Phase Of Crop Growth Research Articles

Mitigating moisture stress in bhendi through osmolyte application

The purpose of this study was to identify the best osmolyte for foliar application to overcome moisture stress under field conditions in Bhendi (Abelmoschus esculentus L. Moench). Foliar applications of the osmolytes, viz., proline (50 mM), glycine betaine (50 mM), ascorbic acid (100 ppm), salicylic acid (100 ppm) and KCl (1 %) were applied twice, at 25 and 45 days after sowing (DAS), to mitigate moisture stress imposed by withholding irrigation during the vegetative and reproductive phases of crop growth. Data on yield parameters and yield were recorded. The results revealed that, in terms of the yield attributes, foliar sprays of proline (50 mM) resulted in increased pod length (12.2 cm) and higher pod yield per plant (335.1 g) in Bhendi. However, the highest benefit cost ratio of 1.52 and 1.23 was obtained by applying KCl (1%) followed by salicylic acid (100 ppm) during moisture stress at the reproductive stage. From the study, it is concluded that foliar sprays of proline (50 mM) and salicylic acid (100 ppm) were effective in mitigating moisture stress under field conditions in Bhendi.

District Level Crop Weather Calendars and Advisories for Kharif Rice in Odisha, India

The crop weather calendar is a visual depiction of key facts about crop growth phases, typical crop water requirements, and alerts that should be sent out in response to weather that is conducive to the spread of pests and diseases. Farmers and other stakeholders may successfully plan crops, schedule irrigation, and take plant protection measures by using these calendars, which are practical and helpful tools for farmers. The crop weather calendars are prepared in different languages for better understanding to farmers and explain the usage importance and plan farm operation and activities by taking decisions as per the prevalent crop weather conditions in fields. It plays a vital role for important crops and various varieties through research & development-based process at village/ panchayat level. It also helpful for improving the quality of medium range weather forecast based on Agro-Advisory Services (AAS). The AAS provides strategies based on weather for crop and livestock management to increase production and food security. The AAS has been useful to advise farmers regarding farm operations to manage the inclement weather for effective crop production in the changing environment. The Research was carried out on the studies of crop weather calendar on Rice crop in different districts of Odisha by All India co-ordinated research project on Agrometeorology, Bhubaneswar centre with the support of Agro Meteorological Field Unit (AMFU). It has been prepared with an objective to study climate normal of past 30 years from (1993-2023). Climatic data of Rice crop in Kharif season has been taken 25th SMW to 42nd SMW for medium duration (125 days) and 26th to 49th SMW for long duration (150 days) Rice crop in both English and Odia (local) languages for the coastal districts i.e (Khordha, Puri, Kendrapada and Jagatsinghpur) of Odisha. From the crop weather calendar the medium duration of rice crop, it was found that for sowing to seeding the mean temperature is 290C, before the transplanting and the water requirement of 670-690 mm is found congenial for better yield of the crop. The growth of the crops severely affected where the temperature falls below 200C, for high yielding of Rice crop during the kharif season the favourable weather conditions are Tmax: 300C, Tmin: 260C, Rainfall: 78 mm to 110 mm during the 29th to 30th week with RH 87%. For the pest likes stem borer and leaf folder the congenial weather conditions are Temperature :20 to 300C, RH:87%, Wind speed (Km/h) <5 and Rainfall: 00-30 mm. Similarly for Blast and BLB diseases, the favourable conditions during the 28th-31st week to 48th week, when the temperature range 20-300C, RH=> 90 %, Wind speed < 5 (Km/h) RH:30-50%. It has been found that the severity of pest and diseases increases with decreases in temperature and High RH and very low rainfall.

Satellite Based Composite Weather Insurance Product for assessing mid-term adversary

