Increased nitrogen use efficiency in crop production can provide economic and environmental benefits

From Images to Loci: Applying 3D Deep Learning to Enable Multivariate and Multitemporal Digital Phenotyping and Mapping the Genetics Underlying Nitrogen Use Efficiency in Wheat

The selection and promotion of high-yielding and nitrogen-efficient wheat varieties can reduce nitrogen fertilizer application while ensuring wheat yield and quality and contribute to the sustainable development of agriculture; thus, the mining and localization of nitrogen use efficiency (NUE) genes is particularly important, but the localization of NUE genes requires a large amount of phenotypic data support. In view of this, we propose the use of low-altitude aerial photography to acquire field images at a large scale, generate 3-dimensional (3D) point clouds and multispectral images of wheat plots, propose a wheat 3D plot segmentation dataset, quantify the plot canopy height via combination with PointNet++, and generate 4 nitrogen utilization-related vegetation indices via index calculations. Six height-related and 24 vegetation-index-related dynamic digital phenotypes were extracted from the digital phenotypes collected at different time points and fitted to generate dynamic curves. We applied height-derived dynamic numerical phenotypes to genome-wide association studies of 160 wheat cultivars (660,000 single-nucleotide polymorphisms) and found that we were able to locate reliable loci associated with height and NUE, some of which were consistent with published studies. Finally, dynamic phenotypes derived from plant indices can also be applied to genome-wide association studies and ultimately locate NUE- and growth-related loci. In conclusion, we believe that our work demonstrates valuable advances in 3D digital dynamic phenotyping for locating genes for NUE in wheat and provides breeders with accurate phenotypic data for the selection and breeding of nitrogen-efficient wheat varieties.

Combined Application of Leguminous Green Manure and Straw Determined Grain Yield and Nutrient Use Efficiency in Wheat-Maize-Sunflower Rotations System in Northwest China

Leguminous green manure (LGM) has a reputation for improving crop productivity. However, little is known about the beneficial interactions with straw on crop yield and nutrient (N, P, K) use efficiency. Herein, a 9-year field experiment (from 2015 to 2023) containing three treatments-(1) chemical fertilizer as the control (CK), (2) NPK + straw return (Straw) and (3) NPK + straw return with LGM (Straw + LGM)-was conducted to investigate whether the combined application of LGM and straw can increase productivity and nutrient use efficiency in the wheat-maize-sunflower diversified cropping rotation. The results showed that in the third rotation (2021-2023), Straw + LGM significantly increased wheat yield by 10.2% and maize yield by 19.9% compared to CK. The total equivalent yield under Straw + LGM was the highest (26.09 Mg ha-1), exceeding Straw and CK treatments by 2.7% and 12.3%, respectively. For each 2 Mg ha-1 increase in straw returned to the field, sunflower yield increased by 0.2 Mg ha-1, whereas for each 1 Mg ha-1 increase in LGM yield from the previous crop, sunflower yield increased by 0.45 Mg ha-1. Compared to CK, the co-application of LGM and straw increased the N use efficiency of maize in the first and third rotation cycle by 70.6% and 55.8%, respectively, and the P use efficiency by 147.8% in the third rotation cycle. Moreover, Straw treatment led to an increase of net income from wheat and sunflower by 14.5% and 44.6%, while Straw + LGM increased the net income from maize by 15.8% in the third rotation cycle. Combining leguminous green manure with a diversified cropping rotation has greater potential to improve nutrient use efficiency, crop productivity and net income, which can be recommended as a sustainable agronomic practice in the Hetao District, Northwest China.

Evaluation of three sets of advanced backcrosses of eggplant with wild relatives from different gene pools under low N fertilization conditions

The development of new cultivars with improved nitrogen use efficiency (NUE) is key for implementing sustainable agriculture practices. Crop wild relatives (CWRs) provide valuable genetic resources for breeding programs aimed at achieving this goal. In this study, three eggplant (Solanum melongena) accessions together with their advanced backcrosses (ABs; BC3 to BC5 generations) were evaluated for 22 morpho-agronomic, physiological, and NUE traits under low nitrogen (LN) fertilization conditions. The ABs were developed with introgressions from the wild relatives Solanum insanum, Solanum dasyphyllum, and Solanum elaeagnifolium. The AB population comprised a total of 25, 59, and 59 genotypes, respectively, with overall donor wild relative genome coverage percentages of 58.8%, 46.3%, and 99.2%. The three S. melongena recurrent parents were also evaluated under control (normal) N fertilization. Reduction of N fertilization in the parents resulted in decreased chlorophyll content-related traits, aerial biomass, stem diameter, and yield and increased NUE, nitrogen uptake efficiency (NUpE), and nitrogen utilization efficiency (NUtE). However, the decrease in yield was moderate, ranging between 62.6% and 72.6%. A high phenotypic variation was observed within each of the three sets of ABs under LN conditions, with some individuals displaying improved transgressive characteristics over the recurrent parents. Using the single primer enrichment technology 5 k probes platform for high-throughput genotyping, we observed a variable but high degree of recurrent parent genome recovery in the ABs attributable to the lines recombination, allowing the successful identification of 16 quantitative trait loci (QTL). Different allelic effects were observed for the introgressed QTL alleles. Several candidate genes were identified in the QTL regions associated with plant growth, yield, fruit size, and NUE-related parameters. Our results show that eggplant materials with introgressions from CWRs can result in a dramatic impact in eggplant breeding for a more sustainable agriculture.

