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Article

Optimizing Seeding Ratio for Semi-Leafless and Leafed Pea Mixture with Precise UAV Quantification of Crop Lodging

by
Yanben Shen
1,
Lena D. Syrovy
2,
Eric N. Johnson
3,
Thomas D. Warkentin
3,4,
Thuan Ha
3,
Devini de Silva
4 and
Steven J. Shirtliffe
3,*
1
Department of Agronomy, College of Agriculture and Life Sciences, Iowa State University, Ames, IA 50011, USA
2
Department of Soil Science, College of Agriculture and Bioresources, University of Saskatchewan, Saskatoon, SK S7N 5E5, Canada
3
Department of Plant Science, College of Agriculture and Bioresources, University of Saskatchewan, Saskatoon, SK S7N 5E5, Canada
4
Crop Development Center, University of Saskatchewan, Saskatoon, SK S7N 5E5, Canada
*
Author to whom correspondence should be addressed.
Agronomy 2022, 12(7), 1532; https://doi.org/10.3390/agronomy12071532
Submission received: 25 May 2022 / Revised: 22 June 2022 / Accepted: 24 June 2022 / Published: 26 June 2022
(This article belongs to the Special Issue Mixed Cropping—a Low Input Agronomic Approach to Sustainability)
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Abstract

:
The field pea has both semi-leafless (SL) and leafed (L) types. Mixing these two types together might improve yield by optimizing pea solar radiation interception, reducing lodging, and decreasing disease. However, an optimum mixing ratio has not yet been established, since previous studies mixed two leaf types from two separate varieties. This study used four near-isogenic pairs of pea genotypes differing only in leaf type to determine the optimal mixing ratio for yield and agronomic traits. Two leaf types were mixed at seeding in five mixing ratios: 0:100, 50:50, 67:33, 83:17, and 100:0 SL/L. With precise UAV quantification of canopy height (r2 = 0.88, RMSE = 2.6 cm), the results showed that a ratio of over 67% semi-leafless pea had a 10% greater lodging resistance when compared to the leafed monoculture. For mycosphaerella blight and Uromyce viciae-fabae rust diseases, the 83:17 mixture decreased disease severity by 4% when compared with the leafed monoculture. Regression analysis of yield estimated that the 86:14 ratio provided an 11% increase to the leafed monoculture, but there was no increase compared with the semi-leafless monoculture. Mixing the two types in a high semi-leafless ratio can reduce leafed lodging and prevent yield loss but does not increase the overall yield over the semi-leafless monoculture.

