Plant Density Research Articles

Historical increases of maize leaf area index in the US Corn Belt due primarily to plant density increases

ContextLeaf area index (LAI) and leaf area distribution within the maize plant are important traits used to explain and predict light interception and thus crop productivity. ObjectivesHere we investigate breeding and plant density effects of leaf area traits. Our objectives are to 1) quantify maize breeding impacts on leaf area distribution and determine bell-shape coefficients used in crop modeling, 2) dissect the contribution of breeding from plant density, and 3) explore the relationship between LAI and crop yields. MethodsWe studied 18 hybrids released between 1983 and 2017 at two density treatments: current (8.5 pl m-2) and historical increasing density (from 4.6 to 8.5 pl m-2) in Iowa, USA. ResultsResults indicated that concurrent changes in hybrids and increases in plant density have increased LAI from 3.4 (in 1983) to 5.9 m2 m-2 (in 2017), with the highest LAI increases (>50%) to be realized in the middle canopy. At historical increasing in plant density treatment, the LAI increased by 1.6% year-1, but the individual plant leaf area decreased by 0.33% year-1 from 1983 to 2017. This trade-off indicates that new hybrids are more tolerant to higher plant populations than old hybrids. At current plant density treatment, the year of hybrid release did not affect LAI or individual plant leaf area. New hybrids had 5% narrower leaf area distributions, 23% higher optimum LAI values (5.2 vs 4.2 m2 m-2) and 19% higher grain yields compared to old hybrids. ConclusionsThe main reason for the increase in maize LAI in the US Corn Belt is plant density. However, an increase in LAI does not necessarily translate to higher grain yields as new hybrids had significantly higher grain yields than older hybrids at similar LAI values. Present results contribute to our understanding of maize canopy architecture and allow us to better calibrate crop models to accurately estimate LAI and grain yield.

The detrimental effect of rainforest conversion to rubber plantations on soil dissolved organic carbon and C: N stoichiometry, mediated by altered soil biogeochemistry

Rainforest conversion into rubber (Hevea brasiliensis) plantations (RP) alters global carbon cycling and contributes to climate change. However, the impact of this widespread tropical land use change on various elements of the carbon cycle is poorly understood. Here, we aimed to investigate the impact of rainforest conversion into RP on soil-dissolved organic carbon (DOC), one of the most mobile organic matter (OM) in the terrestrial ecosystem that causes the transformation and migration of C. We also explored the underlying edaphic factors regulating soil DOC changes. Our study sites were rubber monoculture, mixed-rubber plantations (H. brasiliensis, Ficus langkokensis, and Actinodaphne henryi), and a reference rainforest. We found that soil DOC concentration was 150-200% higher in RP than in rainforests, with an unchanged pattern across the seasons (dry and rainy) and plantation type. These results were concomitant with degradation in main soil properties, markedly including lower pH, electrical conductivity, SOC, available nitrogen, available phosphorus, total nitrogen (TN), and total phosphorus (TP), following the RP establishment and explicitly having a significant negative correlation with DOC. Our fitted structure equation model (SEM) highlights that RP caused accelerated DOC production and a higher DOC/DN ratio by decreasing SOC (38.5%) and nutrients (TN and TP). Further, the SEM revealed a significant negative correlation between microbial biomass C (MBC) and N (MBN) and the DOC/DN ratio, implying limited microbial degradation of DOC under RP. This is further supported by our findings of 81.1% lower MBC per unit DOC and 37.1% lower MBN per unit DN under RP compared to rainforests, indicating poor transformation of DOC to microbial biomass under RP. Collectively, our findings suggest that RP with high nutrient demands and altered soil properties lead to increased leaching of DOC due to its limited utilization by microbes. These findings underscore the importance of robust and sustainable soil management (such as optimizing plant density and legume intercropping) in RP to improve soil health and minimize DOC leaching and its potential environmental consequences.

