Mar 2024, Volume 3 Issue 1

    

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• High-throughput phenotyping and deep learning to analyze dynamic panicle growth and dissect the genetic architecture of yield formation

  Zedong Geng, Yunrui Lu, Lingfeng Duan, Hongfei Chen, Zhihao Wang, Jun Zhang, Zhi Liu, Xianmeng Wang, Ruifang Zhai, Yidan Ouyang, Wanneng Yang

  2024, 3(1): 1-11. https://doi.org/10.1016/j.crope.2023.10.005

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  The dynamic growth of shoots and panicles determines the final agronomic traits and yield. However, it is difficult to quantify such dynamics manually for large populations. In this study, based on the high-throughput rice automatic phenotyping platform and deep learning, we developed a novel image analysis pipeline (Panicle-iAnalyzer) to extract image-based traits (i-traits) including 52 panicle and 35 shoot i-traits and tested the system using a recombinant inbred line population derived from a cross between Zhenshan 97 and Minghui 63. At the maturity stage, image recognition using a deep learning network (SegFormer) was applied to separate the panicles from the shoot in the image. Eventually, with these obtained i-traits, the yield could be well predicted, and the R² was 0.862. Quantitative trait loci (QTL) mapping was performed using an extra-high density single nucleotide polymorphism (SNP) bin map. A total of 3,586 time-specific QTLs were identified for the traits and parameters at various time points. Many of the QTLs were repeatedly detected at different time points. We identified the presence of cloned genes, such as TAC1, Ghd7.1, Ghd7, and Hd1, at QTL hotspots and evaluated the magnitude of their effects at different developmental stages. Additionally, this study identified numerous new QTL loci worthy of further investigation.
• Grain yield and protein concentration relationships in rice

  Shu Fukai, Jaquie Mitchell

  2024, 3(1): 12-24. https://doi.org/10.1016/j.crope.2023.11.002

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  Grain protein concentration (GPC) is an important aspect of rice grain quality, which contributes to nutritional intake requirements; however, high GPC may also reduce eating quality. Both GPC and grain yield (GY) are greatly affected by nitrogen (N) management, and GPC is strongly linked to GY through shared N pathways. This review aims to determine how GPC in rice is affected under different growing conditions and crop management options and how varieties differ in GPC under different conditions and to identify the link between GPC and GY. It highlights the importance of total N uptake by the crop and that GPC gradually increases with the N application rate up to an optimum at which GY reaches a maximum. While GY varies greatly depending on the growing conditions, GPC tends to be maintained within a relatively narrow range. When a number of genotypes are compared, there is often an inverse relationship between GY and GPC, with a mean reduction in GPC of 0.46 percentage point for each 1.0 t ha^-1 increase in GY. However, the balance between GY and GPC is altered based on the genotype's capacity to both take up N from the soil and distribute it to grain, including its ability to translocate N from vegetative organs to growing grain. The balance varies greatly among genotypes, as demonstrated in the case of hybrids, where GY is often higher but GPC is lower compared with inbred varieties. The review concludes with the identification of future research efforts to further understand the GY-GPC relationship.
• Agronomic assessment of the yield variability and yield gap of maize in Bhutan

  Passang Wangmo, Kinzang Thinley, Taiken Nakashima, Yoichiro Kato

  2024, 3(1): 25-32. https://doi.org/10.1016/j.crope.2023.11.003

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  Maize is the staple food crop in Bhutan, which has not achieved national food self-sufficiency. On-farm assessment of yield variability would provide insights into the priorities for Bhutan's maize development program. Here, we conducted three studies in Bhutan: a household survey, on-station experiment, and on-farm monitoring. First, we interviewed 100 households and collected information on maize crop management options and farming characteristics. Second, we evaluated maize growth at two research stations in different elevation zones (640 and 1,700 m a.s.l.). Third, we harvested maize from 25 farm fields at low and high elevations. The gaps between potential yield (with the best management practices at the research stations) and average farm yield and between the best and average farm yields were 53% and 23%, respectively, at the low elevation, and 23% and 20%, respectively, at the high elevation. The classification and regression tree (CART) model showed that field location (distance from the farmer's home), seed source (certified vs. self-produced), and the number of household members involved in farming were the key farming characteristics that affected yield variability, and the manure application regime, urea application, sowing method, and weeding frequency were key management practices. Our results suggest that future research should clarify the most suitable sowing methods and nutrient and weed management regimes, and identify optimal cultivars for each elevation zone, with the goal of developing crop management guidelines for smallholder farmers in Bhutan.
• Sensor-based measurements of NDVI in small grain and corn fields by tractor, drone, and satellite platforms

