Heading Stage Research Articles

Estimation Model of Rice Aboveground Dry Biomass Based on the Machine Learning and Hyperspectral Characteristic Parameters of the Canopy

Accurately estimating aboveground dry biomass (ADB) is crucial. The ADB of rice has primarily been estimated using vegetation indices with several discrete bands; nevertheless, these indices cannot take advantage of continuous bands available with hyperspectral remote sensing. This study analyzed the quantitative relationship between canopy hyperspectral characteristic parameters (HCPs) and the ADB of rice. Twenty HCPs were used, including red edge area (SDr), blue edge area (SDb), and others. The variable-screening methods involved stepwise regression (SR), a regression coefficient (RC), variable importance in projection (vip), and random forest (RF). Stepwise and partial least squares regression methods were employed with traditional linear regression as well as machine learning methods including random forest (RF), a support vector machine (SVM), a BP artificial neural network (BPNN), and an extreme learning machine. Whole- and screening-variable models were constructed to estimate rice ADB at jointing, booting, heading, and maturing stages and across growth stages. Screening-variable models include SVM models based on SR (SVM-sr), RF models based on vip (RF-vip), and others. The results show that the HCPs had a significant correlation with ADB containing elements in the red edge region, namely SDr, SDr/SDb, and (SDr − SDb)/(SDr + SDb) at each growth stage. In addition, the screening performance of vip and SR was better than that of RC and RF, and fewer variables were screened. Moreover, the HCPs of the red edge region were screened using different screening methods at each growth stage. Among them, SDr/SDb and (SDr − SDb)/(SDr + SDb) appeared frequently, indicating they are important. Furthermore, at each growth stage, ADB could be well-estimated using diverse models with the RF modeling method based on vip screening variables found to be the best modeling method for ADB estimation; the independent variables of the RF-vip model involved the (SDr − SDb)/(SDr + SDb) at each growth stage.

Enhancing Wheat Above-Ground Biomass Estimation Using UAV RGB Images and Machine Learning: Multi-Feature Combinations, Flight Height, and Algorithm Implications

Above-ground biomass (AGB) serves as an indicator of crop growth status, and acquiring timely AGB information is crucial for estimating crop yield and determining appropriate water and fertilizer inputs. Unmanned Aerial Vehicles (UAVs) equipped with RGB cameras offer an affordable and practical solution for efficiently obtaining crop AGB. However, traditional vegetation indices (VIs) alone are insufficient in capturing crop canopy structure, leading to poor estimation accuracy. Moreover, different flight heights and machine learning algorithms can impact estimation accuracy. Therefore, this study aims to enhance wheat AGB estimation accuracy by combining VIs, crop height, and texture features while investigating the influence of flight height and machine learning algorithms on estimation. During the heading and grain-filling stages of wheat, wheat AGB data and UAV RGB images were collected at flight heights of 30 m, 60 m, and 90 m. Machine learning algorithms, including Random Forest Regression (RFR), Gradient Boosting Regression Trees (GBRT), Ridge Regression (RR), Least Absolute Shrinkage and Selection Operator (Lasso) and Support Vector Regression (SVR), were utilized to construct wheat AGB estimation models. The research findings are as follows: (1) Estimation accuracy using VIs alone is relatively low, with R2 values ranging from 0.519 to 0.695. However, combining VIs with crop height and texture features improves estimation accuracy, with R2 values reaching 0.845 to 0.852. (2) Estimation accuracy gradually decreases with increasing flight height, resulting in R2 values of 0.519–0.852, 0.438–0.837, and 0.445–0.827 for flight heights of 30 m, 60 m, and 90 m, respectively. (3) The choice of machine learning algorithm significantly influences estimation accuracy, with RFR outperforming other machine learnings. In conclusion, UAV RGB images contain valuable crop canopy information, and effectively utilizing this information in conjunction with machine learning algorithms enables accurate wheat AGB estimation, providing a new approach for precision agriculture management using UAV remote sensing technology.