The types of growing media and plant density on the growth and yield of kailan (Brassica oleracea L.) In a floating raft system hydroponic

This research aimed to know the effect of the type of growing media and population density on the growth and yield of kailan (Brassica oleracea L.) hydroponically. The research was conducted in the greenhouse of the integrated agricultural system area at Curug Serang Banten Province. This research used a Randomized Completely Block Design (RCBD) as factorial with two factors. The first factor was the type of growing media (J) which consisted of 3 levels, J1 (Rockwool), J2 (Zeolite), and J3 (Sponge). The second factor was population density (K), which consisted of 3 treatment levels, K1 (3 plants per tub), K2 (4 plants per tub), and K3 (5 plants per tub). The results showed that the type of growing media had a significant effect on plant height growth 7 Day After Plating (DAP) of (4.67cm), 14 DAP (11.58 cm), 21 DAP (17.09 cm), 28 DAP (22.29 cm), 35 DAP (37.57 cm), number of leaves 14 DAP (4.59), 28 HST (6.96), 35 DAP (8.59) and the root weight of your plants was 35 DAP (3.43gram). Population density treatment had a significant effect on plant height growth 28 DAP (22.26 cm), 35 DAP (37,37 cm) and there was an interaction between media type treatment and population density on plant height parameters 35 DAP.

Genome-wide dissection of genes shaping inflorescence morphology in 242 Chinese south–north sorghum accessions

The inflorescences morphology (IM) of sorghum (Sorghum bicolor L. Moench) affects its resistance to pests, diseases, and grain yields. However, the specific genetic factors underlying in IM are not yet fully elucidated. Here we conducted a comprehensive genome-wide association analysis (GWAS) to identify the stable and adaptive Quantitative Trait Loci (QTL) for five IM traits (panicle length, the number of cob nodes, the number of primary branches, the largest length of the primary branch, and panicle type) in a sorghum panel, which adapted to different environments from the south to north in China. Totally, 2,015,850 high quality single nucleotide polymorphisms (SNPs) were obtained. Population structure analysis showed that two distinct genetic sub-populations were divided according to their geographic origin. Seventy-one QTLs distributed in 41 genetic regions on 9 chromosomes were identified. These regions harbored 21 high-confident candidate genes that were homologous to rice domestication genes, including 7 related to IM. Two domestication-related genes (Sobic.003G052700 and Sobic.006G247700) were located into two major QTL regions (QTL3.4721839 and QTL6.58709500) which were identified in multi-environments. Allelic variations in the two genes displayed a geographical pattern, indicating that different IM traits were selected by south and north sorghum breeders, such as south sorghums had long and loose panicles in order to adapt the hot and humid climate, while north sorghums had short and compact panicle to increase planting density and grain yield per unit area due to dry climate. This work provides new breeding strategies and resources for developing locally adapted sorghum varieties.

Photosynthetic characteristics and genetic mapping of a yellow-green leaf mutant jym165 in soybean

BackgroundLeaves are important sites for photosynthesis and can convert inorganic substances into organic matter. Photosynthetic performance is an important factor affecting crop yield. Leaf colour is closely related to photosynthesis, and leaf colour mutants are considered an ideal material for studying photosynthesis.ResultsWe obtained a yellow-green leaf mutant jym165, using ethyl methane sulfonate (EMS) mutagenesis. Physiological and biochemical analyses indicated that the contents of chlorophyll a, chlorophyll b, carotenoids, and total chlorophyll in the jym165 mutant decreased significantly compared with those in Jiyu47 (JY47). The abnormal chloroplast development of jym165 led to a decrease in net photosynthetic rate and starch content compared with that of JY47. However, quality traits analysis showed that the sum of oil and protein contents in jym165 was higher than that in JY47. In addition, the regional yield (seed spacing: 5 cm) of jym165 increased by 2.42% compared with that of JY47 under high planting density. Comparative transcriptome analysis showed that the yellow-green leaf phenotype was closely related to photosynthesis and starch and sugar metabolism pathways. Genetic analysis suggests that the yellow-green leaf phenotype is controlled by a single recessive nuclear gene. Using Mutmap sequencing, the candidate regions related of leaf colour was narrowed to 3.44 Mb on Chr 10.ConclusionsAbnormal chloroplast development in yellow-green mutants leads to a decrease in the photosynthetic pigment content and net photosynthetic rate, which affects the soybean photosynthesis pathway and starch and sugar metabolism pathways. Moreover, it has the potentiality to increase soybean yield under dense planting conditions. This study provides a useful reference for studying the molecular mechanisms underlying photosynthesis in soybean.

