Sorghum (Sorghum bicolor) is a model C₄ crop made experimentally tractable by extensive genomic and genetic resources. Biomass sorghum is studied as a feedstock for biofuel and forage. Mechanistic modeling suggests that reducing stomatal conductance (g_s) could improve sorghum intrinsic water use efficiency (iWUE) and biomass production. Phenotyping to discover genotype-to-phenotype associations remains a bottleneck in understanding the mechanistic basis for natural variation in g_s and iWUE. This study addressed multiple methodological limitations. Optical tomography and a machine learning tool were combined to measure stomatal density (SD). This was combined with rapid measurements of leaf photosynthetic gas exchange and specific leaf area (SLA). These traits were the subject of genome-wide association study and transcriptome-wide association study across 869 field-grown biomass sorghum accessions. The ratio of intracellular to ambient CO₂ was genetically correlated with SD, SLA, g_s, and biomass production. Plasticity in SD and SLA was interrelated with each other and with productivity across wet and dry growing seasons. Moderate-to-high heritability of traits studied across the large mapping population validated associations between DNA sequence variation or RNA transcript abundance and trait variation. A total of 394 unique genes underpinning variation in WUE-related traits are described with higher confidence because they were identified in multiple independent tests. This list was enriched in genes whose Arabidopsis (Arabidopsis thaliana) putative orthologs have functions related to stomatal or leaf development and leaf gas exchange, as well as genes with nonsynonymous/missense variants. These advances in methodology and knowledge will facilitate improving C4 crop WUE.

Sorghum (Sorghum bicolor L.) is a major food cereal for millions of people worldwide. The sorghum genome, like other species, accumulates deleterious mutations, likely impacting its fitness. The lack of recombination, drift, and the coupling with favorable loci impede the removal of deleterious mutations from the genome by selection. To study how deleterious variants impact phenotypes, we identified putative deleterious mutations among ~5.5M segregating variants of 229 diverse biomass sorghum lines. We provide the whole-genome estimate of the deleterious burden in sorghum, showing that about 33 percent of nonsynonymous substitutions are putatively deleterious. The pattern of mutation burden varies appreciably among racial groups. Across racial groups, the mutation burden correlated negatively with biomass, plant height, specific leaf area (SLA), and tissue starch content (TSC), suggesting deleterious burden decreases trait fitness. Putatively deleterious variants explain roughly half of the genetic variance. However, there is only moderate improvement in total heritable variance explained for biomass (7.6%) and plant height (average of 3.1% across all stages). There is no advantage in total heritable variance for SLA and TSC. The contribution of putatively deleterious variants to phenotypic diversity therefore appears to be dependent on the genetic architecture of traits. Overall, these results suggest that incorporating putatively deleterious variants into genomic models slightly improve prediction accuracy because of extensive linkage. Knowledge of deleterious variants could be leveraged for sorghum breeding through either genome editing and/or conventional breeding that focus on the selection of progeny with fewer deleterious alleles.

Stomata allow CO₂ uptake by leaves for photosynthetic assimilation at the cost of water vapor loss to the atmosphere. The opening and closing of stomata in response to fluctuations in light intensity regulate CO₂ and water fluxes and are essential for maintaining water-use efficiency (WUE). However, a little is known about the genetic basis for natural variation in stomatal movement, especially in C₄ crops. This is partly because the stomatal response to a change in light intensity is difficult to measure at the scale required for association studies. Here, we used high-throughput thermal imaging to bypass the phenotyping bottleneck and assess 10 traits describing stomatal conductance (g_s) before, during and after a stepwise decrease in light intensity for a diversity panel of 659 sorghum (Sorghum bicolor) accessions. Results from thermal imaging significantly correlated with photosynthetic gas exchange measurements. g_s traits varied substantially across the population and were moderately heritable (h² up to 0.72). An integrated genome-wide and transcriptome-wide association study identified candidate genes putatively driving variation in stomatal conductance traits. Of the 239 unique candidate genes identified with the greatest confidence, 77 were putative orthologs of Arabidopsis (Arabidopsis thaliana) genes related to functions implicated in WUE, including stomatal opening/closing (24 genes), stomatal/epidermal cell development (35 genes), leaf/vasculature development (12 genes), or chlorophyll metabolism/photosynthesis (8 genes). These findings demonstrate an approach to finding genotype-to-phenotype relationships for a challenging trait as well as candidate genes for further investigation of the genetic basis of WUE in a model C₄ grass for bioenergy, food, and forage production.

Purpose of Review: The paper discusses how robotics and autonomous systems (RAS) are being deployed to decarbonise agricultural production. The climate emergency cannot be ameliorated without dramatic reductions in greenhouse gas emissions across the agri-food sector. This review outlines the transformational role for robotics in the agri-food system and considers where research and focus might be prioritised. Recent Findings: Agri-robotic systems provide multiple emerging opportunities that facilitate the transition towards net zero agriculture. Five focus themes were identified where robotics could impact sustainable food production systems to (1) increase nitrogen use efficiency, (2) accelerate plant breeding, (3) deliver regenerative agriculture, (4) electrify robotic vehicles, (5) reduce food waste. Summary: RAS technologies create opportunities to (i) optimise the use of inputs such as fertiliser, seeds, and fuel/energy; (ii) reduce the environmental impact on soil and other natural resources; (iii) improve the efficiency and precision of agricultural processes and equipment; (iv) enhance farmers’ decisions to improve crop care and reduce farm waste. Further and scaled research and technology development are needed to exploit these opportunities.

Photovoltaic Agriculture (PA) is a new management system combining industry with modern agriculture that can effectively reduce the competition for limited land resource usage between electric power production and agricultural production. However, PA has been facing the challenge of managing plant protection measures because it is difficult to monitor plants grown under the photovoltaic panels by remote sensing satellites and pesticide applications using drones. To overcome this challenge, Solar Insecticidal Lamps (SILs) can be used for phytoprotection in PA. However, to effectively use SILs in PA, it is important to identify a suitable field location to maintain strong wireless communication signals. In this paper, two testbeds were designed and a series of experiments in PA was performed. The results indicate that there is considerable interference exists around the confluence box. A higher interference seriously reduces the Packet Reception Rate (PRR) of the nearby node, which is an important constraint for deploying wireless sensors in PA. Finally, new challenges and future research opportunities are proposed.

Sorghum and maize share a close evolutionary history that can be explored through comparative genomics. To perform a large-scale comparison of the genomic variation between these two species, we analyzed 13 million variants identified from whole genome resequencing of 468 sorghum lines together with 25 million variants previously identified in 1,218 maize lines. Deleterious mutations in both species were prevalent in pericentromeric regions, enriched in non-syntenic genes, and present at low allele frequencies. A comparison of deleterious burden between sorghum and maize revealed that sorghum, in contrast to maize, departed from the “domestication cost” hypothesis that predicts a higher deleterious burden among domesticates compared to wild lines. Additionally, sorghum and maize population genetic summary statistics were used to predict a gene deleterious index with an accuracy higher than 0.5. This research represents a key step towards understanding the evolutionary dynamics of deleterious variants in sorghum and provides a comparative genomics framework to start prioritizing them for removal through genome editing and breeding.