1. Introduction

Canada is the world’s field pea (Pisum sativum L.) production and export leader, with a production of 4.6 million tonnes in 2020 [1]. Of the 4.6 million exported tonnes in 2020, Saskatchewan accounted for 54.4% of production or 2.48 million tonnes [1]. Field pea is a crop that can take advantage of the growing plant protein market due to its relatively high protein content of 21.3–24.7% [2]. Besides its significant profit potential, the spring-sown field pea is well suited for rotation with canola and wheat for nitrogen fixation, interruption of disease and insect life cycles, microbial biodiversity, and many other sustainable benefits [3].
The semi-leafless (SL) and leafed (L) peas are the same species but differ in leaf structure. In the leafed pea, the leaf consists of a stipule, leaflets, and tendrils, whereas the semi-leafless pea leaf consists of only a stipule and tendrils. This modified leaf structure causes them to differ in field characteristics. The leafed leaflet leads to a greater leaf area than the semi-leafless tendrils at the vegetation stage, which provides suppression of inter-row weeds and greater canopy radiation interception [4,5,6]. Moreover, the leafed type has greater green area index, extended green area duration and maintains a high growth rate than the semi-leafless type [7]. In comparison, the semi-leafless type improves the lodging resistance of plants and has greater disease resistance than the leafed pea [8,9]. Tran et al. [10] found that the semi-leafless genotype had a 51% higher seed yield compared to the leafed genotypes. On the basis of their agronomic advantages, semi-leafless peas have replaced leafed peas for food production in Western Canada.
The field pea stem has a weak base, and the pod filling on the shoots leads to a higher lodging risk mid-way and late in the season, so lodging resistance is necessary for pea yield. A mixture of semi-leafless and leafed plants reduces lodging and disease severity for the leafed monoculture, while improving weed competition in comparison to sole-grown leaf types. The photosynthetic activity of plants may be reached optimally with the leaf mixtures. Leafed leaflets intercept light in the upper canopy, and semi-leafless tendrils intercept the penetrated light in the lower plants. Schouls and Langelaan [11] first mixed leafed peas with semi-leafless peas at seeding and reported a lodging resistance improvement and higher yield from the mixture when compared to pure leafed stands. In Western Canada, mixing ratios of 25:75, 50:50, and 75:25 (semi-leafless/leafed) were compared in organic cropping for weed control [12]. The study reported that the 50:50 mixture reduced weed biomass by 19% when compared to a semi-leafless monoculture. Moreover, the 75:25 leaf mixture produced 18% and 156% higher yield than the pure semi-leafless and pure leafed stand, respectively [12].
Plant height is strongly correlated with lodging susceptibility in field pea [13]. Unoccupied aerial vehicles (UAV) and image analysis enables agricultural scientists to use high-resolution cameras to capture, process, and measure the physiological feature of plants and replace tedious, time-consuming data collection and visual ratings [14]. Canopy height can be estimated by the crop elevation model, and lodging severity can be derived from the height variation. Previous studies successfully used RGB, multispectral, hyperspectral, and Lidar camera in UAV-imaging to measure crop height [15,16,17,18,19]. Previous studies have shown that canopy heights derived from UAV images had a strong correlation (r2 > 0.9) with the ground measurements [20,21]. As such, it should be possible to assess lodging severity by computing a time series of canopy height from UAV flights, whereby determining the most lodging resistant mixture.
Mixing semi-leafless and leafed peas in different ratios affects lodging and disease severity. Increasing leafed pea percentages linearly increased lodging when compared to the semi-leafless pea [12]. The mixing ratio affects yield because yield is dependent on lodging in peas. Leaf mixture in five ratios, 0:100, 25:75, 50:50, 75:25, and 100:0 SL/L, were compared in terms of yield and land equivalent ratio (LER) [22]. The 75:25 mixture had a greater yield than other mixtures, with 1.18 LER. LER is an index that describes the relative land area required under monoculture to obtain the same yield as under an intercrop [23]. Schouls and Langelaan [11] recommended that the optimal semi-leafless percentage was 53–67% for the leaf type mixture. Based on the previous information, the optimal ratio may range from a 50% or higher semi-leafless ratio where the semi-leafless crop is the supporting crop and the leafed crop is the supported crop. However, because all previous individual studies mixed two different varieties with varying yield potential, lodging resistance, and vine length, a mixing ratio has not to be determined.
Utilizing blends of near isogenic lines (NIL) could minimize the effect of the genotype. Previous studies compared the semi-leafless and leafless types with the leafed type in a series of NIL to evaluate yield trait and photosynthetic potential with respect to leaf area and morphology [4,24,25]. In the current study, an AFILA allele (AF), which controls leaflet development, was introgressed into a semi-leafless variety. The progenies were selected for the leafed phenotype and repeatedly crossed with the semi-leafless parent. The objective of this study was to determine an optimal ratio of near-isogenic semi-leafless and leafed mixture to optimize pea disease resistance, lodging resistance, and yield.

2. Materials and Methods

2.1. Site Description

This study was conducted at the University of Saskatchewan Kernen Research Farm, Canada (latitude 52°09′, longitude 106°32′) in 2017 (1 site), 2018 (2 sites), and 2019 (3 sites), and the Rural Municipality of Blucher in 2019 (1 site). All sites are located on a Sutherland series clay loam soil (Bradwell Dark Brown Chernozem; 10% sand, 40% silt, 50% clay) and the pre-seeding soil test report is described in Table A1.

2.2. Plant Materials

The leafed NILs were bred by crossing four semi-leafless parental lines with a leafed variety (CDC Sonata) to introgress the AF allele into their progenies using a backcrossing method (De Silva and Warkentin). In the F1 generation, the leafed progenies were phenotypically selected and backcrossed with the related semi-leafless parent to reduce the proportion of the leafed genome. After five generations, the leafed near-isogenic line expressed in relatively homozygous backgrounds genetically resembled their related semi-leafless variety with the AF allele; it was 96.875% similar to the semi-leafless parent line. The semi-leafless varieties in this experiment were all bred by the Crop Development Centre (CDC) in Saskatoon (Table 1).

2.3. Experimental Design and Management

The experiment was a two-way factorial design evaluating ratio and variety (Table 2). The proportions of the semi-leafless pea were higher than the leafed pea because mixtures of over 50% semi-leafless types were targeted to transfer the semi-leafless lodging resistance to the leafed pea [12,22]. The field layout was an alpha lattice design with four replicates.
Pea was seeded in early May at a target density of 88 plants m−2 in 1.8 m × 3 m plots consisting of 6 rows, 30 cm apart. Seed of the leafed and semi-leafless peas was mixed prior to planting and seeded using a cone plot seeder. TagTeam® granular inoculant (Penicillium bilaii and Rhizobium leguminosarum) (Novozymes North America Inc., Franklinton, NC, USA) was applied to the seed at a rate of 4.6 kg ha−1. Monoammonium phosphate (NH4H2PO4) was also applied to the seed to supply 16.5 kg ha−1 P2O5 and 3.85 kg ha−1 N, based on the soil report and recommended fertilization [26]. The site was managed similar to a commercial farm. Plots were treated with Odyssey® herbicide (imazamox 35% a.e. + imazethapyr 35% a.e.) (BASF Canada Inc., Mississauga, ON, Canada) for weed control using a rate of 30 g ai ha−1 at the V3 stage following Knott’s [27] field pea growth scale. The plots were desiccated with Reglone® Ion (Diquat ion 20% a.e.)(Syngenta Canada Inc., Guelph, ON, Canada) at the full maturity (R7 stage).