Planting Density and Sowing Date Strongly Influence Canopy Characteristics and Seed Yield of Soybean in Southern Xinjiang

Southern Xinjiang is an important soybean production region in China. However, the short growing season and the cultivation of winter crops (such as wheat) in the region limit the expansion of soybean planting areas. An increased planting density can compensate for the loss in yield due to delayed sowing. To identify the quantitative relationship between increased density and delayed days, a two-year field experiment was conducted at the Tarim University Agronomy Experiment Station. Two sowing dates (April 7 (S1) and May 7 (S2)) and three planting densities of 206,800 plants·ha−1 (D1), 308,600 plants·ha−1 (D2), and 510,200 plants·ha−1 (D3) were used to compare various plant growth parameters and canopy characteristics. Late sowing and a high planting density significantly increased the plant height (S2 was 37.3% higher than S1, and D3 was 17.6% and 8.8% higher than D1 and D2), main stem internode, petiole length, and the mean tilt angle of the leaves (S2 was 22.5% higher than S1, and D3 was 11.7% higher than D2) but reduced the stem diameter (D3 was 28.6% and 12.5% lower than D1 and D2), branch number (S2 was 26.7% lower than S1, and D2 was 75% lower than D1), canopy light transmittance (S2 was 49.2% lower than S1, and D3 was 36.7% and 20.8% lower than D1 and D2), photosynthetic rate, and dry matter. The highest yield was achieved at S1D1, but the lowest yield was found for S2D1. Overall, the results suggest that earlier sowing and a lower planting density contribute to achieving an optimum canopy structure and higher yield. Our conclusions provide a reference for soybean production in southern Xinjiang.

Sugar transporter modulates nitrogen-determined tillering and yield formation in rice

Nitrogen (N) fertilizer application ensures crop production and food security worldwide. N-controlled boosting of shoot branching that is also referred as tillering can improve planting density for increasing grain yield of cereals. Here, we report that Sugar Transporter Protein 28 (OsSTP28) as a key regulator of N-responsive tillering and yield formation in rice. N supply inhibits the expression of OsSTP28, resulting in glucose accumulation in the apoplast of tiller buds, which in turn suppresses the expression of a transcriptional inhibitor ORYZA SATIVA HOMEOBOX 15 (OSH15) via an epigenetic mechanism to activate gibberellin 2-oxidases (GA2oxs)-facilitated gibberellin catabolism in shoot base. Thereby, OsSTP28-OSH15-GA2oxs module reduces the level of bioactive gibberellin in shoot base upon increased N supply, and consequently promotes tillering and grain yield. Moreover, we identify an elite allele of OsSTP28 that can effectively promote N-responsive tillering and yield formation, thus representing a valuable breeding target of N use efficiency improvement for agricultural sustainability.

Cultivation Technology and Plant Density Affecting the Yield and Carotenoid Content of Beauregard Sweet Potato

Cultivation Technology and Plant Density Affecting the Yield and Carotenoid Content of Beauregard Sweet Potato

Plant Photosynthetic and Respiration Rates Are Key Populational Traits to Improve Yield and Quality for Good-Tasting Double-Cropped Rice

Improving the yield and quality for tasty rice varieties is a great challenge. In the present study, different nitrogen rates and plant density were utilized to form differential rice populational structures, which were determined to clarify key traits determining grain yield and quality for tasty rice varieties in a double-cropped rice system in subtropical China. The present results showed that the plant photosynthetic rate, leaf area index and plant respiration rate had important and significant impacts on the grain yields of both early and late rice, though the late rice yield was also significantly affected by the canopy temperature. In addition, among the studied populational traits, plant photosynthetic and/or respiration rates had significant effects on all quality traits. Consistently, grain yield and quality were significantly improved with the increasing plant photosynthetic and respiration rates through correlative analysis, which was also observed in principal components analysis. Overall, the present study suggests that both the grain yield and milling and appearance qualities could be improved through the optimal management of nitrogen and plant density through increasing plant photosynthetic and respiration rates.

Oceanographic‐informed coral out‐planting density for coral reef restoration activities

Out‐planting corals onto coral reefs as a mechanism to increase coral cover on degraded reef systems is an increasing global activity. Current practices typically focus on asexual out‐planting of coral fragments (coral gardening). Newer sexual reproductive approaches are being developed to out‐plant younger corals produced in aquaculture facilities or sea‐based rearing pools to enable assisted evolution or assisted gene flow conservation genetics approaches. Designing out‐planting deployment operations requires decisions to be made on planting density and location in order to maximize future recruitment on both the out‐planted reefs, and on nearby reefs that are connected through oceanographic transport processes. The thinking presented here seeks to unpack how out‐planting density may be influenced, especially by local oceanographic conditions, in order to guide practitioners undertaking restoration projects.