Genetic resources and precise gene editing for targeted improvement of barley abiotic stress tolerance

Abiotic stresses, predominately drought, heat, salinity, cold, and waterlogging, adversely affect cereal crops. They limit barley production worldwide and cause huge economic losses. In barley, functional genes under various stresses have been identified over the years and genetic improvement to stress tolerance has taken a new turn with the introduction of modern gene-editing platforms. In particular, clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) is a robust and versatile tool for precise mutation creation and trait improvement. In this review, we highlight the stress-affected regions and the corresponding economic losses among the main barley producers. We collate about 150 key genes associated with stress tolerance and combine them into a single physical map for potential breeding practices. We also overview the applications of precise base editing, prime editing, and multiplexing technologies for targeted trait modification, and discuss current challenges including high-throughput mutant genotyping and genotype dependency in genetic transformation to promote commercial breeding. The listed genes counteract key stresses such as drought, salinity, and nutrient deficiency, and the potential application of the respective gene-editing technologies will provide insight into barley improvement for climate resilience.

Suitable fertilization can improve maize growth and nutrient utilization in ridge-furrow rainfall harvesting cropland in semiarid area

The ridge-furrow rainfall harvesting system (RFRH) improved the water shortages, and reasonable fertilization can promote nutrient uptake and utilization of crops, leading to better yield in semi-arid regions. This holds significant practical significance for improving fertilization strategies and reducing the application of chemical fertilizers in semi-arid areas. This field study was conducted to investigate the effects of different fertilization rates on maize growth, fertilizer use efficiency, and grain yield under the ridge-furrow rainfall harvesting system during 2013-2016 in semiarid region of China. Therefore, a four-year localization field experiment was conducted with four fertilizer treatments: RN (N 0 kg hm^-2, P₂O₅ 0 kg hm^-2), RL (N 150 kg hm^-2, P₂O₅ 75 kg hm^-2), RM (N 300 kg hm^-2, P₂O₅ 150 kg hm^-2), and RH (N 450 kg hm^-2, P₂O₅ 225 kg hm^-2). The results showed that the total dry matter accumulation of maize increased with the fertilizer application rate. The nitrogen accumulation was highest under the RM treatment after harvest, average increase by 1.41% and 22.02% (P<0.05) compared to the RH and RL, respectively, whereas the phosphorus accumulation was increased with the fertilizer application rate. The nitrogen and phosphorus use efficiency both decreased gradually with the fertilization rate increased, where the maximum efficiency was observed under the RL. With the increase of fertilizer application rate, the maize grain yield initially increased and then decreased. Under linear fitting, the grain yield, biomass yield, hundred-kernel weight, and ear-grain number all showed a parabolic trend with the increase of fertilization rate. Based on comprehensive consideration, the recommended moderate fertilization rate (N 300 kg hm^-2, P₂O₅ 150 kg hm^-2) is suitable for the ridge furrow rainfall harvesting system in semiarid region, and the fertilization rate can be appropriately reduced according to the rainfall.

Ecosystem service benefits to water users from perennial biomass production

Although many agree that a transition to renewable energy sources is needed to avoid the climate consequences of continued reliance on fossil sources, price is a barrier. For renewable energy sources, including bioenergy, penetrating energy markets depends on lowering prices to compete with the price of fossil sources, but the tools used in decision making, such as supply curves, exclude non-market benefits from ecosystem services. Here, we extend the economic concept of an economic supply curve to account for ecosystem services co-produced with perennial biomass. We developed three new types of supply curves to visualize the increased supply of biomass ('sustainable supply') with sufficient water-quality benefits to offset biomass production costs. Using these tools, we show that the value of water-quality improvements could significantly reduce the break-even price of perennial feedstocks if it were available to farmers. In the most optimistic case, nearly half of potential biomass supply in a large tributary of the Mississippi river basin carried water purification value exceeding the cost of biomass production. Furthermore, adding the value to swimmers and waders offset production cost for over 90% of potential supply. Simulated benefits were context specific. For example, total value for water drinkers peaked at an intermediate level of fertilizer application. Geographically, benefits were highest in the eastern portion of the river basin. This research shows where the sustainable supply is needed and can generate value; the next step is to match this supply with credit buyers. Efforts to internalize the values of ecosystem services into biomass prices could help to meet Biden administration targets to meet 100% of sustainable aviation fuels.

