Development of Artificial Intelligence Climate Chamber and Experimental Study on Crop Phenotype Acquisition

Background: The deficiencies of traditional artificial climate chambers in phenotypic collection and analysis were improved to achieve the high-throughput acquisition of crop phenotypes during the growth period. This paper has developed an artificial intelligence climate cabin with functions of crop cultivation management and phenotype acquisition during the whole growth period. This research also established an environmental control system, a crop phenotype monitoring system and a crop phenotype acquisition system with environmental parameter adjustment and crop image collection. Phenotypic feature extraction and other functions were carried out in the cultivation experiment, and phenotype acquisition of wheat was performed under different nitrogen fertiliser application rates. Comparison and analyses were performed by the systematic and manual measurement values of crop phenotype characteristics, and the acquisition of wheat table was evaluated based on artificial intelligence climate cabin. The goodness of fit of the model was used to classify data.Results: During the different growth periods of wheat, the correlation analysis between the systematic and manual measurement values of its leaf area, plant height and canopy temperature showed that the obtained correlation coefficient r was greater than 1, and the fitting determination coefficient R2 was greater than 0.7156, with errors. The coefficient root mean square error was less than 2.42, indicating that the two were positively correlated, and their correlation was excellent. Conclusion: The results verified the feasibility and applicability of the artificial intelligence climate cabin to study the phenotypic characteristics of crops.

CROP WATER STRESS INDEX FOR PREDICTING YIELD LOSS IN COMMON BEAN

The crop water stress index (CWSI), an index derived from canopy temperature, has been widely studied as a physiological indicator of plant water status to optimize irrigation in common beans. However, it is not clear how this index could contribute to yield prediction as a decision support tool in irrigation management. This paper aimed to use the CWSI for predicting yield loss in common bean (Phaseolus vulgaris L.) subjected to water stress under drip irrigation. A rain shelter experiment was conducted using a completely randomized design with five replications. The indeterminate growth cultivar TAA Dama was subjected to three irrigation treatments: 100% of the field capacity (FC), 75 and 50% FC from 20 days after sowing (DAS) until the end of the crop cycle. Grain yield was reduced by 42% under 50% FC treatment. Furthermore, stomatal conductance was reduced under this treatment, whereas the CWSI and canopy temperature increased as irrigation levels decreased. The relationship between grain yield and CWSI (R2=0.76, RSME=2.35g) suggests that canopy temperature data could be used to forecast grain yield losses. In conclusion, farmers can have a low-cost, effective technique for making water management decisions in common bean.

Behaviour of relative evapotranspiration with agrometeorological stress indices in wheat

Complex behaviour of stress indices with relative evapotranspiration was observed in early and late sown wheat, however, under normal sown conditions it was linearly decreasing. Predawn leaf water potential and transpiration rate proved to be a stable stress index parameter for characterizing the internal moisture status in the plant as compared to the canopy temperature and stomatal resistance under stress conditions in wheat. Since it is easy to quantify canopy/leaf temperature and within seasonal variations it is widely used for scheduling irrigation and quantigying moisture stress effects on growth and development in wheat.

Sudden changes in crop environment, as influenced by total solar eclipse

The Division of Agricultural Meteorology, at Pune of IMD conducted an experiment at Principal Evapotranspiration Observatory, Canning, W.B., during October, 1995 to study the sudden changes in crop environment. The present study revealed that both the crop canopy temperature and observatory temperature at different heights recorded sharp fall of around 2.0°C at 0900 hr (IST) on the eclipse day. The relative humidity (% ) increased sharply at 0900 hr (IST) on the eclipse day within crop canopy as well as within observatory. The soil temperature dropped suddenly at 10 and 20 cm depths of the subsoil and delayed reversal of the soil temperature gradient occurred on the eclipse day; the grass minimum temperature was 21.2°C. Bright sunshine hours reduced by 0.8 on 'the eclipse day as compared to the preceding and succeeding days. The wind during the eclipse period was almost calm between 0900 -0930 hr (IST). The daily total ET recorded on the eclipse day was the minimum. The rate of evapotranspiration was less than half as compared to the other days, as recorded at 0830 hr (IST) (0.2 mm) on the eclipse day, which was closely followed by that observed at 1130 hr (IST) (0.3 mm).

