R1 Growth Stage Research Articles

Responses of seed yield, quality, and composition to the harvest‐aid paraquat in soybean grown in Mississippi

AbstractParaquat is used as a harvest‐aid to desiccate green tissues for increasing harvest efficiency and maintaining seed quality. However, its application can cause significant crop damage and yield loss if applied too early. Limited information is available on determining the optimum time for applying paraquat. Therefore, the objectives of this study were to investigate the effects of the timing (critical stages of seed‐fill) of paraquat application on soybean seed yield, seed quality (germination, viability, hard‐seed, and seed damage), and seed composition. Field experiments were conducted in 2019 and 2020 at Stoneville, MS. Paraquat was applied at a rate of 0.56 kg a.i. ha–1 at growth stages R6 (full seed‐fill), R6.5 (pod cavities completely filled with seeds), or R7 (yellow color/beginning maturity). Cultivars P46A57BX and P48A60X were used. The results showed that the application of paraquat at R6 or R6.5 resulted in significant yield loss for both cultivars in both years, whereas application at R7 resulted in significant yield loss for P46A57BX in both years, but in only 1 yr for P48A60X. Seed germination and viability were significantly increased over the control in 2020 for both cultivars at all three application stages, but with mixed effects in 2019. No seed damage that would result in dockage was observed in any treatment, as seed damage for all treatments was below 2%. Application of paraquat at R6 resulted in significantly higher seed protein, oleic acid, raffinose, and stachyose but lower oil and sucrose. This research demonstrated that the harvest‐aid paraquat significantly reduced seed yield, increased seed protein, oleic acid, raffinose, and stachyose when applied before growth stage R7. Therefore, producers should use caution when applying paraquat for harvest efficiency before R7, as they will also likely reduce seed yield the earlier paraquat is applied.

Evaluation of Soil Test Phosphorus Extractants and Tissue Analysis for Corn

The objective of this study was to evaluate the relationship of four different soil test phosphorus methods (Mehlich 3, Bray 1, Bray 2, and Haney H3A) for corn production, and determine critical P tissue concentration at different growing stages. The experiment was conducted at 12 locations, and the fertilizer treatments consisted of five phosphorus fertilizer rates applied by broadcast pre-plant. Soil samples were collected at 0- to 6-in. depth, then samples were collected before treatment application by block. Tissue samples were collected at the V6 and R1 growth stages. The relationship between the different soil test phosphorus methods and the R2 varies between 0.24–0.93. Mehlich 3 and Bray 1 have a higher correlation, and Bray 1 and Bray 2 have a lower correlation. Linear plateau determined the critical phosphorus levels for the V6 growth stage was 0.42%, and for the R1 stage was 0.22%. The relationship between the concentration at V6 and R1 was moderately correlated with R2 = 0.62, having a higher phosphorus concentration in the early stage.

Crop damage, economic losses, and the economic damage threshold for northern corn leaf blight

Northern corn leaf blight (NCLB), caused by Exserohilum turcicum (E. turcicum), is one of the most common maize (Zea mays L.) diseases worldwide. To determine the crop damage and economic losses caused by NCLB and propose economic damage thresholds (EDTs), 16 field experiments were performed for seven crop seasons (2010–11 to 2016–17) during different naturally occurring outbreaks of NCLB in central-northern Córdoba province, Argentina. NCLB severity gradients were generated by applying different fungicides and doses at different growth stages to seven susceptible (S) and nine moderately susceptible (MS) hybrids. Plots were arranged in a completely randomized block design with four replications. Severity was evaluated at the R4 growth stage by estimating the percentage of leaves affected; and grain yield in kg ha−1 per plot was also estimated. A critical-point yield model was fitted with NCLB severity and the EDT and the action damage threshold (ADT) were calculated. The management regime generated disease gradients with severities ranging between 3.2 and 33.1. There was a statistically significant negative correlation between severity and yield (R2 = 0.52; p = 0.001). On average, for each percentage point increase, in NCLB severity, 20.15 kg t−1 of yield were lost; MS and S hybrids were 23.88 kg t−1 and 15.21 kg t−1, respectively. The mean EDT was 1.09% of severity and the mean ADT was 0.88%. Furthermore, the mean economic losses were 243.6 USD ha−1 [122.0–353.2]. The generated information can play a role in optimizing the use of fungicides for NCLB control, reducing disease control costs, and protecting the ecological environment of farmlands.

