments were carried out in the field to evaluate yield attributes, and from the seeds harvested, seed quality attributes were evaluated in controlled environment. Early application of harvest-aid herbicides reduced seed yield and 1000-seed mass in both evaluated cultivars, being more expressive for early growth cycle cultivar. Seeds from plants submitted to early application of harvestaid herbicides had higher enzymatic activity related to oxidative metabolism. The early growth cycle cultivar (maturity group - MG 6.2) produced more than the medium growth cycle cultivar (MG 7.7), however, had greater sensitivity to the early application of harvest-aid herbicide.

Excluding Flying Insects During Flowering does not Affect Soybean Yield

The possible role of pollinators enhancing soybean production has been an ongoing topic of study. The effect of flower visitation, especially by honey bees, Apis mellifera L., in this self-pollinated crop has resulted in no benefit increasing soybean yield, or at times a significant impact on grain production, differences that might be caused by the influence of multiple field condition variables. In this study, an experimental design that excludes insects from soybean plants during the ∼20-day flowering period was used. Results indicated that he number of pods per plant, seeds per pod, and grain yield were not different in plants covered with mesh that prevented insect visitation to flowers, compared with adjacent soybean plants not covered. The single-season studies showed that despite a large number of active honey bee hives 25-50 m away from the evaluated soybean plants, the insects rarely entered the fields, and those that did, spent no time foraging, even when more than 5 million soybean flowers per hectare were available at a very short distance from their hives.

QTL mapping of drought tolerance traits in soybean with SLAF sequencing

Drought stress is an important factor affecting soybean yield. Improving drought tolerance of soybean varieties can increase yield and yield stability when the stress occurs. Identifying QTL related to drought tolerance using molecular marker-assisted selection is able to facilitate the development of drought-tolerant soybean varieties. In this study, we used a high-yielding and drought-sensitive cultivar ‘Zhonghuang 35’ and a drought-tolerant cultivar ‘Jindou 21’ to establish F6:9 recombinant inbred lines. We constructed a high-density genetic map using specific locus amplified fragment sequencing (SLAF-Seq) technology. The genetic map contained 8078 SLAF markers distributing across 20 soybean chromosomes with a total genetic distance of 3780.98 cM and an average genetic distance of 0.59 cM between adjacent markers. Two treatments (irrigation and drought) were used in the field tests, the Additive-Inclusive Composite Interval Mapping (ICIM-ADD) was used to call QTL, and plant height and seed weight per plant were used as the indicators of drought tolerance. We identified a total of 23 QTL related to drought tolerance. Among them, seven QTL (qPH2, qPH6, qPH7, qPH17, qPH19-1, qPH19-2, and qPH19-3) on chromosomes 2, 6, 7, 17, and 19 were related to plant height, and five QTL (qSWPP2, qSWPP6, qSWPP13, qSWPP17, and qSWPP19) on chromosomes 2, 6, 13, 17, and 19 were related to seed weight and could be considered as the major QTL. In addition, three common QTL (qPH6/qSWPP6, qPH17/qSWPP17, and qPH19-3/qSWPP19) for both plant height and seed weight per plant were located in the same genomic regions on the same chromosomes. Three (qPH2, qPH17, and qPH19-2) and four novel QTL (qSWPP2, qSWPP13, qSWPP17, and qSWPP19) were identified for plant height and seed weight per plant, respectively. Two pairs of QTL (qPH2/qSWPP2 and qPH17/qSWPP17) were also common for both plant height and seed weight per plant. These QTL and closely linked SLAF markers could be used to accelerate breeding for drought tolerant cultivars via MAS.

Can Palisade and Guinea Grass Sowing Time in Intercropping Systems Affect Soybean Yield and Soil Chemical Properties?