2.4. Data Collection

2.4.1. Seed Germination

Population density was measured three weeks after crop emergence by counting plants in 1 m−2 quadrats. Measurements were taken in both the front and back of each plot, 50 cm from the front plot edge and covering central 3 plant rows, to evaluate the evenness of seed emergence.

2.4.2. Light Interception

Light interceptions were collected weekly from the early vegetative (V6) to the reproductive stages (R1) [28]. The measurements were conducted at solar noon using two sensors. Under the canopy, a LI-191R Line Quantum Sensor (LI-COR Inc., Lincoln, NE, USA) was inserted into the center two rows perpendicular to the row direction and measured photosynthetically active radiation (PAR; μmol s−1 m−2) integrated over a length of 1 m. Above the canopy, a LI-200R Pyranometer (LI-COR Inc., Lincoln, NE, USA) simultaneously measured the PAR above the canopy. The canopy intercepted PAR rate is the PAR below canopy divided by the real-time PAR above canopy. The rate of light interception was calculated using the following formula:
Intercepted PAR = 1 − (PAR below canopy/PAR above canopy)

2.4.3. Disease Severity

In this study, Mycosphaerella blight and Uromyce viciae-fabae rust were the major diseases in 2018, and Mycosphaerella blight and Aphanomyces root rot were observed at the sites in 2019. Disease severity was visually rated at the pod filling stage (R4 stage) and at the time, Aphanomyces root rot symptom was not observed. The percentage of Mycosphaerella blight and U. viciae-fabae rust was inspected on five random plants by rating the progression of disease symptoms up the stems and leaves with an incremental scale [29].

2.4.4. Plant Height Measured Manually

Ground measurement of plant height was measured at the stage of podding and beginning of maturity (R4 or R5 stage). Canopy height and plant length were measured on five random plants in each plot with a meter stick.

2.4.5. Height Reduction Estimated from UAV Images

Image Acquisition

Ground Control Points (GCP) were installed prior to trial planting on bare ground in each corner of the experimental area to represent zero height. The geolocation of each GCP was determined using a real-time kinetic (RTK) GPS. The DJI Matrix 600 platform was used to acquire aerial images, with the MicaSense Red-Edge camera in 2018 and the Hi-Phen camera in 2019. The images were collected at a height of 20 m with a 75% overlap for the experimental plots. Since pea lodging usually occurs after the R4 or R5 stages, the weekly UAV flights began from 56 days after seeding (DAS) to 91 DAS (Table A2). Height reduction was measured in four site-years (site-year is a term that describes the environmental interaction of location and year) because the UAV imagery was limited to one of two sites in 2018.

Preprocessing

The multispectral images were pre-processed with Pix4D software (Pix4D S.A. Switzerland), which matched the GCP and calibrated the overlaps to create a stitched orthomosaic map and a 2D-view digital elevation map (DEM) using structure from motion photogrammetry software processing the captured point clouds. The spatial resolution for DEM and orthomosaic was 2.96 cm/pixel.

Processing

Feature annotation was used to classify each pea plot and the adjacent soil surface in each plot with the plot ID, and all polygons were grouped into a vector layer. The normalized difference vegetation index (NDVI) and the green normalized difference vegetation index (GNDVI), chosen from the literature, were selected to threshold the vegetation material [30,31]:
NDVI = (NIR − Red)/(NIR + Red)
GNDVI = (NIR − Green)/(NIR + Green)
Given the source of the vegetative index thresholds, DEM, and polygons, the model automatically derived all individual dates of canopy height model (CHM) throughout the season (Figure 1). The canopy heights were by estimating the difference of elevation of plants and soil surface, following [18,21,32].
Measures of the canopy height model at multiple dates were derived. The percentage of height reduction was calculated using the maximum heights in the peak and the minimum heights in the post-lodging utilizing the following equation:
Height Reduction% = (Maximum CHM − Minimum CHM)/Maximum CHM × 100

2.4.6. Productivity

Crop biomass was collected when the peas were approaching maturity (R7 stage). Above-ground plant material was sampled in 0.25 m−2 quadrats, 50 cm from the edge in both the front and back of each plot. The collected samples were dried in an oven at 70 °C for 48 h to obtain dry biomass weight. Seed yield was obtained with a plot combine following desiccation when pod moisture was below 30%. The harvested seed was dried with forced air for 48 h to obtain an equilibrium moisture. The seed was cleaned and weighed.