  Jarrod O. Miller, Pinki Mondal, Manan Sarupria

  2024, 3(1): 33-42. https://doi.org/10.1016/j.crope.2023.11.001

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  The use of sensors for variable rate nitrogen (VRN) applications is transitioning from equipment-based to drone and satellite technologies. However, regional algorithms, initially designed for proximal active sensors, require evaluation for compatibility with remotely sensed reflectance and N-rate predictions. This study observed normalized difference vegetation index (NDVI) data from six small grain and two corn fields over three years. We employed three platforms: tractor-mounted active sensors (T-NDVI), passive multispectral drone (D-NDVI), and satellite (S-NDVI) sensors. Averaged NDVI values were extracted from the as-applied equipment polygons. Correlations between NDVI values from the three platforms were positive and strong, with D-NDVI consistently recording the highest values, particularly in areas with lower plant biomass. This was attributed to D-NDVI's lower soil reflectance and its ability to measure the entire biomass within equipment polygons. For small grains, sensors spaced on equipment booms might not capture accurate biomass in poor-growing and low NDVI regions. Regarding VRN, S-NDVI and D-NDVI occasionally aligned with T-NDVI recommendations but often suggested half the active sensor rate. Final yields showed some correlation with landscape variables, irrespective of N application. This finding suggests the potential use of drone or satellite imagery to provide multiple NDVI maps before application, incorporating expected landscape responses and thereby enhancing VRN effectiveness.
• Balancing food security, vertebrate biodiversity, and healthy rice agroecosystems in Southeast Asia

  Catherine R. Propper, Jodi L. Sedlock, Richard E. Smedley, Oliver Frith, Molly E. Shuman-Goodier, Alejandro Grajal-Puche, Alexander M. Stuart, Grant R. Singleton

  2024, 3(1): 43-50. https://doi.org/10.1016/j.crope.2023.11.005

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  Rice is the dominant food staple and an important economic resource throughout Asia. Lowland rice production also provides important wetland habitats in support of biodiversity that may provide ecosystem services back to the rice agroecosystems. This review summarizes the literature on the ecosystem benefits that amphibians, birds, bats, and rodents support in the context of the Southeast Asia rice agroecosystems. The literature provides evidence that these taxonomic groups contribute to cultural, regulatory, and provisioning services in support of smallholder farmers and may allow for economic benefits through reduced use of chemical inputs into crops. We encourage a multipronged research approach to bring stakeholders together to provide structured and scalable education programs that will lead to improved human and agroecosystem health through the promotion of understanding the positive feedbacks from biodiversity in these important agricultural wetland habitats.
• Enhancing maize radiation use efficiency under high planting density by shaping canopy architecture with a plant growth regulator

  Guanmin Huang, Yuling Guo, Weiming Tan, Mingcai Zhang, Zhaohu Li, Yuyi Zhou, Liusheng Duan

  2024, 3(1): 51-63. https://doi.org/10.1016/j.crope.2023.11.004

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  Optimized maize (Zea mays L.) canopy architecture enhances density-tolerance. DHEAP (N, N-Diethyl-2-hexanoyl oxygen radicals-ethyl amine (2-ethyl chloride) phosphonic acid salt) has been shown to increase maize upper canopy strata compactness, but its overall effect on the whole canopy structure and how it shapes the canopy structure remain unclear. This study examined how DHEAP affected the canopy structure of maize hybrids Zhengdan 958 (ZD958) and Xianyu 335 (XY335), with distinct canopy structures, under different planting densities. The results showed that DHEAP increased the leaf orientation value (LOV) of upper canopy strata by 8.0% while reducing middle and lower strata LOV by 11.7% and 18.4%, respectively. This indicates that DHEAP shaped a canopy structure that was compact in the upper strata and loose in the middle and lower strata. Multiple linear regression analysis showed that leaf angle had a greater impact on the upper canopy strata, while leaf auricle size had a greater impact on the middle and lower canopy strata. After DHEAP treatment, light transmission above different canopy strata increased at the reproductive stage. Concurrently, the middle canopy captured more light energy, enhanced yield formation, and boosted radiation use efficiency by 21.9% under high density. In terms of grain yield, DHEAP treatment resulted in a 9.1% and 23.9% increase in ZD958 and XY335, respectively, under high-density conditions. These results suggest that DHEAP shaped the maize canopy structure with high density tolerance, improved the distribution of light within the canopy, and increased grain yield.