Microtensiometers Accurately Measure Stem Water Potential in Woody Perennials

Stem water potential (Ψstem) is considered to be the standard measure of plant water status. However, it is measured with the pressure chamber (PC), an equipment that can neither provide continuous information nor be automated, limiting its use. Recent developments of microtensiometers (MT; FloraPulse sensors), which can continuously measure water tension in woody tissue of the trunk of the tree, can potentially highlight the dynamic nature of plant water relations. Thus, this study aimed to validate and assess the usefulness of the MT by comparing the Ψstem provided by MT with those same measurements from the PC. Here, two irrigation treatments (a control and a deficit treatment) were applied in a pear (Pyrus communis L.) orchard in Washington State (USA) to capture the full range of water potentials in this environment. Discrete measurements of leaf gas exchange, canopy temperature and Ψstem measured with PC and MT were made every two hours for four days from dawn to sunset. There were strong linear relationships between the Ψstem-MT and Ψstem-PC (R2 > 0.8) and with vapor pressure deficit (R2 > 0.7). However, Ψstem-MT was more variable and lower than Ψstem-PC when Ψstem-MT was below −1.5 MPa, especially during the evening. Minimum Ψstem-MT occurred later in the afternoon compared to Ψstem-PC. Ψstem showed similar sensitivity and coefficients of variation for both PC and MT acquired data. Overall, the promising results achieved indicated the potential for MT to be used to continuously assess tree water status.

Microclimate Modification through Groundnut-Pigeon Pea Intercropping System and its Effect on Physiological Responses, Disease Incidence and Productivity

Background: Groundnut (Arachis hypogaea) is the predominant leguminous oilseed crop of India which has turned out to be a sensitive victim to climate change episodes like rising CO2 levels, erratic rainfall pattern, high temperature and moisture stress leaving deleterious imprints in physiology, disease resistance, fertility and productivity. Globally climate change is anticipated to pull down groundnut productivity by 11-25%. Agronomic manipulations like altered time of sowing, intercropping and irrigation management helps in microclimate modification towards reaping higher productivity and economic returns in groundnut. Methods: Field experiments were conducted during 2019-2021 on sandy clay loam soil (Fluventic Ustropept) in a Randomized Block Design with three factors viz., differential cropping systems (sole groundnut, groundnut + red gram intercropping), rainfed and irrigation systems and differential sowing windows (Second fortnight of June, first and second fortnights of July). Growth parameters, physiological traits viz., photosynthetic rate, transpiration rate, stomatal conductance, canopy temperature and light interception, incidence of foliar diseases viz., leaf spot and rust; soil borne disease viz., stem rot, root rot and productivity of groundnut were recorded at critical crop growth stages. Result: Canopy temperature was higher in sole groundnut system while light interception was higher in groundnut - redgram intercropping system, however system productivity did not register statistical superiority between the cropping systems. Irrigated system exerted its influence over rainfed system in terms of pod and kernel yield of groundnut. Sowing of groundnut during second fortnight of June was beneficial than July sowing in pod and kernel yield of groundnut due to uniform distribution of rainfall during the growth and reproductive phases of crop. Although differential cropping systems did not register their impact on disease incidence of groundnut, irrigated system and first sowing windows recorded minimum incidence of root rot, stem rot, early leaf spot, late leaf spot and rust diseases compared to rainfed system and July sowing.

Identifying Traits Associated With Terminal Drought Tolerance in Sesame (Sesamum indicum L.) Genotypes

Sesame is predominantly cultivated in rainfed and low fertile lands and is frequently exposed to terminal drought. Sesamum species inhabiting dryland ecosystems adaptively diverge from those inhabiting rainfed habitats, and drought-specific traits have a genetic basis. In sesame, traits associated with drought conditions have not been explored to date, yet studies of these traits are needed given that drought is predicted to become more frequent and severe in many parts of the world because of climate change. Here, 76 accessions from the available Indian core set were used to quantify variation in several traits under irrigated (WW) and terminal drought stress (WS) conditions as well as their association with seed yield over two consecutive years. The range of trait variation among the studied genotypes under WW and WS was significant. Furthermore, the traits associated with seed yield under WW and WS differed. The per se performance of the accessions indicated that the expression of most traits was reduced under WS. The correlation analysis revealed that the number of branches, leaf area (LA), leaves dry weight (LDW), number of capsules plant–1, and harvest index (HI) were positively correlated with seed yield under WW and WS, and total dry matter (TDM), plant stem weight, and canopy temperature (CT) were negatively correlated with seed yield under WW and WS, indicating that smaller and cooler canopy genotypes had higher yields. The genotypes IC-131936, IC-204045, IC-204861, IC-205363, IC-205311, and IC-73576 with the highest seed yields were characterized by low canopy temperature, high relative water content, and high harvest index under WS. Phenotypic and molecular diversity analysis was conducted on genotypes along with checks. Phenotypic diversity was assessed using multivariate analysis, whereas molecular diversity was estimated using simple sequence repeat (SSR) loci to facilitate the use of sesame in breeding and genetic mapping. SSRs showed low allelic variation, as indicated by a low average number of alleles (2.31) per locus, gene diversity (0.25), and polymorphism information content (0.22). Cluster analysis (CA) [neighbor-joining (NJ) tree] revealed three major genotypic groups and structure analysis showed 4 populations. The diverse genotypes identified with promising morpho-physiological traits can be used in breeding programs to develop new varieties.