Exogenous Application of Methyl Jasmonate Promotes Yield and Grain Quality of Rice under Terminal Drought Stress

Exogenous application of methyl jasmonate (MeJA) improves rice drought tolerance, but its effects on rice yield and quality under drought stress during the reproductive phase remain unclear. A pot experiment was conducted to measure rice yield, grain quality, and starch physicochemical properties under three treatments: continuous flooding irrigation throughout the whole growth season (CF), ten days of −40 kPa drought stress at the heading stage (DS), and foliar spraying 100 μmol L−1 MeJA on the first three days of the ten-day −40 kPa heading stage drought stress (DM). An inbred japonica rice variety, Huaidao 5, was the experimental material, and each treatment had 11 replicates for sampling. The results indicated that DS significantly reduced rice yield and quality compared to CF. With increases in superoxide dismutase (+22.2%), peroxidase activities (+10.5%), catalase (+5.0%), and proline content (+5.7%), DM significantly increased 1000-grain weight (+8.6%), filled grain percentage (+3.6%), and yield (+11.1%) compared with DS. Regarding grain quality, DM significantly decreased the chalkiness degree (−12.3%) and protein content (−3.9%) but increased the amylose content (+17.2%) and taste value (+7.3%) relative to DS. In addition, DM improved breakdown viscosity (+17.8%), gelatinization enthalpy (+17.2%), retrogradation enthalpy (+28.0%), 1045/1022 cm−1 ratio (+3.0%), and starch granule morphology compared to DS. In conclusion, exogenous application of 100 μmol L−1 MeJA enhanced the antioxidant capacity of rice leaves, and thus improved starch physicochemical properties to increase grain yield and quality under terminal drought stress.

Nitrogen fertilizer alleviates rice yield loss without increasing global warming potential under elevated temperatures

The adverse impacts of climate warming on rice production have become increasingly evident. In this regard, although our previous field studies enabled us to establish the positive impacts of nitrogen fertilizer on rice grain yield during warming, it remains necessary to clarify whether nitrogen fertilizer under elevated temperatures has any adverse effects on the environment during the grain-filling stage. To further investigate the impacts of nitrogen fertilizer on rice yield and the associated emissions of methane (CH4) and nitrous oxide (N2O) under elevated temperatures, we conducted a 2-year paddy field study using a free-air temperature enhancement (FATE) system. FATE system had a favorable warming effect on the canopy and soil, and greatly decreased grain yield by 23 % on average. In two trial years, elevated temperatures significantly increased in CH4 emissions by 17.7 kg ha−1and 18.9 kg ha−1, but did not affect N2O emissions. Consequently, we detected significant increases in global warming potential (GWP) by 52 % and 19 % and greenhouse gas intensity (GHGI) by 94 % and 56 % under elevated temperatures in 2019 and 2020, respectively. Although nitrogen fertilizer had no significant influence on CH4 emissions under elevated temperatures, N2O emissions significantly increased by 1.5 kg ha−1 and 1.4 kg ha−1 in 2019 and 2020. Nevertheless, nitrogen fertilizer did not affect GWP and significantly decreased GHGI by 10 % under elevated temperatures in 2020. Additionally, elevated temperatures significantly increased the abundance of methanogens (mcrA), ammonia-oxidizing bacteria (AOB), ammonia-oxidizing archaea (AOA), and nitrous oxide reductase (nosZ) genes. Whereas, nitrogen fertilizer significantly increased nitrite reductase (nirS) gene abundance under elevated temperatures. In conclusion, our findings indicated that 60 kg N ha−1 at the heading stage could effectively alleviate the reduction in grain yield attributable to elevated temperatures, without increasing GWP, thereby enhancing the economic and environmental sustainability of paddy field system.

Shifts in the diversity of root endophytic microorganisms across the life cycle of the ratooning rice Jiafuzhan.