The present study formulated a satellite-based rainfall insurance product (SRIP) at sub-seasonal scale during 2015–2020 by integrating meteorological, geophysical and vegetation index products e.g. rainfall (CHIRPS:Climate Hazards Group InfraRed Precipitation with Station), soil moisture (SMAP), normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) from moderate resolution imaging spectro-radiometer (MODIS). The SRIP was meticulously designed to integrate both cause (rainfall) and impact (NDVI, NDWI, soil moisture) parameters to enhance the assessment of min-season crop risks, with a particular emphasis on deficit rainfall. The performance evaluation of SRIP was conducted in two distinct agro-climatic zones viz. Deoria district of Uttar Pradesh (Upper Gangetic Plain Region) and Krishna district of Andhra Pradesh (Southern Plateau and Hills Region) spanned from June to October, which aligns with the major crop-growing season corresponding to the Southwest monsoon period in India. Three sets of SRIPs were investigated i.e. SRIP with cause parameter (SRIP1), SRIP with cause-impact parameters with no lag response (SRIP2) and SRIP with cause-impact parameters with one-month lag response (SRIP3). The SRIP was structured to provide a numerical index on a scale ranging from 0 to 1, representing poor to good crop-growing conditions that could effectively identify the rainfall deficit threshold (SRIP≤0.43) corresponding to negative percent deviation in rainfall (PDR≤−20%). This threshold level was recognized for compensation of triggers at the multiple crop growth phases during the crop-growing season. The district average of SRIP and PDR showed fair correlation co-efficient (0.77 ≤ r ≤ 0.88). Good correlation between sub-seasonal (monthly, bi-monthly, tri-monthly) SRIP and normalized MODIS Gross Primary Productivity (0.65 ≤ r ≤ 0.98), and SRIP deviation and yield deviation (0.45 ≤ r ≤ 0.97) reflect sensitivity of SRIP to crop carbon productivity and crop yield. The findings of the present study recommend SRIP not only a multi-phase composite index for assessing mid-season crop risks in terms of rainfall deficit for clusters of insurance units, but it has the potential to be used by insurance agencies to settle the claims by farmers in a transparent and faster manner for crop loss due to large-scale rainfall deficits. However, SRIP needs to be customized in future to make it more adaptable to settle insurance claims due to weather adversaries at individual farm level.

EDGE AI BASED PLANT DISEASE DETECTION SYSTEM

Agriculture is a crucial industry to humankind's continued existence. Simultaneously, digitalization's pervasive influence made it simpler to accomplish previously challenging jobs in a wide range of disciplines. The agriculture industry, for both the farmer and the consumer, would greatly benefit from technological and digital adaptation. Through the use of technology and consistent monitoring, illnesses can be detected early on and removed, resulting in a higher yield. The economic, social, and political lives of farmers and the entire agricultural industry are profoundly impacted by the health and productivity of their crops. Therefore, in order to detect the illnesses at the proper moment, it is essential to conduct careful monitoring at different phases of crop growth. However, humans may require more than their natural attire, and there may be situations when doing so would be deceiving. Accurate identification requires a system that can automatically recognise and categorise the numerous illnesses that can affect a given crop. The current proposed framework was inspired by this train of thought. The suggested framework is primarily concerned with the transfer learning phenomena based on VGG16, and the "Plant Village" dataset, which contains both damaged and healthy potato and tomato leaves, is being explored for implementation. Keywords: Transfer learning, VGG16, Plant Village.

Estimating distributed autumn irrigation water use in a large irrigation district by combining machine learning with water balance models

Autumn irrigation (AI) after crop harvesting is vital for agricultural production in cold arid regions, typically requiring more water than regular irrigation during crop growth phases. Understanding distributed AI water use (AIWU) is key to optimizing irrigation strategies and refining agro-hydrological simulations. However, field-scale monitoring of irrigation water use is challenging, particularly in large districts, and quantification methods for distributed AIWU have seldom been investigated. Given this, we proposed a remote sensing-based model to estimate AIWU from water balance analysis, with key components derived through machine learning algorithms. Specifically, to address the unique challenge of short water ponding duration during AI, we selected MODIS as the primary data source, supplemented with Sentinel-2 data to enrich field-level details. A Sentinel-2 empirical bathymetry model, informed by in-situ measurements, served as a foundation for constructing a MODIS bathymetry model using random forest. This MODIS bathymetry model was essential for determining water ponding depths, which allowed for accurate estimation of infiltration rates when applied to the MODIS-based water index time series. By integrating these estimates into the water balance framework, we achieved a more precise estimate of AIWU. The proposed model was applied to Hetao Irrigation District (HID), the largest irrigation district in the arid region of China. The estimated steady infiltration rate and canal efficiency align with similar studies. The results indicate that the average AIWU per unit AI area in the HID remains stable during 2010–2020 with substantial spatial variability at the pixel level, providing new insights into the local hydrological cycle. The AIWU of HID has been decreasing by 19 million m3 per year during this period mainly due to the reduction in AI area, with a more prominent trend from 2010 to 2017. Our study deepens insights into the spatial–temporal dynamics of AIWU in arid regions, contributing to better irrigation management.