2.5. Statistical Analysis

The coefficient of variation (CV) was calculated in the pre-analysis to ensure the consistency of the measurements for all response variables (Table A3). Response variables with a CV value < 30% is acceptable for agricultural research [33]. Data were tested for homogeneity of variances prior to analysis using the Levene’s test in the general linear model procedure. The variance of site-year was heterogeneous for all variable responses, except for disease severity. Data were analyzed with analysis of variance (ANOVA) using the MIXED model in SAS 9.4 version (SAS Institute Inc., Cary, NC, USA).
The UAV-developed height was assessed for accuracy by year with 320 plot results. The data from the 2019 sites (240 plots) and 2018 sites (80 plots) were the training and validation datasets, respectively. Measured heights and image derived CHM from the same day in 2019 were analyzed using a linear regression model equation with CHM and measured height as the y and x variables. The CHM in 2018 was then imported into the equation to predict measured heights. The predicted heights were compared with the actual heights using the root mean square error (RMSE) and coefficient of determination (r2).
To compare the mixing ratios, variety, and their interaction, they were analyzed as fixed effects whereas replication nested in site-year, block nested in replication, site-year, and the interaction of site and year with fixed factors were assigned as random effects in height reduction, disease severity, crop biomass, and crop yield. Repeated measures of light interception, days after seeding (date), mixing ratios, variety, and their interaction were analyzed as fixed effects. REPEATED statements in the MIXED analysis were used for spatial variability and to adjust for heterogeneity of variance [34]. To measure the spatial variability, the position of each plot was converted to a matrix by inputting east and north locations of each plot in the site. The exponential covariance structure was used to model the matrix for spatial variation [35]. The group = option adjusted the site-year covariance. Treatment means were separated using least significant difference (LSD) test. Treatment effects were declared significant at p < 0.05; however, some trends are reported at p < 0.1.

3. Results

3.1. Climate and Growing Conditions

The climate varied throughout the three growing seasons (Table 3). In June and July 2019, an adequate total precipitation was recorded to facilitate pea growth and yield. In comparison, drought occurred in 2017 and 2018, in which the total precipitation was less than half the amount in 2019. The germination rate of each variety was over 75% and no significant difference was found between treatments.

3.2. Light Interception

There was a significant date-by-variety interaction (Table 4) as varieties differed considerably in their rate of canopy closure. The interaction of light interception was described by a quadratic polynomial regression model (Figure 2). The CDC Striker canopy initially had a greater light interception than all other varieties, and this trend continued to be greater than CDC Dakota and CDC Centennial. CDC Amarillo canopy development was similar to CDC Dakota in the early stages but approached CDC Striker later in the season. CDC Dakota had a slightly higher PAR than CDC Centennial early in the growing season; however, that trend reversed as the season progressed.

3.3. Disease Severity

Mycosphaerella blight and pea rust (Uromyce viciae-fabae) symptoms were observed in 2018, whereas mycosphaerella blight and aphanomyces root rot symptoms were observed in 2019. The difference between the mean disease severity of the mixing ratio trended to be significant (Table 4). Three leaf-type mixtures had relatively low disease severities, developing a 4% lower infection than the leafed monoculture (Figure 3).

3.4. Height Reduction by Lodging in Pea

Comparing canopy heights taken on the same day by image-derived and ground measurements from the 2018 trial showed the image estimation to be r2 = 0.88 (Figure 4a). The RMSE found the difference between the two measurements to be 2.6 cm. The plant length estimations (Figure 4b) also found that applying the maximum CHM over the season positively correlated with plant length (r2 = 0.81, RMSE = 4.63 cm). These results demonstrate that crop heights can be extracted from UAV images, and CHM can represent canopy height when evaluating lodging severity. Furthermore, the maximum CHM was applied to predict the pea yield. The yield prediction showed a good correlation with yield (r2 = 0.506, RMSE = 160 kg/ha) and could be a secondary trait for yield prediction.
The image canopy heights were extracted in each imaged flight in each site-year (Figure A1). The study analyzed the percentage of height reduction and reported significant variety and mixing ratio effects (Table 4). The height reduction by the interaction of variety and ratio effects showed that the semi-leafless proportion increase had a lower reduction in canopy height in all varieties. In addition, the semi-leafless monoculture had the lowest height reduction than the leaf-type mixtures and the leafed monocultures. On the basis of the consistent results of height reduction among varieties, the current study combined the varieties’ results. The height reduction showed that the semi-leafless proportion of over 83% was significantly lower than the semi-leafless proportion of below 50% (Figure 5).

3.5. Biomass

The interaction between the ratio and variety tested significantly affected biomass weight (Table 4). In CDC Centennial, the leafed monoculture produced an 11% lower biomass than the semi-leafless monoculture and the mixture of 67:33 SL/L. There was no difference in biomass among the mixtures or between the leaf types within all other varieties (Figure 6).