The diversity of root endophytic microorganisms, which is closely related to plant life activities, is known to vary with the plant growth stage. This study on the ratooning rice Jiafuzhan explored the diversity of the root endophytic bacteria and fungi and their dynamics during the plant life cycle. By sequencing the 16S ribosomal ribonucleic acid (16S rRNA) and internal transcribed spacer (ITS) genes, 12,154 operational taxonomic units (OTUs) and 497 amplicon sequence variants (ASVs) were obtained, respectively. The root endophytic microorganisms of rice in the seedling, tillering, jointing, heading, and mature stages of the first crop and at 13, 25, and 60 days after regeneration (at the heading, full heading, and mature stages of the second crop, respectively) were analyzed using diversity and correlation analyses. There were significant differences in the α-diversity and β-diversity of root endophytic bacteria and fungi in the growth stage. Additionally, linear discriminant analysis (LDA) effect size (LEfSe) analysis revealed biomarker bacteria for each growth stage, but biomarker fungi did not exist in every stage. Moreover, the correlation analysis showed that the bacterial and fungal biomarkers interacted with each other. Furthermore, the nitrogen-fixing genus Bradyrhizobium existed in all growth stages. These findings indicate the pattern of root endophytic microorganisms of ratooning rice at different growth stages, and they provide new insights into the high yield of the second crop of ratooning rice (in light of the abundance of various bacteria and fungi).

RNA-Seq Transcriptome Analysis and Evolution of OsEBS, a Gene Involved in Enhanced Spikelet Number per Panicle in Rice.

Spikelet number per panicle (SNP) is one of the most important yield components in rice. Rice ENHANCING BIOMASS AND SPIKELET NUMBER (OsEBS), a gene involved in improved SNP and yield, has been cloned from an accession of Dongxiang wild rice. However, the mechanism of OsEBS increasing rice SNP is poorly understood. In this study, the RNA-Seq technology was used to analyze the transcriptome of wildtype Guichao 2 and OsEBS over-expression line B102 at the heading stage, and analysis of the evolution of OsEBS was also conducted. A total of 5369 differentially expressed genes (DEGs) were identified between Guichao2 and B102, most of which were down-regulated in B102. Analysis of the expression of endogenous hormone-related genes revealed that 63 auxin-related genes were significantly down-regulated in B102. Gene Ontogeny (GO) enrichment analysis showed that the 63 DEGs were mainly enriched in eight GO terms, including auxin-activated signaling pathway, auxin polar transport, auxin transport, basipetal auxin transport, and amino acid transmembrane transport, most of which were directly or indirectly related to polar auxin transport. Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathway analysis further verified that the down-regulated genes related to polar auxin transport had important effects on increased SNP. Analysis of the evolution of OsEBS found that OsEBS was involved in the differentiation of indica and japonica, and the differentiation of OsEBS supported the multi-origin model of rice domestication. Indica (XI) subspecies harbored higher nucleotide diversity than japonica (GJ) subspecies in the OsEBS region, and XI experienced strong balancing selection during evolution, while selection in GJ was neutral. The degree of genetic differentiation between GJ and Bas subspecies was the smallest, while it was the highest between GJ and Aus. Phylogenetic analysis of the Hsp70 family in O. sativa, Brachypodium distachyon, and Arabidopsis thaliana indicated that changes in the sequences of OsEBS were accelerated during evolution. Accelerated evolution and domain loss in OsEBS resulted in neofunctionalization. The results obtained from this study provide an important theoretical basis for high-yield rice breeding.