Salinity Stress in Maize: Consequences, Tolerance Mechanisms, and Management Strategies

Maize, along with rice and wheat, is a popular staple food crop worldwide, and the most widely produced cereal crop. It is a versatile crop that may be utilized as a source of raw materials for human and animal fodders. Low agricultural yield and rapid population expansion significantly threaten future food security. Maize production is hampered by biotic and abiotic causes, with abiotic factors being the most critical limitation to agricultural output worldwide. Soil salinity is a key abiotic factor that reduces agricultural production by imposing negative impacts at several life cycle phases, including germination, seedling, vegetative, and reproductive development. Maize plants experience many physiological changes due to osmotic stress, toxicity of particular ions, and nutritional imbalance induced by salt stress. The degree and duration of stress, crop growth phases, genetic characteristics, and soil conditions influence yield reduction. Maize plants can tolerate salt stress involving a complex mechanism by changing their physiological, biochemical, and metabolic activities like stomatal functioning, photosynthesis, respiration, transpiration, hormone regulation, enzymes, metabolite generation, etc. After studying the salt tolerance mechanisms of maize plants under stress, integrated management techniques should be developed for maize agriculture in saline settings. Therefore, the study of plant responses to salt stress, stress tolerance mechanisms, and management strategies is one of the most imperative research fields in plant biology, and the study will focus on the effects of salt stress in different growth stages, plant tolerance mechanisms, and agronomic management practices for successful maize production all over the world.

Effect of salinity and drip fertigation on maize (<i>Zea mays</i>) and water use efficiency

Climatic variability is immensely pressurised on freshwater availability in arid and semi-arid ecosystems, leading to poor quality water for crop production not becoming uncommon, especially in coastal ecosystems. A field experiment was conducted during winter (rabi) season of 2022–23 at the Saline Water Scheme at Agricultural College Farm, Acharya N. G. Ranga Agricultural University, Bapatla, Andhra Pradesh to assess the impact of saline water on maize growth, yield and water use efficiency under drip fertigation. The experiment consisted 8 treatments laid in randomized block design (RBD) with 4 replications. The utilization of the BAW irrigation method, together with the application of a prescribed quantity of fertilizer, resulted in the highest plant height and dry matter accumulation during all phases of crop growth. These outcomes were comparable to those achieved by using a combination of fresh water and saline water with an electrical conductivity of 2 dS/m. The maximum values for the number of kernels per cob (451), cob length (17.2 cm), cob weight (164.4 g), kernel yield (7.38 t/ha), stover yield (9.61 t/ha) and water use efficiency (18.5 kg/ha mm) of maize were observed under the irrigation treatment T4. The parameters exhibited their minimum values when irrigation was conducted using water with a salt level of 4 dS/m and no fertilizers were used. However, there was no statistically significant difference observed in the number of cobs per plant and harvest index of maize when saline water was used in conjunction with drip fertigation. In the context of maize cultivation, employing a cyclic irrigation technique that alternates between salty (EC 2–4 dS/m) and freshwater sources, in conjunction with recommended dose of fertiliser (RDF) has the potential to deliver comparable crop development, productivity, and economic benefits when compared to the use of freshwater sources alone.

The coincidence of climate extremes with sensitive crop growth phases: Projected impact on sustainable crop water use and crop yield in the IGB river basins

Increased climate variability and extremes are unequivocal with unprecedented impacts on water resources and agriculture production systems. However, little is known about the impacts of climate extremes at the intra-seasonal level which remained largely unexplored. We investigated the coincidence of climate extremes with sensitive crop growth phases of wheat and rice in the Indus, Ganges and Brahmaputra (IGB) river basins of South Asia. We also quantified the related impacts on irrigation water demand (IWD), gross primary production (GPP) and crop yields (CY) simulated by a hydrological-vegetation model (LPJmL) during 1981–2100 using RCP4.5-SSP1 and RCP8.5-SSP3 framework. The climate extremes revealed a higher frequency and intensity during crop growth phases with significant increasing trends in future. Diverse changes in IWD, GPP and CY are projected in future under the influence of crop phase-specific extremes. The crop phase-specific changes in the IWD of wheat and rice will intensify in the future. More than 50 % of the change in future wheat irrigation is caused by warm and dry extremes during the ripening phase. Whereas, increase in IWD for rice is mainly associated with warm extremes only. The crop phase-specific GPP shows a decreasing trend in future for both wheat and rice in the Western part of IGB with the largest decrease during the reproductive phase of wheat (up to 36 %) and vegetative phase of rice (>20 %). This decrease is clearly reflected in seasonal yields i.e., both wheat (20 %) and rice (12 %) showed a decrease in future linked with warm and dry extremes. However, in the Eastern part of IGB, the GPP will mostly increase in future during the three crop phases of wheat and rice. These results can be used to help develop efficient adaptation strategies considering seasonal changes and sensitive crop phases for sustained food and water security in South Asia.