A New Threshold-Based Method for Extracting Canopy Temperature from Thermal Infrared Images of Cork Oak Plantations

Canopy temperature (Tc) is used to characterize plant water physiology, and thermal infrared (TIR) remote sensing is a convenient technology for measuring Tc in forest ecosystems. However, the images produced through this method contain background pixels of forest gaps, thereby reducing the accuracy of Tc observations. Extracting Tc data from TIR images is of great significance for understanding changes in ecosystem water status. In this study, a temperature threshold method was developed to rapidly, accurately, and automatically extract forest canopy pixels for Tc data obtention. Specifically, this method takes the temperature corresponding to the point with a slope of 0.5 in the curve composed of the normalized average temperature and the normalized cumulative number of pixels as the segmentation threshold to separate the forest gap pixels from the forest canopy pixels in the TIR images and extract the separated forest canopy pixels based on the pixel coordinates for Tc data obtention. Taking the Tc values, measured using a thermocouple, as the standard, Tc extraction using the new temperature threshold method and traditional methods (the Otsu algorithm and direct extraction) was compared in cork oak plantations. The results showed that the temperature threshold method offered the highest extraction accuracy, followed by the direct extraction method and the Otsu algorithm. The temperature threshold method was determined to be the most suitable for extracting Tc data from the TIR images of cork oak plantations.

Selecting Drought-Tolerance Markers: An Exploratory Analysis in Contrasting Soybeans

Identifying high-yield genotypes under low water availability is an important goal for soybean breeding. However, a major bottleneck lies in phenotyping, particularly in selecting cost-efficient markers associated with stress tolerance and yield stabilization. Here, we conducted in-depth phenotyping experiments using two soybean genotypes with contrasting drought tolerance, MUNASQA (tolerant) and TJ2049 (susceptible), aiming to identify and statistically validate stress tolerance and yield stabilization markers. Firstly, at the R5 critical reproductive stage, the molecular differences between the genotypes responses to mild water deficit were explored through massive analysis of cDNA ends (MACE)-transcriptomic and gene ontology. MUNASQA transcriptional profile, compared to TJ2049, revealed significant differences when responding to drought. Next, both genotypes were phenotyped under mild water deficit, imposed in vegetative (V3) and R5 stages, by evaluating 22 stress-response, growth and water-use markers, which were subsequently correlated between phenological stages and with yield. Several markers showed high consistency, independent of the phenological stage, demonstrating the effectiveness of the phenotyping methodology and its possible use for early selection. Finally, these markers were classified and selected according to their cost-feasibility, statistical weight and correlation with yield. Here, pubescence, stomatal density and canopy temperature depression emerged as promising markers for early selection of drought-tolerant soybeans.

PLANT SPACING AND ITS EFFECT ON YIELD, FIBRE QUALITY AND PHYSIOLOGICAL PARAMETERS IN COTTON

The purpose of this study was to see how changing plant spacings affected cotton yield, yield components, fibre quality traits, and physiological parameters. In this study, six plant spacings (no thinning, 5, 10, 15, 20, and 25 cm) were investigated. Plant density caused significant differences in the number of first fruiting branches, number of bolls, ginning percentage, seed cotton yield, fibre yield, and normalised difference vegetative index (NDVI). Plant height, the number of sympodial branches, number of monopodial branches, boll weight, seed cotton weight/boll, number of 100-seed weight, seeds/boll, canopy temperature, chlorophyll content, leaf area, and fibre quality properties (micronaire, length, strength, elongation, uniformity, short fibre index, reflectance, yellowness, and spinning consistency index [SCI] were non-significant. The highest values of seed cotton yield, fibre yield, ginning percentage, number of first fruiting branches, and NDVI were obtained in the no thinning and 5 cm plant spacing applications, while the highest boll number was obtained at 20 and 25 cm plant spacings. In this study, physiological parameters, such as canopy temperature, leaf area, chlorophyll content, and fibre technological traits, were not affected by plant spacing. The highest seed cotton yield, fibre yield, ginning percentage and NDVI were obtained from no thinning and 5 cm intra-row spacing, indicating their impact on examined characteristics. Therefore, a yield estimation can be made in the flowering period with the NDVI in different plant densities in cotton.