Foliar application of glutamate and phenylalanine induced regulation in yield, protein components, aroma, and metabolites in fragrant rice

Amino acids are a type of organic nutrient essential for plant growth and can be used as fertilizer in agriculture. However, the effects of foliar application of amino acids on fragrant rice performances have rarely been reported. In the present study, glutamate and phenylalanine were foliar applied to fragrant rice plants at the initial heading stage in a two-year field experiment. The grain yield, yield-related traits, grain quality parameters, volatiles, and chlorophyll were determined. An untargeted metabolomics analysis using LC-MS was used to further explore the regulation mechanism. The results showed that foliar application of glutamate and phenylalanine significantly increased the seed-setting rate, grain yield, and the contents of chlorophyll a, chlorophyll b, and carotenoid. GC-MS analysis showed that volatiles including 2-acetyl-1-pyrroline, heptanal, 2-pentylfuran, and D-limonene, were significantly affected by glutamate and/or phenylalanine. Higher grain 2-acetyl-1-pyrroline content was observed in phenylalanine treatment in both years. Glutamate treatment significantly increased globulin, prolamin, and glutelin contents. Untargeted metabolomics analysis showed that glutamate regulated 104 metabolites in leaves and 93 metabolites in grains, and phenylalanine regulated 132 metabolites in leaves and 123 metabolites in grains.

Impact of Two Phosphorus Fertilizer Formulations on Wheat Physiology, Rhizosphere, and Rhizoplane Microbiota.

Phosphorus (P) is the second most important macronutrient for crop growth and a limiting factor in food production. Choosing the right P fertilizer formulation is important for crop production systems because P is not mobile in soils, and placing phosphate fertilizers is a major management decision. In addition, root microorganisms play an important role in helping phosphorus fertilization management by regulating soil properties and fertility through different pathways. Our study evaluated the impact of two phosphorous formulations (polyphosphates and orthophosphates) on physiological traits of wheat related to yield (photosynthetic parameters, biomass, and root morphology) and its associated microbiota. A greenhouse experiment was conducted using agricultural soil deficient in P (1.49%). Phenotyping technologies were used at the tillering, stem elongation, heading, flowering, and grain-filling stages. The evaluation of wheat physiological traits revealed highly significant differences between treated and untreated plants but not between phosphorous fertilizers. High-throughput sequencing technologies were applied to analyse the wheat rhizosphere and rhizoplane microbiota at the tillering and the grain-filling growth stages. The alpha- and beta-diversity analyses of bacterial and fungal microbiota revealed differences between fertilized and non-fertilized wheat, rhizosphere, and rhizoplane, and the tillering and grain-filling growth stages. Our study provides new information on the composition of the wheat microbiota in the rhizosphere and rhizoplane during growth stages (Z39 and Z69) under polyphosphate and orthophosphate fertilization. Hence, a deeper understanding of this interaction could provide better insights into managing microbial communities to promote beneficial plant-microbiome interactions for P uptake.

Inorganic and Natural Silicon Sources as Soil Amendment on Growth of Local Aromatic Rice Variety

Lodging causes a yield loss of approximately 1 ton per hectare as 20% of the total rice production. Silicon(Si) fertilisers significantly improve paddy grain yield, and lodging resistance by improving leaf firmnessbesides promoting better plant canopy and boosting photosynthesis. The objective of this study was todetermine the effects of Si derived from calcium silicate (CaSiO3), rice husk ash, and rice straw on paddyplant growth. A pot study was conducted at MARDI Seberang Perai during the main season (2019/2020)and the off-season (2020) using the MRQ 76 rice variety to evaluate 10 Si carriers. The growth parametersof the paddy plants such as number of tillers, plant height, and chlorophyll content at different growth stageswere evaluated. During season 1, treatment with 100% CaSiO3 (T4) significantly improved the plant height.Nevertheless, the organic Si (T1, T2, and T3) and combination between organic Si with CaSiO3 (T5, T6,T7, and T8) resulted in the tallest plants during season 2. Treatment T7 increased the tillering number permeter square during season 1 whereas in season 2 treatment T8 performed better compared to the standardfertiliser (T9) and control (T10). However, the treatments evaluated in this study did not significantly affectthe chlorophyll content of the paddy plants. Applying a combination of rice straw (50%) and rice husk ash(50%) a day before transplanting, followed by CaSiO3 (100%) as a silicate material during panicle initiation,along with additional NPK fertiliser (17:3:25:2MgO) during heading stage (T7), and without additionalNPK fertiliser (17:3:25:2MgO) at the heading stage (T8) were most effective in enhancing crop growth andmaintaining the paddy cultivation. Therefore, the findings in this study suggested the potential of usinginorganic and organic Si to improve the growth and development of aromatic rice variety.