Genomic prediction of cereal crop architectural traits using models informed by gene regulatory circuitries from maize.

Plant architecture is a major determinant of planting density, which enhances productivity potential for crops per unit area. Genomic prediction is well positioned to expedite genetic gain of plant architectural traits since they are typically highly heritable. Additionally, the adaptation of genomic prediction models to query predictive abilities of markers tagging certain genomic regions could shed light on the genetic architecture of these traits. Here, we leveraged transcriptional networks from a prior study that contextually described developmental progression during tassel and leaf organogenesis in maize (Zea mays) to inform genomic prediction models for architectural traits. Since these developmental processes underlie tassel branching and leaf angle, 2 important agronomic architectural traits, we tested whether genes prioritized from these networks quantitatively contribute to the genetic architecture of these traits. We used genomic prediction models to evaluate the ability of markers in the vicinity of prioritized network genes to predict breeding values of tassel branching and leaf angle traits for 2 diversity panels in maize and diversity panels from sorghum (Sorghum bicolor) and rice (Oryza sativa). Predictive abilities of markers near these prioritized network genes were similar to those using whole-genome marker sets. Notably, markers near highly connected transcription factors from core network motifs in maize yielded predictive abilities that were significantly greater than expected by chance in not only maize but also closely related sorghum. We expect that these highly connected regulators are key drivers of architectural variation that are conserved across closely related cereal crop species.

Influence of Spatial Scale Effect on UAV Remote Sensing Accuracy in Identifying Chinese Cabbage (Brassica rapa subsp. Pekinensis) Plants

The exploration of the impact of different spatial scales on the low-altitude remote sensing identification of Chinese cabbage (Brassica rapa subsp. Pekinensis) plants offers important theoretical reference value in balancing the accuracy of plant identification with work efficiency. This study focuses on Chinese cabbage plants during the rosette stage; RGB images were obtained by drones at different flight heights (20 m, 30 m, 40 m, 50 m, 60 m, and 70 m). Spectral sampling analysis was conducted on different ground backgrounds to assess their separability. Based on the four commonly used vegetation indices for crop recognition, the Excess Green Index (ExG), Red Green Ratio Index (RGRI), Green Leaf Index (GLI), and Excess Green Minus Excess Red Index (ExG-ExR), the optimal index was selected for extraction. Image processing methods such as frequency domain filtering, threshold segmentation, and morphological filtering were used to reduce the impact of weed and mulch noise on recognition accuracy. The recognition results were vectorized and combined with field data for the statistical verification of accuracy. The research results show that (1) the ExG can effectively distinguish between soil, mulch, and Chinese cabbage plants; (2) images of different spatial resolutions differ in the optimal type of frequency domain filtering and convolution kernel size, and the threshold segmentation effect also varies; (3) as the spatial resolution of the imagery decreases, the optimal window size for morphological filtering also decreases, accordingly; and (4) at a flight height of 30 m to 50 m, the recognition effect is the best, achieving a balance between recognition accuracy and coverage efficiency. The method proposed in this paper is beneficial for agricultural growers and managers in carrying out precision planting management and planting structure optimization analysis and can aid in the timely adjustment of planting density or layout to improve land use efficiency and optimize resource utilization.

Relationship between root characteristics and saturated hydraulic conductivity in a grassed clayey soil

Soil saturated hydraulic conductivity plays a crucial role in the fields of hydrology, geotechnical and geological engineering. This study investigated the relationship between root characteristics and soil saturated hydraulic conductivity in a grassed soil. The saturated hydraulic conductivity of soil specimens with varying soil dry densities and planting densities were experimentally determined. Root parameters of each specimen were measured, and the relationship between root parameters and soil saturated hydraulic conductivity was determined through the stepwise multiple regression analysis. Experimental results show that both soil dry density and planting density significantly influence root growth and the saturated hydraulic conductivity of the grassed soil. Root length ratio (>4 cm), root length, and root weight density exhibit a positive correlation with planting density, while root length density and root length ratio (>4 cm) are negatively correlated with dry density. Higher dry density leads to lower soil saturated hydraulic conductivity and the permeable effects become more pronounced with increased planting density. When planting density is higher, roots create more preferential flow channels in the soil, resulting in increased soil saturated hydraulic conductivity. Root length density exerts the most significant effect on soil saturated hydraulic conductivity (|r| = 0.82, p＜0.01), followed by root length ratio (>4 cm) and root weight density. This study provides insights into the relationship between root parameters and soil saturated hydraulic conductivity, and identifies key root parameters that govern the saturated hydraulic conductivity of soil. These findings hold significant implications for enhancing the understanding of slope protection using vegetation.