3.6. Seed Yield

There was an interaction of variety and ratio for seed yield (Table 4). The leafed monoculture had a significantly lower yield than all mixtures and the semi-leafless monoculture for CDC Amarillo, CDC Centennial, and CDC Striker. Moreover, CDC Amarillo and CDC Dakota had a significantly greater yield than CDC Striker in the leafed monoculture. Maximum yield is a critical feature for optimal leaf mixture; however, the ratios having the highest yield varied with variety. The 67:33 SL/L ratio in CDC Centennial optimized yield. Meanwhile, the 50:50 SL/L ratio in CDC Dakota, the 83:17 SL/L ratio in CDC Amarillo, and the 100:0 SL/L ratio in CDC Striker resulted in the highest yield (Figure 7). Therefore, the yield potential of leaf-type mixture is affected by genotype backgrounds. The combined yield results of four varieties showed that the mixture of 83:17 SL/L produced the highest yield, providing a 10% yield increase compared to the leafed monoculture but no yield difference in comparison to the semi-leafless monoculture.
A quadratic regression (p < 0.001), which combined all varieties, was developed to predict the variation in yield response of the mixing ratios (Figure 8). Regression analysis revealed that the mixture of 86:14 SL/L ratio had the highest yield, providing an 11% yield increase above the leafed monoculture, yet no difference in yield in comparison to the semi-leafless monoculture (Figure 8).

4. Discussion

The canopy height by UAV image estimation provides high accuracy, with an r2 = 0.88 and RMSE = 2.6 cm compared with ground measurement. Previous studies used UAV images and characterized the canopy height with structure-from-motion and the results showed an r2 = 0.85–0.95 canopy height estimation in peanut, wheat, maize, and vineyard [18,20,21,36]. Through canopy height estimation in pre-and post-lodging, the previous study quantitatively assessed the lodging severity across 1320 and then identified a key genomic region for the underlying genetic architecture of lodging in wheat [36]. With precise UAV quantification of canopy height, the time-series height reduction provides precise monitoring for lodging progression.
This study compared mixtures of near-isogenic leaf types with their monocultures in several mixing ratios. The ratio affected lodging, disease severity, crop biomass, and seed yield. The results of UAV-canopy height showed a trend where the leafed component in the leaf-type mixture would increase lodging. Height reduction determined that lodging severity would be significantly increased if the leafed proportion was over 33%. The results are similar to the a previous study reporting that the 25–33% L and 75–67% SL mixtures substantially reduced lodging compared to the sole leafed monoculture [11]. When comparing the lodging severity among the different leaf types and the mixing ratios, the height reduction in the sole semi-leafless type was the lowest. It can be concluded that the semi-leafless monoculture has the greatest lodging resistance when compared to the leafed monoculture and the leaf-type mixture. The great lodging resistance of semi-leafless pea has also been shown by Syrovy [12], in which the semi-leafless monoculture remained upright during the reproductive and maturation stages.
Previous studies have observed that mycosphaerella blight was positively correlated to lodging timing and severity [9,37]. The pathogens in lodged, compacted canopies are exposed to higher humidity, which is conducive to disease development [8]. Hence, sole leafed pea first lodged, and infections proceeded upward to the mid and top leaves resulting in greater severity compared to the mixture and semi-leafless monoculture. Since U. viciae-fabae rust and mycosphaerella blight are both fungal foliar diseases with similar infection progress, lodging theoretically enhances the rust infection.
The current study found that the semi-leafless and leafed ratios did not affect canopy interception for active photosynthetic radiation (Table 4). The photo-assimilation area among leaf-type mixtures and leaf monocultures was no different. Previous studies reported that the leafed type has a greater leaf area than the semi-leafless type at the vegetative stage [25,38]. However, the dense canopy causes a reduction in light penetration to lower plant parts and corresponds with a decrease in photosynthetic activity [39]. In comparison, the semi-leafless type has extended stipules and tendrils in the lower parts which might compensate for the reduction in leaf area and supply for the root and lower reproductive nodes. Therefore, the plant productivity of semi-leafless pea did not decrease with the leaf area [4,40,41]. The corresponding results in this study confirmed that the anticipated higher biomass weight in the mixtures was not observed.
The study used four pairs of near-isogenic lines and found that the optimal leaf mixture might vary with different genotype backgrounds. On the basis of yield results, we indicated that the optimal mixing ratio is in the range of 67–86% semi-leafless and 33–14% leafed pea. This would provide a relatively lodging-resistant canopy and that amount of leafed portion would not reduce yield in comparison to the semi-leafless monoculture. The anticipated yield benefits by leaf-type mixture with semi-leafless peas were not achieved in the present study; however, it could be due to the near-isogenic lines of two leaf types having a similar photosynthetic potential at the podding and seed filling stages. Previous studies showed that mixing two leaf types had a small or no yield increase compared with two sole leaf monocultures. Živanov et al. [42] used a 50:50 SL/L ratio and showed that the yield of the mixture did not differ from the leafed and semi-leafless monocultures, which was intermediate to the monocultures. Antanasovic et al. [22] found that a 75:25 SL/L ratio had a greater yield than the monocultures at the 80 plant/m2 density with 9% and 39% for semi-leafless and leafed monocultures, respectively.
Differences in agronomic responses to leaf type mixtures in peas may be due to the cropping system in which they were grown. In contrast to the present study, Syrovy et al. [12] found that a leaf-type mixture with a 75:25 SL/L ratio led to a weed and lodging reduction, with a 156% increase in leafed yield in the mixture compared to the leafed monoculture and a 18% increase compared to the semi-leafless monoculture. Gollner et al. [43] showed that the leafed monoculture had a higher yield than the mixture of 50:50 SL/L ratio and the semi-leafless monoculture due to greater nitrogen fixation and photosynthetic efficiency. In comparison, the current study was conducted in a conventional cropping system, which provided sufficient fertility for plant growth. Moreover, weeds were controlled by herbicides in early vegetative stages, thus early weed competition among these leaf types was excluded.