Climate-induced shifts in irrigation water demand and supply during sensitive crop growth phases in South Asia

This study investigated the shifts in irrigation water demand and supply of the major staple and water-intensive crops (wheat and rice) in the Indus, Ganges and Brahmaputra (IGB) river basins of South Asia under the combined impacts of climate change and socio-economic development during the period 1981–2100. It explores irrigation water usage during climate-sensitive crop growth phases (i.e. vegetative and reproductive which required ~ 60% of the total seasonal (sowing to harvest) water demand), which is supposed to be crucial for long-term integrated crop water management. A hydrology vegetation model Lund Potsdam Jena Managed Land is forced with an ensemble of eight downscaled (5 arc-min) global climate model’s using the RCP (Representative concentration pathways) -SSP (Shared socio-economic pathways) framework, i.e. RCP4.5-SSP1 and RCP8.5-SSP3. To investigate phase-specific crop water projections, trend analysis is performed. It shows a significant (p<0.001) increase in irrigation water demand during the vegetative phase of wheat (6 mm) and reproductive phase of rice (26 mm) and a decrease during the reproductive phase of wheat (13 mm) and vegetative phase of rice (11 mm) in selected study sites. The large decrease in projected irrigation demand for wheat can be explained by a shortening of the growing season length as a result of rising temperatures and increased precipitation. Whereas, an increase in irrigation demand for rice is a combined effect of higher temperatures and less precipitation during the reproductive phase in the region. At the same time, irrigation supply by surface water and groundwater is likely to change in future due to warmer and drier growing periods, causing a significant increase in groundwater irrigation, mainly for rice. Our major research findings show the importance of crop water assessments during the sensitive crop growth phases of wheat and rice which vary in space and time. Including crop phase-specific, climate impact assessments of regional and global projection will help improve the region’s existing crop-water management strategies and adaptation practices.

Influence of Organic Manure and Inorganic Fertilizers on Growth and Yield of Radish (Raphanus sativus L.) in Gird Region of Madhya Pradesh, India

A field experiment was conducted to study the effect of organic manure and inorganic fertilizers on growth and yield of Radish (Raphanus sativus L.) in Grid region of Madhya Pradesh as factorial based on the randomized block design(RBD) with three replication and Ten treatments viz., T1-(100% NPK through inorganic sources), T2-(100% NPK through Farm Yard manure (16t/ha)), T3-(100% NPK through Vermicompost (12t/ha)), T4-(100% NPK through Poultry Manure (9.48t/ha)), T5-(75% NPK+25%N through FYM), T6-(75% NPK+25% N through Vermicompost), T7-(75% NPK+25% N through Poultry manure), T8-(50% NPK+50% N through FYM), T9-(50% NPK+50% N through Vermicompost), T10-(50% NPK+50% N through Poultry manure) were made up of singlevariety Ivory white the experiment was planted in the CRC-II, School of agriculture, ITM University Gwalior. At all of the periodic crop growth phases except at 15 DAS, T6 showed significant plant height and leaf count increases across crop phases. T5, T6 had maximum heights; T3, T10 had minimum. T5, T6, T8 displayed the highest leaf counts; T1 the least. Leaf lengths followed a similar trend, with T8, T6 having the longest; T1 the shortest. Overall, T6 exhibited prominent growth in both height and leaf attributes, while T1 consistently showed the lowest values throughout all stages and measurements. The conventional practices T6 had significant positive influence on yield and yield attributing parameters, viz; root length (35.05cm), weight of whole plant (418.91g), initial fresh weight of roots (355.54g) but initial fresh weight of leaves (72.52g) in recorded in treatment T2, root diameter (50.61mm), girth of root (12.3cm), dry weight of leaves (13.49g) measured in T2, dry weight of root (102.19g), root yield per plot (21.33kg), root yield per hectare (319.98qha-1). Conclusion-: Economically the application of 75% NPK+25% N through vermicompost gave maximum net return (Rs. 262553.80) and BC ratio (3.94).