IIn tropical regions, intercropping systems under no-tillage improve biomass quantity, soil conservation, and cash crop productivity. However, the optimal sowing time for forage species in these cropping systems is unknown. The objective of this study was to evaluate the effects of two sowing times of palisade and guinea grass on forage production and quality, soybean yield and soil chemical properties. Palisade and guinea grasses were sown for intercropping with maize or after maize silage harvest (hereafter succession) in an experiment carried out over three crop seasons. We evaluated forage dry matter production, pasture nutritive values, straw nutrient content, soybean leaf nutrients, yield, and soil fertility. The highest dry matter production was 8.1 Mg ha−1 for guinea grass in the intercropping system (sum of 3 cuts). Sowing forage after maize silage harvest provided 4% more crude protein compared with intercropping, regardless of grass species. Soybean yield was over 1.0 Mg ha−1 higher when soybean was cropped in succession compared with intercropping; however, the effects of the two forage grasses on soybean production were similar. Soil pH, calcium and magnesium content, cation exchange capacity, and base saturation were higher in the intercropping systems than in the succession systems, particularly when guinea grass was cultivated. Sowing guinea grass after maize harvest provided better forage quality, nutrient cycling, soybean yields, and soil chemical properties in tropical conditions.

Soybean yield, protein content and oil quality in response to interaction of arbuscular mycorrhizal fungi and native microbial populations from mono- and rotation-cropped soils

Two main soil management practices are generally used for soybean production: monoculture (MC) and crop rotation (CR). These strategies have different impacts on soil microbial communities. Among them, arbuscular mycorrhizal fungi (AMF) are well known to provide access to nutrients in a majority of cultivated plants. AMF communities have been shown to be more diverse in CR than in MC. Because AMF species differ in their effects on nutrition and development of plants, it could be expected that soil biota from different soil management practices affect soybean yield and quality. Therefore the objective of this study was to examine the combined effects of soil microbial communities and soil management practices (MC and CR) on yield, protein content, and oil quality of soybean grown under greenhouse conditions. The effects of three soil treatments, namely: sterile (S); microorganisms without AMF (MO); and microorganisms with AMF (AMF) were evaluated. These treatments were applied to soils from two crop management practices (CR and MC). Sterile soil promoted lower numbers of pods and seed weight per plant in MC but not in CR. AMF showed increased seed protein content (12–14%) whereas MO presented increased oil concentration (20–27%) (mainly within CR). Soybean grown with AMF from CR soil showed significantly higher amounts of oleic acid (21–25%), and lower linoleic acid (9%) when compared with other treatments. Findings from this study suggest that soybean yield and quality are affected by crop management practices and soil biota composition. Further, these parameters should be considered at the time of selecting agricultural strategies.

Assessing cloudiness effect on soybean yield in the Southeast Brazil

The solar radiation is one of the most important weather variables for determining the potential yield of agricultural crops. Soybean is the main Brazilian agricultural commodity, with great social and economical importance for the country. It is well recognized that cloudiness is a limiting factor for crop growth rate. Few studies have been conducted to systematically evaluate how much cloud affect soybean yield and none, to our knowledge, is available for tropical soybean. The objective of this paper was to quantify the implications of cloudiness on soybean growth and development in tropical Brazil. To do so, experimental data associated with the simulations of the DSSAT/CROPGRO (DC) model was used, and two treatments were simulated: a) the first used measured solar radiation and b) the second used estimated solar radiation for non-cloud days. Thus, based on the model output variables (growth rate of aerial dry matter, grain yield, specific leaf weight, and light saturation point) and comparing the data with the literature review. We found that simulations exhibited an increase in the dry matter production rate of up to 23%, during days of clear sky, resulting in a yield increase between 26 and 37%. Also, the DC could simulate some adaptation in the plant when the solar radiation changes, like the specific foliar weight and the light-saturated photosynthesis rate.