Optimizing Planting Density, Irrigation, and Nitrogen Application Can Improve Rapeseed Yield in Xinjiang’s Aksu by Reducing the Lodging Rate

This study aimed to investigate the effects of planting density, irrigation volume, and nitrogen application on the resistance of rapeseed to lodging and yield and to provide technical support for achieving high yield and lodging resistance. We employed an L9 (34) orthogonal array, different planting densities, irrigation levels, and nitrogen applications to investigate their impact on rapeseed lodging and yield. The results showed the following: (1) Irrigation had the greatest effect on rapeseed lodging. This effect was most pronounced for the combination (A3B3C2), which exhibited the most severe lodging phenomenon (90%). Planting density had the greatest effect on yield, and the optimal combination was A2B2C3, which reached 3744 kg/hm2 in 2023 and 3420 kg/hm2 in 2024. (2) The agronomic practices increased the content of lignin, cellulose, hemicellulose, crude fiber, pectin, and soluble sugar fractions in the stalks by enhancing their flexural, puncture, and stress resistance. This led to the highest yield while reducing the rate of lodging. This emphasizes the importance of agricultural practices for rapeseed lodging and yield, providing critical insights into rapeseed cultivation in the Aksu region of Xinjiang.

Correlations between Tree/Shrub Diversity and Herbaceous Biomass with Soil Physico-chemical Properties under Acacia saligna Canopy

Acacia saligna (A. saligna) is originated from South Western Australia, and it was brought to the Tigray region of Ethiopia in 1972 with the intention of restoring the ecosystem and conserving soil and water. This study aims to evaluate the correlations between tree/shrub diversity and herbaceous biomass with some soil physico-chemical properties under Acacia saligna canopy and away from the canopy in Atsibi Wemberta district, Tigray, Ethiopia. For collecting of vegetation data, herbaceous cover and soil sample, twelve A.saligna tree stands were used as a replication.Woody species identification, herbaceous cover and biomass production were collected under the canopy of A.saligna and 50 m away from the canopy at 1 m2 for woody species, and 0.25 m2 for herbaceous cover, and biomass production. Soil samples were taken using auger at 20 cm soil depth under the canopy and in the canopy gap A.saligna. The species richness under the canopy of A.saligna was positively insignificant correlated with pH (r = 0.48, p = 0.11), availability of phosphorus (Av.P) (r = 0.16, p = 0.63), total nitrogen (TN (r = 0.12, p = 0.7) and Silt (r = 0.71, p = 0.009). However, it is also negatively correlated with soil organic carbon (SOC (r = -0.06, p = 0.85), and sand (r = -0.77, p = 0.003). The Pearson’s correlation matrix in the canopy gap of A.saligna showed that, Shannon diversity index is insignificantly positively correlated with SOC (r = 0.19, p = 0.53), Av.P (r = 0.46, p = 0.12), availability of potassium (Av.K) (r = 0.43, p = 0.16) and TN (r = 0.13, p = 0.69). However, species richness and Shannon diversity index have insignificantly negatively correlated with pH(r = -0.13, p = 0.68, r = -0.15, p = 0.63) and sand (r = -0.23, p = 0.51, r = -0.44, p = 0.14), respectively. In the canopy gap of A.saligna, the herbaceous biomass was positively correlated with Av.K (r = 0.47, p = 0.12), silt (r = 0.39, p = 0.20), and clay( r = 0.37, p = 0.24), but the Pearson’s correlation matrix between herbaceous biomass and some soil parameters in the canopy gap is observed to be insignificantly negatively correlated with pH (r = -0.24, p = 0.44), SOC (r = -0.04, p = 0.9), Av.P (r = -0.34, p = 0.28), and TN (r = -0.33, p = 0.31).The species richness, Shannon diversity indexes and herbaceous biomass were insignificantly positively correlated with pH under the canopy of A.saligna, but for similar parameters in the canopy gap was observed negatively insignificant correlated with pH. Overall, the small positive correlation found in the current study between same soil physico chemical and diversity indexes under the A. saligna canopy suggests that the presence of these large A. saligna trees may increase soil nutrient availability through litterfall. The study found clear relationships between plant density and Shannon diversity with herbaceous biomass in Acacia saligna's canopy gap and beneath its canopy. In particular, both settings showed a substantial negative connection between herbaceous biomass and plant density, suggesting that increased plant density tends to diminish herbaceous biomass. On the other hand, a strong positive association was seen between Shannon diversity and herbaceous biomass, indicating that higher species diversity is linked to higher herbaceous biomass. Therefore, it is imperative to manage and conserve A. saligna and the woody species growing beneath the canopy in order to preserve and strengthen the favorable connections that exist between diversity indexes and the physical and chemical characteristics of soil.