Morpho-physiological responses and growth indices of triticale to drought and salt stresses

Salinity and drought are two major abiotic stresses challenging global crop production and food security. In this study, the effects of individual and combined effects of drought (at different phenological stages) and salt stresses on growth, morphology, and physiology of triticale were evaluated. For this purpose, a 3 x 4 factorial design in three blocks experiment was conducted. The stress treatments included three levels of salinity (0, 50, and 100 mM NaCl) and four levels of drought (regular irrigation as well as irrigation disruption at heading, flowering, and kernel extension stages). The stresses, individual as well as combined, caused a significant decrease in chlorophyll contents, total dry matter, leaf area index, relative water content, and grain yield of triticale. In this regard, the highest reduction was recorded under combined stresses of 100 mM NaCl and drought stress at flowering. However, an increase in soluble sugars, leaf free proline, carotenoid contents, and electrolyte leakage was noted under stress conditions compared to the control. In this regard, the highest increase in leaf free proline, soluble sugars, and carotenoid contents were noted under the combination of severe salinity and drought stress imposed at the flowering stage. Investigating the growth indices in severe salinity and water deficit stress in different phenological stages shows the predominance of ionic stress over osmotic stress under severe salinity. The highest grain yield was observed under non-saline well-watered conditions whereas the lowest grain yield was recorded under severe salinity and drought stress imposed at the flowering stage. In conclusion, the flowering stage was more sensitive than the heading and kernel extension stages in terms of water deficit. The impact of salinity and water deficit was more pronounced on soluble sugars and leaf free proline; so, these criteria can be used as physiological indicators for drought and salinity tolerance in triticale.

Soil nutrition management may preserve non-detrimental weed communities in rainfed winter wheat (T. aestivum)

Overuse of fertilizers has been associated with the selection of competitive and dominant weed communities and biodiversity loss. Considering that crop nutrient management is going through a continuous revisitation process to improve nutrient use efficiency and energy savings, we addressed the consequences of different nutritional levels (low, optimal, and surplus) on weed community composition and wheat growth, yield, and kernel quality. Weed density and biomass were evaluated on sampling areas at the heading stage, and the data obtained were subjected to a cluster analysis for the identification of different weed communities throughout the experimental plots. At harvest, plant growth, yield and quality traits of wheat and wheat kernels were evaluated and correlated with the presence of different weed communities. Out of the four weed communities identified under optimal and low nutrition, two communities did not significantly reduce wheat yield. Under surplus nutrition only one weed community was identified, which resulted to be detrimental for wheat production in terms of yield quantity and quality. The non-detrimental communities were characterized by a high presence of corn chamomile (Anthemis arvensis L.), birdeye speedwell (Veronica persica Poir.), and common chickweed (Stellaria media (L.) Vill). On the contrary, the detrimental communities, were characterized by a high density and aboveground biomass of burr medic (Medicago polymorpha L.). Finally, under surplus nutrition, species richness declined, and the density and aboveground biomass of annual ryegrass (Lolium rigidum Gaud.) increased compared to optimal and low nutrition. Our results showed that soil fertilization plays a crucial role in differentiating detrimental vs. non-detrimental weed communities, with excess fertilization reducing species richness and selecting for competitive and specialized weed species. Overall, an efficient management of soil nutrients may promote non-detrimental weed communities while reducing weed management intensity and thereby improving biodiversity and sustainability. Assessing the efficiency of soil fertilization management and understanding how different fertilization rates and forms may affect weed communities is crucial to advancing sustainable weed management.