Short‐run net returns to a cereal rye cover crop mix in a midwest corn–soybean rotation

AbstractUnsubstantiated economic returns are a major contributor to producers’ reluctance to adopt cover crops. The objective of this study is to evaluate the direct short‐run net returns to the producer of implementing a predominantly cereal rye (Secale cereal L.) cover crop mix into a Midwest corn (Zea mays L.)–soybean [Glycine max (L.) Merr.] rotation. Experimental agronomic data from field experiments in Lexington, IL, are used to calibrate economic simulations of the costs and benefits of cover crop adoption. Results indicate that net returns to cover crops, including current cost‐share payments, were routinely negative. Returns to the soybean phase of the rotation were higher than corn given that the cover crop significantly reduced corn yield in 1 of 2 yr but did not significantly affect soybean yield. A scenario where cover crop biomass was hypothetically harvested and valued as a livestock feedstuff increased returns. However, further research is needed to validate the agronomic assumptions underlying this scenario. Finally, the breakeven subsidy that would make the producer indifferent to planting cover crops was estimated to be US$13–$23 kg–1 of nitrate saved from leaving the field each year (or approximately $195–$345 ha–1). This is higher than current cost‐share payments ($140 ha–1). In the short‐run, incentivizing producers to adopt cover crops will likely require (i) improved recommendations for cover crop best management practices to eliminate current downside risk and (ii) higher cost‐share payments or established markets to internalize cover crop benefits that accrue to society.

Identification of QTN and Candidate Gene for Seed-flooding Tolerance in Soybean [Glycine max (L.) Merr.] using Genome-Wide Association Study (GWAS).

Seed-flooding stress is one of the major abiotic constraints severely affecting soybean yield and quality. Understanding the molecular mechanism and genetic basis underlying seed-flooding tolerance will be of greatly importance in soybean breeding. However, very limited information is available about the genetic basis of seed-flooding tolerance in soybean. The present study performed Genome-Wide Association Study (GWAS) to identify the quantitative trait nucleotides (QTNs) associated with three seed-flooding tolerance related traits, viz., germination rate (GR), normal seedling rate (NSR) and electric conductivity (EC), using a panel of 347 soybean lines and the genotypic data of 60,109 SNPs with MAF > 0.05. A total of 25 and 21 QTNs associated with all three traits were identified via mixed linear model (MLM) and multi-locus random-SNP-effect mixed linear model (mrMLM) in three different environments (JP14, HY15, and Combined). Among these QTNs, three major QTNs, viz., QTN13, qNSR-10 and qEC-7-2, were identified through both methods MLM and mrMLM. Interestingly, QTN13 located on Chr.13 has been consistently identified to be associated with all three studied traits in both methods and multiple environments. Within the 1.0 Mb physical interval surrounding the QTN13, nine candidate genes were screened for their involvement in seed-flooding tolerance based on gene annotation information and available literature. Based on the qRT-PCR and sequence analysis, only one gene designated as GmSFT (Glyma.13g248000) displayed significantly higher expression level in all tolerant genotypes compared to sensitive ones under flooding treatment, as well as revealed nonsynonymous mutation in tolerant genotypes, leading to amino acid change in the protein. Additionally, subcellular localization showed that GmSFT was localized in the nucleus and cell membrane. Hence, GmSFT was considered as the most likely candidate gene for seed-flooding tolerance in soybean. In conclusion, the findings of the present study not only increase our knowledge of the genetic control of seed-flooding tolerance in soybean, but will also be of great utility in marker-assisted selection and gene cloning to elucidate the mechanisms of seed-flooding tolerance.

Soybean intraspecific genetic variation in response to elevated CO2

ABSTRACTAlthough elevated atmospheric CO2 concentration (elevated CO2 (eCO2)) considerably affect soybean yield, the agronomic and physiological contributors to the yield variation among cultivars in response to eCO2 have not been fully understood. Such investigation will fundamentally benefit future breeding strategies to enhance soybean adaptability to eCO2 environments. Twenty-four soybean cultivars were exposed to ambient CO2 (aCO2, 390 ppm) or eCO2 (580 ppm) throughout growth stages. The results showed the stimulation of eCO2 on soybean yield varied among cultivars, resulting in the increase from 3.3% in Yuanbaojin to 95% in Suinong 8. The yield gain under eCO2 was negatively correlated with yield under aCO2. The increases of the pod and seed number (sink) were strongly positive correlated (P< 0.001) with the increase of yield, but not the change of seed number per pod, seed size, leaf area, and leaf nitrogen and chlorophyll concentrations at the initial pod filling stage (R5). There was a strong positive correlation between yield gain and the accumulation of biomass during R5–R8 (full maturity). These results indicated that, among cultivars, the potential of sink size and the strength of photosynthetic capability during R5–R8 could be the limiting factors to yield response to eCO2.