Direct Infusion Metabolomics of the Photosystem and Chlorophyll Related Metabolites within a Drought Tolerant Plant Introduction of Glycine max.

Drought is the most prolific form of abiotic stress that legumes and cereal plants alike can endure, and the planting of an improper cultivar at the beginning of a season can cause unexpected losses up to fifty percent under water deficient conditions. Herein, a plant introduction (PI) of an exotic cultivar of soybean (Glycine max), PI 567731, which demonstrates a slow wilting (SW) canopy phenotype in maturity group III, was profiled under drought conditions in field trials in Missouri against a drought susceptible check cultivar, Pana. Metabolomic profiling was carried out on samples of leaves from each of these cultivars at V5 and R2 growth stages both while irrigated and while under drought stress for three weeks. PI 567731 was observed to have differential phytochemical content, and enhanced levels of chlorophyll (Chl) a/b and pheophytin (Pheo) were profiled by direct infusion electrospray Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). Indicating drought induced changes of the photosystem and photosynthetic capabilities alongside water preservation strategies are important within the SW phenotype drought response. Subsequent multivariate analysis was able to form predictive models, encompassing the variance of growth and drought stress of the cultivar. Moreover, the existence of unique Chl-related metabolites (CRM) (m/z > 900) were confirmed through tandem mass spectrometry. The resultant coordination of fatty acids to the core of the porphyrin ring was observed and played an unknown role in the proliferation of the photosynthesis. However, the relative ratio of the most abundant CRM is undisturbed by drought stress in PI 567731, in contrast to the drought susceptible cultivar. These results provide key insights into drought related metabolic mechanisms.

Critical timing of weed removal in dry bean as influenced by the use of preemergence herbicides

AbstractThe critical timing of weed removal (CTWR) is the point in crop development when weed control must be initiated to prevent crop yield loss due to weed competition. A field study was conducted in 2018 and 2020 near Scottsbluff, NE, to determine how the use of preemergence herbicides affects the CTWR in dry bean. The experiment was arranged as a split plot, with herbicide treatment and weed removal timing as main and sub-plot factors, respectively. Herbicide treatments consisted of no-preemergence application, or pendimethalin (1,070 g ai ha–1) + dimethenamid-P (790 g ai ha–1) applied preemergence. Sub-plot treatments included season-long weed-free, weed removal at: V1, V3, V6, R2, and R5 dry bean growth stages, and a season-long weedy control. A four-parameter logistic model was used to estimate the impact of time of weed removal, for all response variables including dry bean yield, dry bean plants m–1 row, number of pods per plant, number of seeds per pod, and seed weight. The CTWR based on 5% yield reduction was estimated to range from the V1 growth stage [(16 d after emergence (DAE)] to the R1 growth stage (39 DAE) in the no-preemergence herbicide treatment. In the preemergence-applied treatment, the CTWR began at the R2 growth stage (47 DAE). Number of dry bean plants m–1 row was reduced in the no-preemergence treatment when weed removal was delayed beyond the R2 growth stage in the 2020 field season. The use of preemergence herbicides prevented a reduction in the number of pods per plant in 2020, and the number of seeds per pod in 2018 and 2020. In 2018, the number of pods per plant was reduced by 73% when no preemergence herbicide was applied, compared to 26% in the preemergence-applied treatment. The use of preemergence-applied soil-active herbicides in dry bean delayed the CTWR and preserved yield potential.

A Potential Role of Coumestrol in Soybean Leaf Senescence and Its Interaction With Phytohormones.