Peroxidación lipídica, contenido en prolina libre y azúcares solubles como indicadores de tolerancia al estrés oxidativo en algunas líneas avanzadas de trigo duro (Triticum durum Desf.).

Oxidative stress induced by glyphosate is a complex phenomenon caused by an imbalance between reactive oxygen species (ROS) and antioxidants in plants cells. The present research was carried out at the field crops institute, Agricultural Experimental Station of Setif (ITGC-AES), to assess the response of some durum wheat (Triticum Durum Desf.) lines exposed to oxidative stress induced by glyphosate herbicide. In the heading stage, a solution of 5 Mm of glyphosate was sprayed on flag leaves, and each measurement was taken 48 hours after the glyphosate application. Lipid peroxidation, free proline and soluble sugars were determined. The results indicated that oxidative stress increased the content of lipid peroxidation, proline, and soluble sugars in flag leaves. Analysis of variance revealed significant differences among the genotypes tested, the increase in the level of lipid peroxidation is much higher in advanced lines G5 and G3, in which lipid peroxidation and membrane damage are greater. Oxidative damage also increased the proline content in lines G3 and G4, and soluble sugars in line G5, which were showing a high tolerance to the oxidative stress induced.

Enhancing Rice Yield and Nitrogen Utilization Efficiency through Optimal Planting Density and Reduced Nitrogen Rates

Rice yields can only be achieved by selecting a high-quality population. Nitrogen rates and transplanting density play a significant role in determining population quality and yield. Field experiments were conducted in Heshan District, Hunan Province, China, to explore suitable nitrogen rates and appropriate transplanting densities for rice production in 2021 and 2022. In this study, three levels of nitrogen, e.g., N1, N2, and N3 (0, 150, and 210) kg ha−1, and three transplanting densities, e.g., B1, B2, and B3 (1, 2, and 3) seedlings per hill were used to study their individual or combined effects on rice (Taiyou 390) population quality, yield, and yield components, nitrogen-related enzyme activities, and nitrogen absorption and utilization efficiency. The results showed that N2B3 had the highest yield, with an average yield of 9.30 t ha−1 in two years, which was 3.7~49.6% higher than other treatments. This increase was attributed to higher dry matter accumulation (1538.22 g m−2) and effective panicle number (435.2 × 104 ha−1), influenced by increased nitrate reductase activity at the booting stage and glutamine synthase at the heading stage, along with maintenance of higher SPAD value and leaf area index. Nitrogen rates and transplanting densities significantly affected nitrogen use efficiency, with the contribution rate of nitrogen fertilizer to yield decreasing as nitrogen rates increased. However, N2B3 improved nitrogen use efficiency and stabilized rice yield by reducing nitrogen fertilizer application. This study suggested that N2B3 treatment could enhance rice yield by improving plant nitrogen use efficiency under low nitrogen supplementation.

Predrought and Its Persistence Determined the Phenological Changes of Stipa krylovii in Inner Mongolia

Clarifying the response of plant phenology to drought duration is helpful for accurately interpreting and predicting carbon sinks in ecosystems. Based on the response of different phenological periods of the dominant species Stipa krylovii to monthly, seasonal, and semiannual time scale drought in the typical steppe of Inner Mongolia from 1983 to 2018, the results revealed that (1) the start of the growing season (SOS) was characterized by an advance–delay–advance pattern, and the heading stage (HOS), flowering stage (FOS), and end of the growing season (EOS) all showed consistent advanced trends, which provided additional insight into the conclusions of previous studies that found the SOS was advanced in arid and semiarid regions. (2) The response mechanism of the SOS to the timing of drought was not consistent. Among the response mechanism, the SOS was delayed because of the January–February drought at different time scales but advanced because of the April drought at different time scales. The HOS/FOS was delayed by the June–July drought at different time scales, and the EOS was advanced by the August–September drought at different time scales. (3) More importantly, the SOS, HOS, FOS, and EOS were affected by predrought and its persistence, and the effects were greater the closer to the phenological periods that drought occurred. (4) At the monthly scale, droughts in January, June, and August were the critical drought periods affecting the SOS, HOS/FOS, and EOS, while seasonal and semiannual scale droughts in February, June–July, and September were the critical periods affecting the SOS, HOS/FOS, and EOS. The results of this study enrich our understanding of how drought at different time scales affects different phenological periods, providing a basis for improving plant phenological models.