Winter grazing does not affect soybean yield despite lower soil water content in a subtropical crop-livestock system

Commercial-scale integrated crop-livestock systems intensify land use by combining complementary agricultural enterprises and leveraging synergistic ecosystem services to achieve both productive and environmental outcomes. Although widely implemented in southern Brazil as an annual beef/soybean rotation, tradeoffs such as competing soil water use between pasture and crop phases may result from seasonal grazing in this system. We compared soil water and plant physiological variables in the crop phase of an integrated annual beef-soybean system managed with no-till and best grazing practices with those of an ungrazed cover crop control as part of a long-term experiment in southern Brazil. A mixed black oat (Avena strigosa Schreb.) and Italian ryegrass (Lolium multiflorum Lam.) pasture was either grazed by beef cattle to 20-cm sward height or left as an ungrazed cover crop in the winter, and direct-planted to soybean (Glycine max [L.] Merr.) in the summer. Although soybean yields did not differ between grazed and ungrazed treatments, soil matric potential was on average 25% lower across depths and growth stages in plots that had been grazed during winter. Soybeans in grazed plots also exhibited up to 34% lower light-use efficiency and a 2-week slower time to physiological maturation than soybeans in plots that had not been previously grazed. These results describe for the first time the differential crop growing conditions and crop physiological responses created after 16 years of integration with grazing animals. As integrated crop-livestock systems grow in importance in commercial production settings, this research can inform adaptive management practices to ensure the sustainability of these systems into the future and under a variety of environmental conditions.

Identification of agronomical and morphological traits contributing to drought stress tolerance in soybean

Abiotic stresses, especially drought, may seriously affect soybean yield. Due to the complexity of drought tolerance, one of the difficulties in selecting genotypes is the identification of traits contributing to improve stress tolerance. This study carried out soybean phenotyping under water deficit in vegetative and reproductive stages in field conditions at two consecutive crop seasons (2012/13 and 2013/14). The experiment was performed in Londrina, PR, Brazil, with two soybean cultivars with distinct levels of drought tolerance, BR 16 (sensitive) and Embrapa 48 (less sensitive). Water deficit was applied through rainout shelters, moving on rails to cover plots when the rainfall begins and uncover them when it ends. Then, some agronomic and morphological traits were measured. Multivariate statistics through the principal component analysis (PCA) associated with the biplot graph identified traits contributing to greater yield stability under drought. Result showed that water deficit affected soybean yield, mainly in the reproductive stage, in which Embrapa 48 had greater yield stability when compared to BR 16. However, opposite results were obtained for stress induced in the vegetative stage, when Embrapa 48 was more negatively affected than BR16 cultivar. Seed weight influenced yield differences between cultivars. Lighter seeds, but in larger number, constituted an advantage under water deficit. Due to the difficulty in introducing all drought tolerance mechanisms in one genotype, breeding programs need to define selection parameters according to regional drought conditions.

Field Pennycress Seeding Date and Corn Herbicide Management Effects on Corn, Pennycress, and Soybean Production