Coumestrol is a natural organic compound synthesized in soy leaves and functions as a phytoalexin. The coumestrol levels in plants are reported to increase upon insect attack. This study investigates the correlation between coumestrol, senescence, and the effect of phytohormones on the coumestrol levels in soybean leaves. Our analysis involving high-performance liquid chromatography and 2-D gel electrophoresis indicated a significant difference in the biochemical composition of soybean leaves at various young and mature growth stages. Eight chemical compounds were specifically detected in young leaves (V1) only, whereas three different coumestans isotrifoliol, coumestrol, and phaseol were detected only in mature, yellow leaves of the R6 and R7 growth stage. MALDI-TOF-MS analysis was used to identify two proteins 3,9 -dihydroxypterocarpan 6A-monooxygenase (CYP93A1) and isoflavone reductase homolog 2 (IFR2) only in mature leaves, which are key components of the coumestrol biosynthetic pathway. This indicates that senescence in soybean is linked to the accumulation of coumestrol. Following the external application of coumestrol, the detached V1-stage young leaves turned yellow and showed an interesting development of roots at the base of the midrib. Additionally, the application of phytohormones, including SA, methyl jasmonate (MeJA), and ethephon alone and in various combinations induced yellowing within 5 days of the application with a concomitant significant increase in endogenous coumestrol accumulation. This was also accompanied by a significant increase in the expression of genes CYP81E28 (Gm08G089500), CYP81E22 (Gm16G149300), GmIFS1, and GmIFS2. These results indicate that various coumestans, especially coumestrol, accumulate during leaf maturity, or senescence in soybean.

Effect of soil water content changes caused by ridge-furrow plastic film mulching on the root distribution and water use pattern of spring maize in the Loess Plateau

Ridge-furrow plastic film mulching (RFPM) is an efficient planting technique for rainwater harvesting in rainfed regions of the Loess Plateau, China. However, relevant data on root water use patterns under RFPM remain sparse. To clarify the water use pattern of roots under this planting technique and determine the root characteristic parameters related to water absorption, this study conducted a two-year field experiment using spring maize with three treatments: flat planting (FP), and RFPM with two different ridge:furrow ratios (40 cm:70 cm and 70 cm:40 cm). Hydrogen and oxygen stable isotopes (δD and δ18O) of different water sources were measured, and the MixSIAR model was used to quantify the contributions of different water sources to spring maize root water uptake. The results showed that the root characteristic parameters of spring maize under the three treatments decreased with increasing soil depth and were mainly distributed in the shallow (0–20 cm) and middle (20–60 cm) soil layers. Compared to FP, under RFPM the distribution proportions of the root characteristic parameters in shallow soil were higher, which may be related to the increase in shallow soil water content. The main water-absorbing soil layers of spring maize under the three treatments were the same: 0–20 cm, 20–40 cm, 40–60 cm, 40–60 cm, and 0–20 cm in the V6, V12, R1, R3, and R6 growth stages, respectively. However, compared to FP, under RFPM the water use proportion of spring maize of shallow soil increased, especially under the larger ridge to furrow ratio, and correlation analysis showed that this phenomenon might be related to the RFPM increasing the proportion of the spring maize root characteristic parameters in shallow soil. Correlation analysis further showed that the root length density and root surface area density might be the key characteristic parameters for determining root water uptake.

Growth and Yield Losses of Roundup Ready Soybean as Influenced by Micro-rates of 2,4-D

