Long-term weed dynamics and crop yields under organic and conventional cropping systems in the Canadian prairies

Differences in cropping practices, including tillage, inputs and crop rotations are the driving factors affecting weed dynamics (weed abundance, composition and crop-weed competition), which can ultimately affect crop yields. Several experiments were carried out to assess the impact of long-term organic and conventional cropping systems on weed abundance, weed community composition, crop yield and yield loss using a long-term (18 year) alternative cropping systems study (ACS) at Scott, Saskatchewan, Canada. The ACS study consisted of three input systems, namely high (conventional tillage), reduced (no-till conventional) and organic input systems and three crop rotation diversities (low diversity, diversified annual grains and diversified annual-perennials). A statistical analysis of the 18-year rotation revealed that the organic rotations have four and seven times higher weed density and 32% and 35% lower crop yields than the reduced and the high input systems respectively. Weed community composition was consistently different in organic rotations compared to the two conventional rotations throughout the years, but year to year random variations were more profound. All cropping systems showed an increase in weed density, weed biomass and crop yields over time, probably due to an increase in rainfall over time. Increasing the crop rotation diversity with annual and perennial crops did not reduce weeds, but decreased crop yields in all systems. A two-year micro-plot experiment with four additional weed competition treatments on the ACS study revealed that the wheat yields were lower in the organic rotations even in the absence of weeds, implying that lower crop yields were due to soil fertility related factors. A greenhouse pot experiment from soils obtained from both organic and reduced rotations revealed that wheat yields were still lower in organic compared to the reduced input systems, even after excess mineral N and P were added. Furthermore, no differences in crop yield loss due to weed competition among cropping systems were identified. Overall, this study revealed that eliminating tillage and reducing inputs are possible without long-term changes in weed abundance, weed community composition or affecting crop yields. However, eliminating synthetic inputs as was done in the form of organic crop rotations resulted in increased weed abundance, changed community composition and decreased crop yields

Enhancing the competitive ability of oat (Avena sativa L.) cropping systems

Abstract Ecological based weed management strategies are imperative in cropping systems when herbicide use is limited or prohibited. Herbicides are not applicable in controlling wild oat (Avena fatua L.) in oat (Avena sativa L.) cropping systems, as they are closely related. Moreover, herbicide use is prohibited in organic oat cultivation, resulting in a need for developing alternative weed management strategies. Enhancing the crop competitive ability (CA) can be an essential strategy in managing weeds in such instances. Two studies were carried with the objectives to: 1) evaluate newly developed oat genotypes for their CA against wild oat; and 2) develop a competitive organic oat cropping system integrating mechanical and cultural weed control practices. In the first study, seven oat lines deliberately bred for enhanced CA and their two parental cultivars were evaluated for the CA with wild oat. The genotypes yielded similarly in the presence and in the absence of wild oat competition. The tall oat line SA050479 with greater seedling leaf size was more wild oat suppressive among all lines. Moreover, SA050479 had greater yield potential and grain quality; thus, it has the potential to be developed as a commercial wild oat suppressive cultivar. The second study used two contrasting levels of genotype, row spacing, crop density and a post-emergence harrowing and a non-harrowed control in two organic oat fields to develop an integrated weed management system. High crop density and harrowing increased the grain yield by 11% and 13% respectively. The competitive cultivar CDC Baler and high crop density (500 plants m-2) reduced weed biomass by 22% and 52% respectively. Harrowing reduced weed density by more than 50% in three site-years. The cultural and mechanical weed control practices when combined were additive in increasing grain yield and reducing weed biomass. Oat seed yields were increased by 25% when high crop density planting and harrowing were combined. Similarly, the combined effect of competitive cultivar, high crop density, and post-emergence harrowing were greater as weed biomass was reduced by 71%. The outcome of this project implies the importance of enhancing the crop CA by means of crop breeding and integrating cultural and mechanical weed control strategies. Furthermore, this study was able to identify the importance of ecological based weed management strategies in order to overcome the constraints in weed management in present oat cropping systems

Weed dynamics under diverse nutrient management and crop rotation practices in the dry zone of Sri Lanka

Integrated weed control strategies are essential for organic and integrated nutrient management, where both systems are progressing with a fundamental of zero or minimum synthetic chemical cultivations. For optimizing the outcome of weed management, a better understanding of the weed dynamic is needed. Especially, with the absence of herbicides, weeds are expected to be controlled by the system itself, during the transition period under rice-based crop rotation systems. This study was conducted to estimate the weed abundance, growth, and composition during the transitional period with conventional (CONV), integrated (INT), and organic (ORG) nutrient management under four crop diversification intensities in a dry zone of Sri Lanka. Monocrop rice and a rice-maize rotation were the starting point. After 1 year, the diversification intensity was increased by adding interseason sunnhemp (rice-sunnhemp-rice and rice-sunnhemp-maize). Weed density and weed biomass were measured at 20 DAS and 60 DAS intervals. Weed density was higher in ORG during the early growth stages of monocrop rice rotation in the 1st cycle, and monocrop rice and rice-sunnhemp-rice rotation in the 2nd cycle while didn’t show any changes during the later growth stage of all systems in both cycles. The total weed biomass in ORG increased with increasing crop diversification. Overall, crop rotation in INT reported the lowest weed density and biomass after two cycles. In the CONV with rice-sunnhemp-maize rotation, weed biomass had declined, while in ORG grass biomass decreased only in sunnhemp cultivated rotations. Overall, INT was the best for weed suppression irrespective of crop rotation intensities. Monoculture with rice in the INT was able to suppress weed more effectively than rice-maize rotation

High-Resolution Flowering Index for Canola Yield Modelling

Canola (Brassica napus), with its prominent yellow flowers, has unique spectral characteristics and necessitates special spectral indices to quantify the flowers. This study investigated four spectral indices for high-resolution RGB images for segmenting yellow flower pixels. The study compared vegetation indices to digitally quantify canola flower area to develop a seed yield prediction model. A small plot (2.75 m × 6 m) experiment was conducted at Kernen Research Farm, Saskatoon, where canola was grown under six row spacings and eight seeding rates with four replicates (192 plots). The flower canopy reflectance was imaged using a high-resolution (0.15 cm ground sampling distance) 100 MP iXU 1000 RGB sensor mounted on an unpiloted aerial vehicle (UAV). The spectral indices were evaluated for their efficiency in identifying canola flower pixels using linear discriminant analysis (LDA). Digitized flower pixel area was used as a predictor of seed yield to develop four models. Seventy percent of the data were used for model training and 30% for testing. Models were compared using performance metrics: coefficient of determination (R2) and root mean squared error (RMSE). The High-resolution Flowering Index (HrFI), a new flower index proposed in this study, was identified as the most accurate in detecting flower pixels, especially in high-resolution imagery containing within-canopy shadow pixels. There were strong, positive associations between digitized flower area and canola seed yield with the peak flowering timing having a greater R2 (0.82) compared to early flowering (0.72). Cumulative flower pixel area predicted 75% of yield. Our results indicate that the HrFI and Modified Yellowness Index (MYI) were better predictors of canola yield compared to the NDYI and RBNI (Red Blue Normalizing Index) as they were able to discriminate between canola petals and within-canopy shadows. We suggest further studies to evaluate the performance of the HrFI and MYI vegetation indices using medium-resolution UAV and satellite imagery