5. Conclusions

This study compared three ratios of near-isogenic leafed and semi-leafless mixtures with their monocultures in four varieties. With precise UAV quantification of canopy height, the time-series height reduction provides precise monitoring for lodging progression. The study found that a lodging-resistant canopy is critical for an optimal leaf-type mixture. Mixtures of 67–86% semi-leafless and 33–14% leafed pea improved lodging resistance when compared to the leafed monoculture. However, the leafed pea did not show a greater light interception and biomass weight than the semi-leafless pea. This can explain why the mixture of 86:14 SL/L ratio had lodging similar to the semi-leafless pea and resulted in no yield difference. It can be concluded that while the leafed and semi-leafless pea only differ in leaf type, mixing the two types in a high semi-leafless ratio can reduce leafed lodging and prevent yield loss, but does not increase the overall yield over the semi-leafless monoculture.

Author Contributions

Conceptualization, L.D.S. and S.J.S.; methodology, L.D.S. and S.J.S.; software, Y.S., L.D.S. and T.H.; validation, Y.S. and L.D.S.; formal analysis, Y.S.; investigation, Y.S. and L.D.S.; resources, T.D.W. and D.d.S.; data curation, Y.S.; writing—original draft preparation, Y.S.; writing—review and editing, Y.S., S.J.S., E.N.J., L.D.S. and T.D.W.; visualization, Y.S. and T.H.; supervision, S.J.S., E.N.J., L.D.S. and T.D.W.; project administration, S.J.S., E.N.J. and L.D.S.; funding acquisition, S.J.S., L.D.S. and T.D.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Ministry of Agriculture, Government of Saskatchewan (grant number 20160294), Saskatchewan Pulse Growers, and Plant Phenotyping and Imaging Research Centre(P2IRC).

Data Availability Statement

Data available on request due to restrictions of privacy.

Acknowledgments

We acknowledge all of the crew in the Agronomy and Weed Ecology Lab for their huge support of my field trials: Shaun Campbell, Sydney Redekop, and summer students. Additionally, we would like to thank the Crop Imaging Lab for their contribution and advice on drone imagery and image analysis: Hema Duddu and Seungbum Ryu.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Appendix A

Table
Table A1. Soil properties of 2017–2019 experiment locations in central Saskatchewan, Canada in 2017 and 2019.
Table A1. Soil properties of 2017–2019 experiment locations in central Saskatchewan, Canada in 2017 and 2019.
LocationsYearDepth (cm)pHSOM (%)NO3 *Phosphorus *Potassium *
Kernen South2017
20190–156.84.82028>600
15–307.4 17
30–608 39
Kernen Southeast2018
20190–156.35.13719509
15–307.8 18
30–607.8 55
Blucher20190–1564.13647532
15–307.22.920 208
30–607.61.729 170
Kernen East20180–157.34.2444>600
15–307.7 3
30–608.1 9
* Total nutrient.
Table
Table A2. Dates and days after seeding (DAS) for UAV flights and manual height measurement for field pea plots in 2018 and 2019.
Table A2. Dates and days after seeding (DAS) for UAV flights and manual height measurement for field pea plots in 2018 and 2019.
UAV Flights Dates (DAS)Manual Height Measurement Dates (DAS)
2019-site 156, 62, 69, 72, 77, 8062
2019-site 261, 71, 8661
2019-site 382, 8482
2018-site 158, 66, 70, 77, 83, 9170
Table
Table A3. Coefficient of Variance for the response variables at 6 site-year during 2017 & 2018 &2019 in central Saskatchewan.
Table A3. Coefficient of Variance for the response variables at 6 site-year during 2017 & 2018 &2019 in central Saskatchewan.
Coefficient of Variance [%]
Source of Variation17-Ratio-One18-Ratio-Two18-Ratio-Three19-Ratio-Four19-Ratio-Five19-Ratio-Six
Yield10.8821.1218.4015.5410.8131.20
Biomass14.3217.3618.8218.5515.7422.81
DiseaseNA17.1917.00NA31.9216.69
Lodging height index NA16.1910.749.9612.5616.26
Agronomy 12 01532 g0a1a 550Agronomy 12 01532 g0a1b 550
Figure A1. The mean of image-derived heights of treatments in each flight from pre-lodging to post-lodging in 2018 and 2019 sites. The legend labels the treatments of variety and semi-leafless ratio.
Figure A1. The mean of image-derived heights of treatments in each flight from pre-lodging to post-lodging in 2018 and 2019 sites. The legend labels the treatments of variety and semi-leafless ratio.
Agronomy 12 01532 g0a1aAgronomy 12 01532 g0a1b