Forest and Biodiversity 2: A tree diversity experiment to understand the consequences of multiple dimensions of diversity and composition for long‐term ecosystem function and resilience

Abstract We introduce a new “ecosystem‐scale” experiment at the Cedar Creek Ecosystem Science Reserve in central Minnesota, USA to test long‐term ecosystem consequences of tree diversity and composition. The experiment—the largest of its kind in North America—was designed to provide guidance on forest restoration efforts that will advance carbon sequestration goals and contribute to biodiversity conservation and sustainability. The new Forest and Biodiversity (FAB2) experiment uses native tree species in varying levels of species richness, phylogenetic diversity and functional diversity planted in 100 m2 and 400 m2 plots at 1 m spacing, appropriate for testing long‐term ecosystem consequences. FAB2 was designed and established in conjunction with a prior experiment (FAB1) in which the same set of 12 species was planted in 16 m2 plots at 0.5 m spacing. Both are adjacent to the BioDIV prairie‐grassland diversity experiment, enabling comparative investigations of diversity and ecosystem function relationships between experimental grasslands and forests at different planting densities and plot sizes. Within the first 6 years, mortality in 400 m2 monoculture plots was higher than in 100 m2 plots. The highest mortality occurred in Tilia americana and Acer negundo monocultures, but mortality for both species decreased with increasing plot diversity. These results demonstrate the importance of forest diversity in reducing mortality in some species and point to potential mechanisms, including light and drought stress, that cause tree mortality in vulnerable monocultures. The experiment highlights challenges to maintaining monoculture and low‐diversity treatments in tree mixture experiments of large extent. FAB2 provides a long‐term platform to test the mechanisms and processes that contribute to forest stability and ecosystem productivity in changing environments. Its ecosystem‐scale design, and accompanying R package, are designed to discern species and lineage effects and multiple dimensions of diversity to inform restoration of ecosystem functions and services from forests. It also provides a platform for improving remote sensing approaches, including Uncrewed Aerial Vehicles (UAVs) equipped with LiDAR, multispectral and hyperspectral sensors, to complement ground‐based monitoring. We aim for the experiment to contribute to international efforts to monitor and manage forests in the face of global change.

Phenotypic characterization and genetic mapping of the semi-dwarf mutant sdw9 in maize.

In summary, we characterized a maize semi-dwarf mutant, sdw9, and successfully isolated the responsible gene, which encodes a GRAS protein, through a combination of map-based cloning and Re-sequencing (Re-seq). Our findings demonstrate that the candidate gene ZmGRAS42 regulates BR signaling genes, thereby influencing internode development. This regulatory function likely involves processes such as cell division, cell cycle regulation and cell wall synthesis. Favorable variations of ZmGRAS42 identified in this study may hold promise for the development of lodging-resistant maize cultivars suitable for high-density planting, contributing to the improvement of maize breeding programs. Plant height and lateral root angle are crucial determinants of plant architecture in maize (Zea mays) which are closely related to lodging resistance at high planting density. These traits are intricately regulated by various phytohormones. Mutations affecting hormone biosynthesis and signaling often lead to reduced yield alongside diminished plant height, posing challenges in breeding dwarf maize varieties. In this study, the maize mutant sdw9 was characterized, which displays shorter stature and altered lateral root angle compared to WT, while showing potential to increase planting density and improve overall yield despite a slight reduction in single-ear yield. Employing positional cloning coupled with Re-seq techniques, we pinpointed a transposon insertion in the candidate gene ZmGRAS42, which encodes a GRAS transcription factor involved in BR signaling in maize. Transcriptome analysis revealed that ZmGRAS42 orchestrates the expression of several known dwarfing genes such as D8, Br2, and Na2, along with genes associated with cell wall organization, cell division, and cell cycle regulation, notably Cesa4, Cesa7, and Cyc11. Furthermore, identification of favorable ZmGRAS42 haplotypes linked to reduced plant height offers novel avenues for maize breeding strategies. These findings not only hold the potential for enhancing maize lodging resistance but also for optimizing land utilization through high-density planting practices.