Relationship between characteristics of basal internodes and lodging and its physiological mechanism in direct‐seeded rice

AbstractLodging is an important factor that limits rice yield and the large‐scale promotion of direct‐seeded rice (DSR). The objective of this study was to clarify the relationship between the characteristics of basal internodes and lodging and the physiological mechanism underlying this process in DSR. A field study was conducted in Changchun, Jilin Province, China, using a japonica rice variety Jiyujing with two direct seeding cultivation methods, including dry DSR (DDSR), wet DSR (WDSR) and conventional‐transplanted rice (CTSR) as a control in 2019 and 2020. Lodging‐related physical parameters, morphological characteristics and carbohydrate components of basal internodes were investigated at heading stage (HS) and 30 days after heading stage (HS30). The results showed that WDSR increased lodging index (LI) and lodging rate compared with CTSR and DDSR. LI increased rapidly from HS to HS30, primarily because of the significant reduction in the breaking strength (M). Correlation analysis revealed that the M of N4 internode was significantly positively correlated with culm plumpness and structural carbohydrate proportions at HS30. Culm plumpness decreased significantly, due to a decrease in nonstructural carbohydrate (NSC) content then primarily the decrease in starch proportions and content. Compared with CTSR and DDSR, WDSR decreased culm wall thickness, dry weight per centimetre of the culm and leaf sheaths, and the proportions and contents of cellulose, lignin and starch of internode, resulting in the decrease in internode breaking strength. Thus, it was concluded that the DSR reduced internode strength by reducing internode plumpness and carbohydrate content, thus decreasing lodging resistance.

Multimodal Deep Learning for Rice Yield Prediction Using UAV-Based Multispectral Imagery and Weather Data

Precise yield predictions are useful for implementing precision agriculture technologies and making better decisions in crop management. Convolutional neural networks (CNNs) have recently been used to predict crop yields in unmanned aerial vehicle (UAV)-based remote sensing studies, but weather data have not been considered in modeling. The aim of this study was to explore the potential of multimodal deep learning on rice yield prediction accuracy using UAV multispectral images at the heading stage, along with weather data. The effects of the CNN architectures, layer depths, and weather data integration methods on the prediction accuracy were evaluated. Overall, the multimodal deep learning model integrating UAV-based multispectral imagery and weather data had the potential to develop more precise rice yield predictions. The best models were those trained with weekly weather data. A simple CNN feature extractor for UAV-based multispectral image input data might be sufficient to predict crop yields accurately. However, the spatial patterns of the predicted yield maps differed from model to model, although the prediction accuracy was almost the same. The results indicated that not only the prediction accuracies, but also the robustness of within-field yield predictions, should be assessed in further studies.

Common population characteristics of direct‐seeded hybrid indica rice for high yield

AbstractDirect seeding of rice has attracted attention because of its simplicity and rapidity compared with traditional cultivation methods. However, the geographical location of the rice region in Southwest China is complex, and the common characteristics of high yield of direct seeding hybrid indica rice and the law of nutrient absorption and accumulation are still unclear. This study results demonstrated that the mean yield of high‐yield varieties (HYV) in the two ecological points increased by 17.68%–19.98% and 17.37%–27.06%, respectively, compared with low‐yield varieties (LYV). The high tillering ability and effective tillering rate of HYV promoted a large leaf area index (LAI) and a strong photosynthetic capacity and stimulated the accumulation of aboveground biomass and nitrogen, phosphorus, and potassium nutrients in rice plants, which were finally transported and allocated to the grains to maintain high yields. Correlation analysis indicated that yield and its components were closely related to spatial population structure and nutrient accumulation and allocation. In particular, LAI at the full heading stage, net photosynthetic rate, aboveground biomass from jointing to maturity stage, and nitrogen, phosphorus, and potassium accumulation and distribution from jointing to full heading stage have the strongest correlation with yield and its components. Therefore, improving the effective tillering rate and LAI, as well as the accumulation and distribution of aboveground biomass, nitrogen, phosphorus, and potassium of rice plants from jointing to full heading stage, are the common laws for the formation of high yield of direct seeding hybrid rice in different ecological areas.