Core Ideas Pennycress has potential as an oil and cover crop in upstate Missouri. Pennycress did not reduce yields of corn when interseeded into corn. Pennycress over seeded into R5–R6 corn had the most consistent yields. Pennycress affected the following soybean crop. Field pennycress (Thlaspi arvense L.) has the potential to serve as a cover crop and oilseed crop for biofuels. Field research was conducted from 2014 to 2017 in northern Missouri to evaluate the effect of (i) pennycress seeding date on corn (Zea mays L.) yield; (ii) corn herbicide treatments on pennycress yield; and (iii) pennycress on soybean [Glycine max (L.) Merr.] yield. The experiment was arranged as a split‐plot design with pennycress seeding date as the main plot and residual corn herbicide was the subplot. Pennycress was broadcast overseeded into corn at V4 to V6 and R5 to R6 growth stages, drill seeded after corn harvest, and compared with a non‐seeded control. There were no differences in pennycress test weight, grain moisture, or yield among corn herbicide treatments. Corn yields were high (13.1 to 16.1 Mg ha−1), but there was no effect of field pennycress overseeding date on corn yields within years. Field pennycress yields were greatest when seeded into R5 to R6 corn in 2015 (252 kg ha−1) and 2016 (229 kg ha−1), but no yield differences were observed among seeding dates in 2017. Drill‐seeded pennycress increased soybean yield in 2015 compared with the non‐seeded control, though overall soybean yields were low (705 to 1320 kg ha−1) due to wet conditions. Pennycress did not affect soybean yield in 2016 or 2017 when yields were high (3950 to 4540 kg ha−1). Pennycress could be integrated into a corn–soybean rotation with no detrimental effects on either crop in northern Missouri.

Mapping and Quantifying White Mold in Soybean across South Dakota Using Landsat Images

White Mold of soybeans (Glycine Max), also known as Sclerotinia stem rot (Sclerotinia sclerotiorum), is among the most important fungal diseases that affect soybean yield and represents a recurring annual threat to soybean production in South Dakota. Accurate quantification of white mold in soybean would help understand white mold impact on production; however, this remains a challenge due to a lack of appropriate data at a county and state scales. This study used Landsat images in combination with field-based observations to detect and quantify white mold in the northeastern part of South Dakota. The Random Forest (RF) algorithm was used to classify the soybean and the occurrence of white mold from Landsat images. Results show an estimate of 132 km2, 88 km2, and 190 km2 of white mold extent, representing 31%, 22% and 29% of the total soybean area for Marshall, Codington and Day counties, respectively, in 2017. Compared with ground observations, it was found that soybean and white mold in soybean fields were respectively classified with an overall accuracy of 95% and 99%. These results highlight the utility of freely available remotely sensed satellite images such as Landsat 8 images in estimating diseased crop extents, and suggest that further exploration of consistent high spatial resolution images such as Sentinel, and Rapid-Eye during the growing season will provide more details in the quantification of the diseased soybean.

Diagnosing, Ameliorating, and Monitoring Soil Compaction in No‐Till Brazilian Soils

Core Ideas One‐time tillage increased soybean yield as a result of improving soil physical properties. Penetration resistance, air capacity, macroporosity, relative field capacity, and S index were the soil physical properties that best predicted soybean yield. The most sensitive soil physical properties for detecting structural related alterations were equally important for predicting soybean yield. Penetration resistance is the indicator that addresses no‐tillage soil compaction and its effect on soybean yield. Soil compaction can significantly reduce crop yield. Our objective was to identify the most sensitive soil physical property and process indicators related to crop yield using a Random Forest algorithm (RFA). This machine‐learning, decision‐making tool was used with field‐scale data from five soil management treatments designed to ameliorate compaction in no‐tillage (NT) fields. The treatments were: T1, NT for 10 yr (control); T2, NT with surface application of 3.6 Mg ha−1 of agricultural gypsum; T3, NT with subsoiling plus 1.44 Mg ha−1 of highly reactive limestone applied to a depth of 0.60 m; T4, NT planting following chisel plowing at a depth of 0.26 m; and T5, NT with subsoiling to a depth of 0.60 m plus 1.44 Mg ha−1 of surface‐applied, highly reactive limestone. Fifteen soil physical properties and processes related to growth and yield of soybean [Glycine max (L.) Merr.] were measured. Mechanical intervention, specifically subsoiling, improved soil physical properties and increased soybean yield cultivated following occasional tillage. The RFA ranked penetration resistance (PR), air capacity, macroporosity, relative field capacity, and the Dexter‐S index as the most sensitive soil physical indicators affecting soybean yield. Those indicators were also sensitive to changes in soil structure due to subsoiling. We conclude that the RFA was an effective tool for screening indicators and that those chosen can be effective for monitoring soil compaction and its effect on soybean yield. Penetration resistance may be used to guide on‐farm decision‐making regarding when and how NT soil compaction should be addressed.