Mapping Irrigated Croplands from Sentinel-2 Images Using Deep Convolutional Neural Networks

Understanding the spatial distribution of irrigated croplands is crucial for food security and water use. To map land cover classes with high-spatial-resolution images, it is necessary to analyze the semantic information of target objects in addition to the spectral or spatial–spectral information of local pixels. Deep convolutional neural networks (DCNNs) can characterize the semantic features of objects adaptively. This study uses DCNNs to extract irrigated croplands from Sentinel-2 images in the states of Washington and California in the United States. We integrated the DCNNs of 101 layers, discarded pooling layers, and employed dilation convolution to preserve location information; these are models which were used based on fully convolutional network (FCN) architectures. The findings indicated that irrigated croplands may be effectively detected at various phases of crop growth in the fields. A quantitative analysis of the trained models revealed that the three models in the two states had the lowest values of Intersection over Union (IoU) and Kappa, i.e., 0.88 and 0.91, respectively. The deep models’ temporal portability across different years was acceptable. The lowest values of recall and OA (overall accuracy) from 2018 to 2021 were 0.91 and 0.87, respectively. In Washington, the lowest OA value from 10 to 300 m resolution was 0.76. This study demonstrates the potential of FCNs + DCNNs approaches for mapping irrigated croplands across large regions, providing a solution for irrigation mapping. The spatial resolution portability of deep models could be improved further by designing model architectures.

Ensemble surface soil moisture estimates at farm-scale combining satellite-based optical-thermal-microwave remote sensing observations

Remote sensing presents great potential for soil moisture mapping, although a lack of high-resolution, all-season suitable data and model-based complications hinders continuous mapping at the farm scale. The current study attempts to access optical (Sentinel-2) and microwave (Sentinel-1) based Water Cloud Model (WCM), optical and/or thermal-based Thermal-Optical TRApezoid Model (TOTRAM), and Optical TRApezoid Model (OPTRAM) utilizing Landsat-8 data, and an ensemble of these three models synergistically using microwave, optical and thermal remote sensing data for fourteen dates spanning two post-monsoon periods over a semi-arid irrigated agricultural farm. The ensemble model developed with Gradient Boosting Machine (GBM) offered a superior SSM estimate for the entire crop growth season. The ensemble model had the lowest RMSE (0.053 m3 m−3), followed by OPTRAM (SWIR2) (0.06 m3 m−3), while TOTRAM recorded the highest RMSE (0.092 m3 m−3), even though the model performances varied throughout crop growth cycles. For SSM mapping in the early phases of crop growth, WCM or TOTRAM were found superior, while during the latter growth stages, the performance of OPTRAM was better. In contrast to TOTRAM, which needs local calibration as the land surface temperature is sensitive to atmospheric conditions, the study emphasizes the shortcomings of WCM in terms of calibration requirements for changing vegetation structure utilizing in situ data. OPTRAM is suitable for generating SSM maps in semi-arid environments with a predominance of clear skies throughout the post-monsoon season. It is straightforward, low data, and resource intensive with universal surface reflectance-soil moisture association. The ensemble technique can be recommended for farm-level irrigation mapping over a post-monsoon period.

The transcriptome of soybean reproductive tissues subjected to water deficit, heat stress, and a combination of water deficit and heat stress.

Global warming and climate change are driving an alarming increase in the frequency and intensity of extreme climate events, such as droughts, heat waves, and their combination, inflicting heavy losses to agricultural production. Recent studies revealed that the transcriptomic responses of different crops to water deficit (WD) or heat stress (HS) is very different from that to a combination of WD+HS. In addition, it was found that the effects of WD, HS, and WD+HS are significantly more devastating when these stresses occur during the reproductive growth phase of crops, compared to vegetative growth. As the molecular responses of different reproductive and vegetative tissues of plants to WD, HS, or WD+HS could be different from each other, and these differences could impact many current and future breeding and/or engineering attempts to enhance the resilience of crops to climate change, we conducted a transcriptomic analysis of different soybean (Glycine max) tissues to WD, HS, and WD+HS. Here we present a reference transcriptomic dataset that includes the response of soybean leaf, pod, anther, stigma, ovary, and sepal to WD, HS, and WD+HS conditions. Mining this data set for the expression pattern of different stress-response transcripts revealed that each tissue had a unique transcriptomic response to each of the different stress conditions. This finding is important as it suggests that attempting to enhance the overall resilience of crops to climate change could require a coordinated approach that simultaneously alters the expression of different groups of transcripts in different tissues in a stress-specific manner.