Widespread resistance to glyphosate has made weed control very challenging. In response, new approaches to managing resistant biotypes such as the Enlist E3TM have been developed. This technology allows in-crop use of 2,4-D but there is fear associated with unintentional application of the herbicide (e.g. direct application, tank contamination, or spray drift) to sensitive crops. A study was conducted to evaluate Roundup Ready (RR) soybean growth and yield loss as influenced by 2,4-D [six micro rates of 1/5, 1/10, 1/50, 1/100, 1/500 and 1/1000 of the 1,120 g ae ha-1 label recommended dose, and a check with no herbicide applied] applied at V2, R1 and R2 growth stages. In general, RR soybean was more sensitive to 2,4-D at R1 than V2 and R2. The highest 2,4-D rate, 1/5 of the label recommended rate, caused 51% soybean injury symptom, 13 d canopy closure delay, 41.2% plant height reduction, and 68.9% yield loss at R1. Based on effective dose (ED) estimates, 37.7 g ae ha-1 2,4-D caused 5% yield loss (0.23 Mg ha-1) at R1 compared with a 2.5- and 2.0-fold higher dose at V2 and R2, respectively. With respect to number of days to canopy closure, both reproductive stages (R1 and R2) were equally less sensitive to 2,4-D than the vegetative one (V2) as the plants had already achieved maximum growth recorded. On the other hand, ED estimates for plant height have shown that both V2 and R2 were equally more sensitive to 2,4-D than R1. These results clearly indicated that RR soybean growth and yield loss were significantly influenced by the timing of exposure and amount of 2,4-D.

Impact of imposed root lodging on corn growth and yield

AbstractStrong winds combined with heavy rains can push corn (Zea mays L.) plants over and pull roots part way out of the soil. Weather events that bring these conditions are becoming more frequent in occurrence in the midwestern United States. Yield losses due to root lodging have been related to partial loss of root activity and reduced light interception, but also may stem from affected pollination and kernel fill. A field study was conducted in Ohio from 2018 to 2020 that simulated root lodging from strong winds imposed at V10, V13–14, VT–R1, or R3 growth stages in three modern hybrids. Plants were pushed perpendicular to row direction at the specified stage following natural rain or irrigation events. Differences in hybrids were recorded in this study, but each hybrid exhibited a similar response to lodging (hybrid × lodging interaction was not evident). Yield was reduced by 5, 22, 43, and 33% compared to non‐lodged control at V10, V13–14, VT–R1, and R3, respectively. Light interception in the upper canopy decreased when measured at R4 if lodged previously, and was of greater magnitude as lodging occurred later in the season. Poor pollination contributed to the large yield loss at VT–R1. In addition to reduced yield, increased vivipary and decreased kernel weights in the R3 treatments could further reduce grain quality. These yield losses from this study are greater than have been reported previously, and should be considered when assessing fields for severe wind damage in the future.

Revisiting Biological Nitrogen Fixation Dynamics in Soybeans.

Biological nitrogen (N) fixation is the most relevant process in soybeans (Glycine max L.) to satisfy plant N demand and sustain seed protein formation. Past studies describing N fixation for field-grown soybeans mainly focused on a single point time measurement (mainly toward the end of the season) and on the partial N budget (fixed-N minus seed N removal), overlooking the seasonal pattern of this process. Therefore, this study synthesized field datasets involving multiple temporal measurements during the crop growing season to characterize N fixation dynamics using both fixed-N (kg ha−1) and N derived from the atmosphere [Ndfa (%)] to define: (i) time to the maximum rate of N fixation (β2), (ii) time to the maximum Ndfa (α2), and (iii) the cumulative fixed-N. The main outcomes of this study are that (1) the maximum rate of N fixation was around the beginning of pod formation (R3 stage), (2) time to the maximum Ndfa (%) was after full pod formation (R4), and (3) cumulative fixation was positively associated with the seasonal vapor-pressure deficit (VPD) and growth cycle length but negatively associated with soil clay content, and (4) time to the maximum N fixation rate (β2) was positively impacted by season length and negatively impacted by high temperatures during vegetative growth (but positively for VPD, during the same period). Overall, variation in the timing of the maximum rate of N fixation occurred within a much narrower range of growth stages (R3) than the timing of the maximum Ndfa (%), which varied broadly from flowering (R1) to seed filing (R5–R6) depending on the evaluated studies. From a phenotyping standpoint, N fixation determinations after the R4 growth stage would most likely permit capturing both maximum fixed-N rate and maximum Ndfa (%). Further investigations that more closely screen the interplay between N fixation with soil-plant-environment factors should be pursued.