Don't panic any more: MORE PANICLES 3 increases rice yield at elevated CO2 levels.

Don't panic any more: MORE PANICLES 3 increases rice yield at elevated CO2 levels.

Assessing the Role of Crop Rotation in Shaping Foliage Characteristics and Leaf Gas Exchange Parameters for Winter Wheat

Properly designed crop rotation enriches the diversity of the agroecosystem, which has a favorable effect on the environmental properties and crop yield. The experiment assessed winter wheat cultivated under the following crop rotations: A. winter rape + catch crop − spring barley − field pea − winter wheat; B. winter rape − winter wheat + catch crop − field pea − winter wheat; C. winter rape + catch crop − field pea − winter wheat − winter wheat; D. winter rape − winter wheat + catch crop − spring barley − winter wheat. The aim of the study was to investigate: (i) whether the cultivation of wheat in crop rotations following forecrops of rape, pea, barley, and wheat will affect its foliage and photosynthesis; (ii) how the photosynthetic process will affect the wheat yield. At the stem elongation stage (BBCH 36) and at the heading stage (BBCH 58), the following were investigated: foliage features, photosynthetic parameters, and the above-ground biomass; while at the BBCH 89 stage, the grain yield was investigated. It was demonstrated that photosynthesis was most intense under crop rotation A (the highest stomatal conductance, transpiration, intercellular CO2 concentration, and net assimilation rate ranged from 13.1–29.7 μmol CO2∙m−2·s−1). This was reflected in the above-ground biomass volume (1245–1634 g m−2) and grain yield (4.58–7.65 t ha−1). The cultivation of wheat following wheat under crop rotation C and following barley under D had a negative effect on both the foliage and photosynthetic parameters.

Receptor-Like Cytoplasmic Kinase STK Confers Salt Tolerance in Rice

BackgroundSoil salinization is a major abiotic environmental stress factor threatening crop production throughout the world. Salt stress drastically affects the growth, development, and grain yield of rice (Oryza sativa L.), and the improvement of rice tolerance to salt stress is a desirable approach for meeting increasing food demand. Receptor-like cytoplasmic kinases (RLCKs) play essential roles in plant growth, development and responses to environmental stresses. However, little is known about their functions in salt stress. Previous reports have demonstrated that overexpression of an RLCK gene SALT TOLERANCE KINASE (STK) enhances salt tolerance in rice, and that STK may regulate the expression of GST (Glutathione S-transferase) genes.ResultsThe expression of STK was rapidly induced by ABA. STK was highest expressed in the stem at the heading stage. STK was localized at the plasma membrane. Overexpression of STK in rice increased tolerance to salt stress and oxidative stress by increasing ROS scavenging ability and ABA sensitivity. In contrast, CRISPR/Cas9-mediated knockout of STK increased the sensitivity of rice to salt stress and oxidative stress. Transcriptome sequencing analysis suggested that STK increased the expression of GST genes (LOC_Os03g17480, LOC_Os10g38140 and LOC_Os10g38710) under salt stress. Reverse transcription quantitative PCR (RT-qPCR) suggested that four stress-related genes may be regulated by STK including OsABAR1, Os3BGlu6, OSBZ8 and OsSIK1.ConclusionsThese findings suggest that STK plays a positive regulatory role in salt stress tolerance by inducing antioxidant defense and associated with the ABA signaling pathway in rice.