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Agronomy 12 01532 g001 550
Figure 1. Workflow of canopy height extraction. Steps of image processing with the functions: 1. Use vegetative index threshold the image to derive the plant pixel mask. 2. Extract plant digital surface map (DSM) from the DEM, plant polygons and plant mask. 3. Extract soil DSM from the DEM and soil polygons. 4. Calculate the normalized canopy height.
Figure 1. Workflow of canopy height extraction. Steps of image processing with the functions: 1. Use vegetative index threshold the image to derive the plant pixel mask. 2. Extract plant digital surface map (DSM) from the DEM, plant polygons and plant mask. 3. Extract soil DSM from the DEM and soil polygons. 4. Calculate the normalized canopy height.
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Figure 2. Canopy light interception of four field pea varieties during early vegetation and podding stages. Mean of one site in 2017, two sites in 2018, and two sites in 2019.
Figure 2. Canopy light interception of four field pea varieties during early vegetation and podding stages. Mean of one site in 2017, two sites in 2018, and two sites in 2019.
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Figure 3. Effect of leaf-type mixing ratio on disease severity. The ratios were listed as semi-leafless + leafed peas. Mean of one site in 2017, two sites in 2018, and two sites in 2019. Columns with different letters (a, b) represent that the mean of disease severity were significantly different in LSD0.05. The error bar represents the positive standard error in LSD0.05.
Figure 3. Effect of leaf-type mixing ratio on disease severity. The ratios were listed as semi-leafless + leafed peas. Mean of one site in 2017, two sites in 2018, and two sites in 2019. Columns with different letters (a, b) represent that the mean of disease severity were significantly different in LSD0.05. The error bar represents the positive standard error in LSD0.05.
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Agronomy 12 01532 g004 550
Figure 4. Validation of the image-derived heights to the ground measured heights in the testing datasets: (a) correlation between actual canopy heights and image-derived canopy heights taken on the same date; (b) correlation between actual plant heights and maximum heights.
Figure 4. Validation of the image-derived heights to the ground measured heights in the testing datasets: (a) correlation between actual canopy heights and image-derived canopy heights taken on the same date; (b) correlation between actual plant heights and maximum heights.
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Agronomy 12 01532 g005 550
Figure 5. Height reduction by image estimation on leafed: semi-leafless pea ratio based on the combined varieties. The Mean of three site-years, one in 2018, and two in 2019. Means with different letters (a–c) are significantly different. The error bar represents the positive standard error in LSD0.05.
Figure 5. Height reduction by image estimation on leafed: semi-leafless pea ratio based on the combined varieties. The Mean of three site-years, one in 2018, and two in 2019. Means with different letters (a–c) are significantly different. The error bar represents the positive standard error in LSD0.05.
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Agronomy 12 01532 g006 550
Figure 6. Interaction of variety and leaf-type mixing ratio on field pea biomass. Mean of six site-years, one in 2017, two in 2018, and three in 2019. Columns with different letters (a–d) represents that the mean biomasses were significantly different in LSD0.05. The error bar represents the positive standard error in LSD0.05. Treatments were listed as semi-leafless + leafed pea, 0/100 is leafed monoculture, for CDC Amarillo (Amarillo), CDC Centennial (Centennial), CDC Dakota (Dakota), and CDC Striker (Striker).
Figure 6. Interaction of variety and leaf-type mixing ratio on field pea biomass. Mean of six site-years, one in 2017, two in 2018, and three in 2019. Columns with different letters (a–d) represents that the mean biomasses were significantly different in LSD0.05. The error bar represents the positive standard error in LSD0.05. Treatments were listed as semi-leafless + leafed pea, 0/100 is leafed monoculture, for CDC Amarillo (Amarillo), CDC Centennial (Centennial), CDC Dakota (Dakota), and CDC Striker (Striker).
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Figure 7. Interaction of variety and leaf-type mixing ratios on yield (kg ha−1). Mean of five site-years, one in 2017, two in 2018, and two in 2019. Columns with different letters (a–h) representing the mean of yield were significantly different in LSD0.05. The error bar represents the positive standard error in LSD0.05. Treatments were listed as semi-leafless + leafed pea, 0/100 is leafed monoculture, for CDC Amarillo (Amarillo), CDC Centennial (Centennial), CDC Dakota (Dakota), and CDC Striker (Striker).