Evaluating the Spectral Response and Yield of Soybean Following Exposure to Sublethal Rates of 2,4-D and Dicamba at Vegetative and Reproductive Growth Stages

The commercialization of synthetic auxin-resistant crops and the commensurate increase in post-emergent auxin-mimic herbicide applications has resulted in millions of hectares of injury to sensitive soybeans in the United States since 2016. Visual yield loss estimations following auxin injury can be difficult. The goal of this research was to determine if spectral variations following auxin injury to soybean allow for more precise yield loss estimations. Identical field experiments were performed in 2018, 2019, and 2020 in Columbia, Missouri to compare the ability of established vegetative indices to differentiate between exposure levels of 2,4-D and dicamba in soybean and predict yield loss. Soybeans were planted at three timings for growth stage separation and were exposed to sublethal rates of 2,4-D and dicamba at the R2, R1, and V3 growth stages. A UAV-mounted multispectral sensor was flown over the trial 14 days after the herbicide treatments. The results of this research found that vegetative indices incorporating the red-edge wavelength were more consistent in estimating yield loss than indices comprised of only visible or NIR wavelengths. Yield loss estimations became difficult when soybean injury occurred during later reproductive stages when soybean biomass was increased. This research also determined that when injury occurs to soybean in vegetative growth stages late in the growing season there is a greater likelihood for yield loss to occur due to decreased time for recovery. The results of this research could provide direction for more objective and accurate evaluations of yield loss following synthetic auxin injury than what is currently available.

Dynamics of Microbial Biomass, Nitrogen Mineralization and Crop Uptake in Response to Placement of Maize Residue Returned to Chinese Mollisols over the Maize Growing Season

Returning residue to soils is not only an effective nutrient management method, but also can reduce the air pollution caused by residue burning, which has become an important factor in global warming. However, it is not clear whether returning residue to the soil can affect the nitrogen mineralization and the nitrogen cycle process, and the environmental impact caused by the nitrogen loss in gaseous forms. Therefore, a pot experiment was conducted to study the effects of residue placement on the nitrogen turnover process, including microbial biomass N (MBN) and C (MBC), inorganic N, crop N uptake, and the contribution of residue-derived N to maize at different maize growth stages. Three treatments were assessed: no residue addition (T0), residue addition to the soil surface (T1), and residue incorporation into the 0–10 cm soil layer (T2). Soil samples were taken at the 0–5 and 5–10 cm layers for all residue treatments. Residue retention (T1 and T2) significantly affected the MBC and MBN contents and decreased MBC/MBN ratio at different maize growth stages. MBC/MBN markedly increased at the R1 stage compared to other growth stages. The differences in total inorganic nitrogen (TIN) were attributed to the balance in net N immobilization and net mineralization in the different maize growth stages. In addition, T2 significantly increased the residue-derived N source for maize by 11.3% compared to T0 in the R3 growth stage. Overall, relative to T1, T2 is a better agriculture management measure to promote N transformation and supply, and enhance residue-derived N release and uptake in maize.

Physical and chemical properties of edamame during bean development and application of spectroscopy-based machine learning methods to predict optimal harvest time

This study aims to investigate the changes in physical and chemical properties of edamame during bean development and apply a spectroscopy-based machine learning (ML) technique to determine optimal harvest time. The edamame harvested at R5 (beginning seed), R6 (full seed), and R7 (beginning maturity) growth stages were characterized for physical and chemical properties, and pods were measured for spectral reflectance (360–740 nm) using a handheld spectrophotometer. The samples were categorized into ‘early’, ‘ready’, and ‘late’ based on the characterized properties. The results showed that pod/bean weight and pod thickness peaked at R6 and remained stable thereafter. Sugar, starch, alanine, and glycine also peaked at R6 but proceeded to decline. The ML method (random forest classification) using pods’ spectral reflectance had a high accuracy of 0.95 for classifying ‘early’ and ‘late’ samples and 0.87 for classifying ‘early’ and ‘ready’ samples. Therefore, this method can determine the optimal harvest time of edamame.