Comparative Transcriptomic Analyses of Nitrate-Response in Rice Genotypes With Contrasting Nitrogen Use Efficiency Reveals Common and Genotype-Specific Processes, Molecular Targets and Nitrogen Use Efficiency-Candidates

The genetic basis for nitrogen (N)-response and N use efficiency (NUE) must be found in N-responsive gene expression or protein regulation. Our transcriptomic analysis of nitrate response in two contrasting rice genotypes of Oryza sativa ssp. Indica (Nidhi with low NUE and Panvel1 with high NUE) revealed the processes/functions underlying differential N-response/NUE. The microarray analysis of low nitrate response (1.5 mM) relative to normal nitrate control (15 mM) used potted 21-days old whole plants. It revealed 1,327 differentially expressed genes (DEGs) exclusive to Nidhi and 666 exclusive to Panvel1, apart from 70 common DEGs, of which 10 were either oppositely expressed or regulated to different extents. Gene ontology analyses revealed that photosynthetic processes were among the very few processes common to both the genotypes in low N response. Those unique to Nidhi include cell division, nitrogen utilization, cytoskeleton, etc. in low N-response, whereas those unique to Panvel1 include signal transduction, protein import into the nucleus, and mitochondria. This trend of a few common but mostly unique categories was also true for transporters, transcription factors, microRNAs, and post-translational modifications, indicating their differential involvement in Nidhi and Panvel1. Protein-protein interaction networks constructed using DEG-associated experimentally validated interactors revealed subnetworks involved in cytoskeleton organization, cell wall, etc. in Nidhi, whereas in Panvel1, it was chloroplast development. NUE genes were identified by selecting yield-related genes from N-responsive DEGs and their co-localization on NUE-QTLs revealed the differential distribution of NUE-genes between genotypes but on the same chromosomes 1 and 3. Such hotspots are important for NUE breeders.

The Genetic Architecture of Nitrogen Use Efficiency in Switchgrass (Panicum virgatum L.)

Switchgrass (Panicum virgatum L.) has immense potential as a bioenergy crop with the aim of producing biofuel as an end goal. Nitrogen (N)-related sustainability traits, such as nitrogen use efficiency (NUE) and nitrogen remobilization efficiency (NRE), are important factors affecting switchgrass quality and productivity. Hence, it is imperative to develop nitrogen use-efficient switchgrass accessions by exploring the genetic basis of NUE in switchgrass. For that, we used 331 diverse field-grown switchgrass accessions planted under low and moderate N fertility treatments. We performed a genome wide association study (GWAS) in a holistic manner where we not only considered NUE as a single trait but also used its related phenotypic traits, such as total dry biomass at low N and moderate N, and nitrogen use index, such as NRE. We have evaluated the phenotypic characterization of the NUE and the related traits, highlighted their relationship using correlation analysis, and identified the top ten nitrogen use-efficient switchgrass accessions. Our GWAS analysis identified 19 unique single nucleotide polymorphisms (SNPs) and 32 candidate genes. Two promising GWAS candidate genes, caffeoyl-CoA O-methyltransferase (CCoAOMT) and alfin-like 6 (AL6), were further supported by linkage disequilibrium (LD) analysis. Finally, we discussed the potential role of nitrogen in modulating the expression of these two genes. Our findings have opened avenues for the development of improved nitrogen use-efficient switchgrass lines.

Systems-level analysis of the plasticity of the maize metabolic network reveals novel hypotheses in the nitrogen-use efficiency of maize roots

This article comments on: Chowdhury NB, Schroeder WL, Sarkar D, Amiour N, Quilleré I, Hirel B, Maranas CD, Saha R. 2022. Dissecting the metabolic reprogramming of maize root under nitrogen-deficient stress conditions. Journal of Experimental Botany 73, 275–291.

Meta-Analysis of Yield-Related and N-Responsive Genes Reveals Chromosomal Hotspots, Key Processes and Candidate Genes for Nitrogen-Use Efficiency in Rice

Nitrogen-use efficiency (NUE) is a function of N-response and yield that is controlled by many genes and phenotypic parameters that are poorly characterized. This study compiled all known yield-related genes in rice and mined them from the N-responsive microarray data to find 1,064 NUE-related genes. Many of them are novel genes hitherto unreported as related to NUE, including 80 transporters, 235 transcription factors (TFs), 44 MicroRNAs (miRNAs), 91 kinases, and 8 phosphatases. They were further shortlisted to 62 NUE-candidate genes following hierarchical methods, including quantitative trait locus (QTL) co-localization, functional evaluation in the literature, and protein-protein interactions (PPIs). They were localized to chromosomes 1, 3, 5, and 9, of which chromosome 1 with 26 genes emerged as a hotspot for NUE spanning 81% of the chromosomes. Further, co-localization of the NUE genes on NUE-QTLs resolved differences in the earlier studies that relied mainly on N-responsive genes regardless of their role in yield. Functional annotations and PPIs for all the 1,064 NUE-related genes and also the shortlisted 62 candidates revealed transcription, redox, phosphorylation, transport, development, metabolism, photosynthesis, water deprivation, and hormonal and stomatal function among the prominent processes. In silico expression analysis confirmed differential expression of the 62 NUE-candidate genes in a tissue/stage-specific manner. Experimental validation in two contrasting genotypes revealed that high NUE rice shows better photosynthetic performance, transpiration efficiency and internal water-use efficiency in comparison to low NUE rice. Feature Selection Analysis independently identified one-third of the common genes at every stage of hierarchical shortlisting, offering 6 priority targets to validate for improving the crop NUE.