Figure 7. Interaction of variety and leaf-type mixing ratios on yield (kg ha−1). Mean of five site-years, one in 2017, two in 2018, and two in 2019. Columns with different letters (a–h) representing the mean of yield were significantly different in LSD0.05. The error bar represents the positive standard error in LSD0.05. Treatments were listed as semi-leafless + leafed pea, 0/100 is leafed monoculture, for CDC Amarillo (Amarillo), CDC Centennial (Centennial), CDC Dakota (Dakota), and CDC Striker (Striker).
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Figure 8. Regression of semi-leafless/leafed ratio on predicted yield based on the combined varieties. Mean of six site-years, one in 2017, two in 2018, and two in 2019.
Figure 8. Regression of semi-leafless/leafed ratio on predicted yield based on the combined varieties. Mean of six site-years, one in 2017, two in 2018, and two in 2019.
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Table
Table 1. Characteristics of field pea varieties tested in field studies.
Table 1. Characteristics of field pea varieties tested in field studies.
CDC AmarilloCDC StrikerCDC DakotaCDC Centennial
Market ClassYellowGreenDunYellow
Years tested101092
Yield % of CDC Amarillo1008110195
Relative MaturityMMMM
Lodging score a3.53.53.55.5
Vine Length (cm)85808568
Mycosphaerella blight score b4.54.54.56.4
Powdery MildewRSRR
Seed Weight (g/1000) 230240205260
Source: Saskatchewan Variety Guide, 2017. a Lodging score (1–9) where 1 = completely upright, 9 = completely lodged. b Mycosphaerella blight score (1–9) where 1 = no disease, 9 = completely blighted. Powdery Mildew where R = resistant, S = susceptible.
Table
Table 2. Near-isogenic semi-leafless and leafed lines grown in five mixing ratios at five locations in 2017, 2018, and 2019.
Table 2. Near-isogenic semi-leafless and leafed lines grown in five mixing ratios at five locations in 2017, 2018, and 2019.
Near-Isogenic CombinationRatios Tested (SL:L)
CDC Amarillo (SL):CDC Amarillo (L)0:100; 50:50; 67:33; 83:17; 100:0
CDC Centennial (SL):CDC Centennial (L)0:100; 50:50; 67:33; 83:17; 100:0
CDC Dakota (SL):CDC Dakota (L)0:100; 50:50; 67:33; 83:17; 100:0
CDC Striker (SL):CDC Striker (L)0:100; 50:50; 67:33; 83:17; 100:0
Table
Table 3. Mean temperature and total precipitation at the experiment site.
Table 3. Mean temperature and total precipitation at the experiment site.
Mean Temperature (°C)
2017201820191981–2010
April4.3−0.74.85.2
May12.114.19.711.8
June16.117.31616.1
July19.618.717.819
August17.817.115.418.2
Average1413.212.714.1
Total Precipitation (mm)
2017201820191981–2010
April18.49.10.416.2
May46.3354.434.4
June30.919.984.863.6
July25.531.167.753.8
August25.217.120.344.4
Total146.3112.2177.6212.4
Sources: Environment Canada.
Table
Table 4. ANOVA table light interception, lodging height index, disease severity, crop biomass, and seed yield as affected by variety, mixing ratio, and days after seeding (date) in 2017, 2018 and 2019.
Table 4. ANOVA table light interception, lodging height index, disease severity, crop biomass, and seed yield as affected by variety, mixing ratio, and days after seeding (date) in 2017, 2018 and 2019.
Source of VariationdfLight InterceptionHeight ReductionDisease SeverityCrop BiomassCrop Yield
Variety (V)30.140.0130.370.130.0844
Ratio (R)40.780.0330.090.850.0033 **
V * R120.220.0230.380.04 *0.0049 **
Date (D)6<0.0001 *----
V * D180.06----
R * D241----
V * R * D720.4----
Block30.020.28750.11nsns
Rep30.03ns0.39ns0.22
Site-year (SY)40.12ns0.50nsns
V * SY120.090.0650.08ns0.010
R * SY160.090.030ns0.130.055
Pooled data. One site in 2017, two sites in 2018 and two sites in 2019. *, ** Source of variation significant at 0.05 and 0.01 p level, respectively;. -, the responses did not do repeat measures.
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Shen, Y.; Syrovy, L.D.; Johnson, E.N.; Warkentin, T.D.; Ha, T.; de Silva, D.; Shirtliffe, S.J. Optimizing Seeding Ratio for Semi-Leafless and Leafed Pea Mixture with Precise UAV Quantification of Crop Lodging. Agronomy 2022, 12, 1532. https://doi.org/10.3390/agronomy12071532

AMA Style

Shen Y, Syrovy LD, Johnson EN, Warkentin TD, Ha T, de Silva D, Shirtliffe SJ. Optimizing Seeding Ratio for Semi-Leafless and Leafed Pea Mixture with Precise UAV Quantification of Crop Lodging. Agronomy. 2022; 12(7):1532. https://doi.org/10.3390/agronomy12071532

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Shen, Yanben, Lena D. Syrovy, Eric N. Johnson, Thomas D. Warkentin, Thuan Ha, Devini de Silva, and Steven J. Shirtliffe. 2022. "Optimizing Seeding Ratio for Semi-Leafless and Leafed Pea Mixture with Precise UAV Quantification of Crop Lodging" Agronomy 12, no. 7: 1532. https://doi.org/10.3390/agronomy12071532

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