Large-scale evaluation of 2,4-D choline off-target movement and injury in 2,4-D-susceptible soybean

AbstractEnlist E3TM soybean cultivars permit over-the-top application of labeled glyphosate, glufosinate, and 2,4-D choline products. Increased Enlist E3TM trait adoption and use of 2,4-D choline postemergence across U.S. soybean production systems raise concerns regarding potential for 2,4-D off-target movement (OTM). A large-scale drift experiment was established near Sun Prairie, WI, and Arlington, WI, in 2019 and 2020, respectively. A 2,4-D-resistant soybean cultivar was planted in the center of the field (∼3 ha), while the surrounding area was planted with a 2,4-D-susceptible cultivar. An application of 785 ae ha−1 2,4-D choline plus 834 g ae ha−1 glyphosate was completed within the center block at R2 and V6 growth stages on August 1, 2019, and July 3, 2020, respectively. Filter papers were placed in-swath and outside of the treated area in one upwind transect and three downwind transects to estimate particle deposition. Low-volume air samplers ran for the 0.5-h to 48-h period following application to estimate 2,4-D air concentration. Injury to 2,4-D-susceptible soybean was assessed 21 d after treatment (0% to 100% injury). The 2,4-D deposition in-swath was 9,966 and 5,727 ng cm−2 in 2019 and 2020, respectively. Three-parameter log-logistic models estimated the distance to 90% reduction in 2,4-D deposition (D90) to be 0.63 m and 0.90 m in 2019 and 2020, respectively. In 2020, the 2,4-D air concentration detected was lower for the upwind (0.395 ng m−3) than the downwind direction (1.34 ng m−3), although both were lower than the amount detected in-swath (4.01 ng m−3). No soybean injury was observed in the downwind or upwind directions. Our results suggest that 2,4-D choline applications following label recommendations pose little risk to 2,4-D-susceptible soybean cultivars; however, further work is needed to understand 2,4-D choline OTM under different environmental conditions and the presence of other susceptible crops.

Dicamba-Tolerant Soybean Response to 2,4-D Micro-Rates at Three Growth Stages Dicamba-Tolerant Soybean Response to 2,4-D Micro-Rates at Three Growth Stages

While dicamba and 2,4-D belong to the same herbicide group, dicamba- and 2,4-D-tolerant soybeans are not cross-resistant. A study was conducted to investigate dicamba-tolerant (DT) soybean response to 2,4-D micro-rates at three growth stages. The study used a randomized complete block design with six replications and a split-plot treatment arrangement. Main plots consisted of three 2,4-D application times [second trifoliate (V2); beginning of flowering (R1); and full flowering (R2)] and subplots consisted of six 2,4-D micro-rates (1/5; 1/10; 1/50; 1/100; 1/500; and 1/1,000 of the label recommended dose of 1,120 g ae ha-1) and a check with no herbicide applied. DT soybean injury symptoms were assessed at 7, 14 and 21 days after treatment (DAT). Yield components, grain yield and yield loss were estimated. The greatest soybean injury (59%) at 21 DAT, delay in canopy closure (16.8 d), and reduction in number of branches plant-1 (52%), pods plant-1 (38%) and 100 seed weight (16%) which ultimately resulted in yield loss (78%) was caused by 1/5 of the label recommended dose of 2,4-D (214 g ae ha-1) at R1 growth stage. Based on effective dose (ED) estimates, 8.66 g ae ha-1 2,4-D caused 0.22 Mg ha-1 (5%) yield loss in DT soybean at R1 but a 1.34- and 2.11-fold higher dose of the same herbicide was required to cause equal yield loss at R2 and V2 growth stages, respectively. Similarly, the number of branches plant-1, pods plant-1 and flowers plant-1 were more sensitive to 2,4-D at R1 than V2 and R2 growth stages with the latter being the most sensitive yield component. On the other hand, 100 seed weight was 3.1- and 4.5-fold more sensitive to 2,4-D at R2 than R1 and V2 growth stages, respectively. Overall, these results showed that DT soybean is most sensitivity to 2,4-D at R1.