Morphology and Allometry of Juvenile Açaí Palms Under Cultivation Conditions in Central Amazonia

Two Amazonian species of açaí palm trees (Euterpe oleracea and Euterpe precatoria) are exploited in the commercial production of açaí pulp or juice. While E. oleracea benefits from developed cultivation technologies, E. precatoria lacks such advancements. Studies on the morphology and development of açaí palms under cultivation conditions can contribute to increasing the productivity of the species. The aim of this study was to carry out morphological characterization, assess growth and development in the juvenile phase of the plants, and obtain allometric models for E. precatoria and E. oleracea. Evaluations were conducted between 44 and 48 months post-planting. Allometric equations were formulated to accurately estimate leaf area. The results showed that E. oleracea begins reproduction earlier and exhibits greater growth in stem dimensions and leaf areas compared to E. precatoria, indicating that E. precatoria can be cultivated at higher planting densities. Allometric models, based on leaf length and width, effectively predicted individual leaf areas for both species, demonstrating their utility in optimizing cultivation strategies.

Fruit Distribution Density Estimation in YOLO-Detected Strawberry Images: A Kernel Density and Nearest Neighbor Analysis Approach

Precise information on strawberry fruit distribution is of significant importance for optimizing planting density and formulating harvesting strategies. This study applied a combined analysis of kernel density estimation and nearest neighbor techniques to estimate fruit distribution density from YOLOdetected strawberry images. Initially, an improved yolov8n strawberry object detection model was employed to obtain the coordinates of the fruit centers in the images. The results indicated that the improved model achieved an accuracy of 94.7% with an mAP@0.5~0.95 of 87.3%. The relative error between the predicted and annotated coordinates ranged from 0.002 to 0.02, demonstrating high consistency between the model predictions and the annotated results. Subsequently, based on the strawberry center coordinates, the kernel density estimation algorithm was used to estimate the distribution density in the strawberry images. The results showed that with a bandwidth of 200, the kernel density estimation accurately reflected the actual strawberry density distribution, ensuring that all center points in high-density regions were consistently identified and delineated. Finally, to refine the strawberry distribution information, a comprehensive method based on nearest neighbor analysis was adopted, achieving target area segmentation and regional density estimation in the strawberry images. Experimental results demonstrated that when the distance threshold ϵ was set to 600 pixels, the correct grouping rate exceeded 94%, and the regional density estimation results indicated a significant positive correlation between the number of fruits and regional density. This study provides scientific evidence for optimizing strawberry planting density and formulating harvesting sequences, contributing to improved yield, harvesting efficiency, and reduced fruit damage. In future research, this study will further explore dynamic models that link fruit distribution density, planting density, and fruit growth status.

Effect of Tree Density on Yield and Fruit Quality of the Grafted Hazelnut Cultivar 'Tonda Francescana®'.

Optimizing planting density is crucial for balancing resource competition, light penetration, and tree productivity in orchard systems. This study investigateed the impact of planting density on the yield and fruit quality of the hazelnut cultivar 'Tonda Francescana®' grafted onto Corylus colurna L. rootstocks. The research aimed to assess how different planting densities influenced light penetration, canopy volume, yield, and the nutritional profile of hazelnuts during their sixth growing season. Three planting densities were tested: 625, 1250, and 2500 trees per hectare (low, medium, and high density, respectively). The results show that medium-density planting provided the best balance between light availability, canopy development, and yield efficiency. The synthesis of monounsaturated fatty acids (MUFA) and α-tocopherol (vitamin E) was more prominent in the medium-density system (80.2% and 10.3%, respectively), suggesting a favorable metabolic response to moderate competition for resources. In contrast, high-density planting yielded the most per hectare (2898 kg/ha) but exhibited lower individual tree productivity (1.16 kg). Low-density planting had the highest light penetration (53%) but lower overall yield (822 kg/ha) and quality, with greater starch accumulation in the fruit. In general, medium-density planting optimized both yield and kernel quality, with potential implications for orchard management and breeding strategies to enhance hazelnut production and nutritional value.