Using Hybrid Artificial Intelligence and Evolutionary Optimization Algorithms for Estimating Soybean Yield and Fresh Biomass Using Hyperspectral Vegetation Indices

Recent advanced high-throughput field phenotyping combined with sophisticated big data analysis methods have provided plant breeders with unprecedented tools for a better prediction of important agronomic traits, such as yield and fresh biomass (FBIO), at early growth stages. This study aimed to demonstrate the potential use of 35 selected hyperspectral vegetation indices (HVI), collected at the R5 growth stage, for predicting soybean seed yield and FBIO. Two artificial intelligence algorithms, ensemble-bagging (EB) and deep neural network (DNN), were used to predict soybean seed yield and FBIO using HVI. Considering HVI as input variables, the coefficients of determination (R2) of 0.76 and 0.77 for yield and 0.91 and 0.89 for FBIO were obtained using DNN and EB, respectively. In this study, we also used hybrid DNN-SPEA2 to estimate the optimum HVI values in soybeans with maximized yield and FBIO productions. In addition, to identify the most informative HVI in predicting yield and FBIO, the feature recursive elimination wrapper method was used and the top ranking HVI were determined to be associated with red, 670 nm and near-infrared, 800 nm, regions. Overall, this study introduced hybrid DNN-SPEA2 as a robust mathematical tool for optimizing and using informative HVI for estimating soybean seed yield and FBIO at early growth stages, which can be employed by soybean breeders for discriminating superior genotypes in large breeding populations.

Optimizing nitrogen supply promotes biomass, physiological characteristics and yield components of soybean (Glycine max L. Merr.).

Avoidable or inappropriate nitrogen (N) fertilizer rates harmfully affect the yield production and ecological value. Therefore, the aims of this study were to optimize the rate and timings of N fertilizer to maximize yield components and photosynthetic parameter of soybean. This field experiment consists of five fertilizer N rates: 0, 75, 150, 225 and 300 kg N ha−1 arranged in main plots and four N fertilization timings: V5 (trifoliate leaf), R2 (full flowering stage) and R4 (full poding stage), and R6 (full seeding stage) growth stages organized as subplots. Results revealed that 225 kg N ha−1 significantly enhanced grain yield components, total chlorophyll (Chl), photosynthetic rate (PN), and total dry biomass and N accumulation by 20%, 16%, 28%, 7% and 12% at R4 stage of soybean. However, stomatal conductance (gs), leaf area index (LAI), intercellular CO2 concentration (Ci) and transpiration rate (E) were increased by 12%, 88%, 10%, 18% at R6 stage under 225 kg N ha−1. Grain yield was significantly associated with photosynthetic characteristics of soybean. In conclusion, the amount of nitrogen 225 kg ha−1 at R4 and R6 stages effectively promoted the yield components and photosynthetic characteristics of soybean.

Impact of Wheat on Soybean Cyst Nematode Population Density in Double-Cropping Soybean Production.

Double-cropping is defined as producing more than one crop on the same parcel of land in a single growing season. It is reported to have many benefits when incorporated in cropping systems, including improving soil health. In some double-cropping systems, soybean is planted following winter wheat. The soybean cyst nematode (SCN) (Heterodera glycines Ichinohe) is a major soybean pathogen, and several reports suggest suppressive effects of wheat on SCN populations. Field trials were conducted from 2017 to 2018 to investigate the effect of wheat on SCN populations in double-cropping soybean. Nine fields with three levels of initial SCN populations (low, moderate, and high) were selected in Illinois. Wheat was planted in strips alternating with strips-maintained weed-free and under fallow over winter and early spring. Soybean was planted in all strips after wheat harvest. SCN egg densities were acquired at four time points: wheat establishment, post-wheat/pre-soybean, mid-soybean (R1 growth stage or beginning of flowering), and post-soybean harvest. Wheat strips reduced SCN egg densities compared with fallow strips at the R1 stage (−31.8%) and after soybean harvest (−32.7%). Double-cropping soybean with wheat has the potential to suppress SCN field populations and is a system with the potential to provide additional farm income. This study is meant to be a first step toward a better understanding of the mechanisms that govern the suppression of SCN by wheat.

DÉFICIT HÍDRICO EN MAÍZ AL CONSIDERAR FENOLOGÍA, EFECTO EN RENDIMIENTO Y EFICIENCIA EN EL USO DEL AGUA

La presencia de períodos de disponibilidad hídrica baja y las eficiencias de riego bajas obligan a los distritos de riego (DR) a implementar acciones como la reducción de la superficie cultivada y el número de riegos de los cultivos. Esto, causa en muchos casos, impactos negativos en rendimiento al no aplicarse en forma científica. El objetivo de esta investigación fue evaluar de manera experimental el efecto del estrés hídrico a partir de la fenología, en los componentes del rendimiento y en el uso eficiente del agua del cultivo de maíz (Zea mays L.). El experimento se realizó en el distrito de riego DR-075, durante el ciclo otoño-invierno (OI) 2012-2013 y se evaluaron cuatro tratamientos (T) de déficit hídrico y un testigo (TES) diseñados a partir de la función FAO que relaciona el déficit hídrico con el rendimiento. T1 recibió dos riegos de auxilio (RA) distribuidos en las etapas V12 y R2; T2 recibió tres RA distribuidos en V9, R1 y R3; T3 recibió cuatro en V7, V12, R1 y R3-R4. T4 cinco RA en V5, V12, R1, R3 y R4. El TES recibió cuatro RA distribuidos igual que T3, pero aplicados en forma convencional. Las variables evaluadas fueron: eficiencia de aplicación (EA), materia fresca (MF), materia seca (MS), rendimiento de grano (Ya), índice cosecha (IC) y productividad del agua (PA). El seguimiento de riegos y fenología se realizó con la plataforma informática IRRIMODEL complementada con observaciones de campo; el monitoreo de la humedad del suelo se realizó con un sensor portátil tipo TDR. Los resultados proporcionaron información científica para manejar el riego del cultivo de maíz considerando fenología, bajo condiciones normales y de disponibilidad hídrica restringida. En el primer escenario se debe evitar el quinto riego de auxilio y en el segundo, utilizar el calendario de tres auxilios (T2) para obtener eficiencias de aplicación iguales o mayores a 64%.

Plant growth stage and leaf part to diagnose sweet corn nitrogen status using chlorophyll sensor and scanner image analysis

The application and use of image analysis to assess the plant nitrogen (N) status has gained importance especially in precision agriculture for cereal plants using aerial remote sensing or even ground-based commercial N sensors. The objective of this work was to propose the plant growth stage and leaf parts possible to be used in sweet corn plant for N diagnosis using the SPAD chlorophyll meter and a table scanner images. A field experiment was carried out at the Federal University of Viçosa. A randomized block design was used, in a 4x3x5 factorial scheme (growth stages x leaf parts x N doses), with five replications. SPAD reading and scanner images were obtained for Red, Green and Blue (RGB) were obtained using the ImageJ® software. The data were submitted to analysis of variance and Pearson's correlation analysis at a 5% probability. Reading position on the middle part of the leaf at V10 and at R1 growth stages are suitable for assessing sweet corn N status using SPAD with 51.40 and 45.09 as an optimal reference value, respectively. RGB values determined with the scanner also was suitable for assessing the N status of sweet corn. The technique does not require special expertise for its application. It is proposed table containing optimal reference values of SPAD and RGB colors in the medial part of the sweet corn leaf at V10 and R1 development stages of corn plant.