Simulating soil-carbon-water interactions in two profiles to select precision cover for soil-health and drought-resilience

BackgroundThe disseminated information to the stakeholders is mostly regional as the urge to meet global production goals and adoption of intensive agricultural practice have been amplified. Regional management strategies (MS) are mainly based on a broad-spectrum of ecoregions and climate scenarios and thus, are not always successful to prescribe a cover without failure. This produces a dilemma which restrains the farmers from adapting soil-covers as a climate-smart conservation practice. Simulating agroecosystems for better-understanding of soil-plant-water relationships within a soil profile would improve the societal acceptance of using cover crops. We intended to bring light into the uncertain conditions of production during drought and inconsistencies in soil organic carbon (SOC) sequestration through analyzing the impacts of soil cover, residue decomposition and inherent soil characteristics on soil moisture variability. MethodIn-situ effects of cover, residues and manure application on specific soil-layers were considered to simulate above and belowground biomass contents and impacts of applied residues, C, nitrogen and moisture content of soils at different crop-growth phases. Soil-environmental factors of seven MS were modeled to reveal the subtle conditions within the profiles of two similar soils of closely-located sites. Decision support systems with Strategic Analysis along with the simulated-results were used for long-term impact-analysis and select a precision cover based on soil and site. Moisture movement through whole soil profiles during drought was analyzed to understand the scope of improving the resiliency of the forage systems. We also compared the impacts of fallow, manure application along with the residue incorporation from rye, clover and winter wheat on two loamy fine-sand soils with similar reaction but contrasting permeability and clay +silt contents. ResultsIrrespective of soil types, impacts of management strategies on SOC were found statistically significant for both 0–20 cm and 20–40 cm soil layers. Slight differences in clay+silt fractionation resulted in different SOC in soil layers and ultimately the moisture availability status. Due to complex interaction effects of management-strategies and soil properties, N leaching was different within two soil profiles. N-uptake was found definable by SOC up to 96% in residue-only treatments and 83% in manure-based MS. ConclusionsA cover of winter-wheat with 50–50 manure +fertilizer and residue application could prove as the best management strategy to improve soil-health and long-term productivity. A precision-cover of clover which results in maximum residue, surface residual-C and SOC addition, and minimum N-leaching could be recommended for resource-use efficiency on low-fertile acid loamy sand soils during drought.

Impact of Agricultural Land Use Types on Soil Moisture Retention of Loamy Soils

Increasingly severe hydrological extremes are predicted for the Pannonian Basin as one of the consequences of climate change. The challenges of extreme droughts require the adaptation of agriculture especially during the intense growth phase of crops. For dryland farming, the selections of the optimal land use type and sustainable agricultural land management are potential adaptation tools for facing the challenges posed by increased aridity. To this end, it is indispensable to understand soil moisture (SM) dynamics under different land use types over drought-affected periods. Within the framework of a Slovenian–Hungarian project, soil moisture, matric potential and rainfall time series have been collected at three pilot sites of different land use types (pasture, orchards and a ploughland) in SW Hungary since September 2018. Experiments were carried out in soils of silt, silt loam and clay loam texture. In the summers (June 1 to August 31) of 2019 and 2022, we identified normal and dry conditions, respectively, with regard to differences in water balance. Our results demonstrated that soil moisture is closely controlled by land use. Marked differences of the moisture regime were revealed among the three land use types based on statistical analyses. Soils under pasture had the most balanced regime, whereas ploughland soils indicated the highest amplitude of moisture dynamics. The orchard, however, showed responses to weather conditions in sharp contrast with the other two sites. Our results are applicable for loamy soils under humid and subhumid temperate climates and for periods of extreme droughts, a condition which is expected to be the norm for the future.

Estimating Sugarcane Yield in a Subtropical Climate Using Climatic Variables and Soil Water Storage

Brazil is the largest producer of sugarcane (Saccharum spp.) in the world, and this crop’s response to climate and soil water storage is essential for optimal management and genetic/yield improvements. The objective of our study was to build a multivariate model to estimate sugarcane yield in the subtropical conditions of the northwestern Paraná region using climatic and soil water storage variables. Observed yield data was used from experiments conducted at the Experimental Station of the Sugarcane Genetic Improvement Program of the Universidade Federal do Paraná. The sugarcane varieties RB72454, RB867515, RB966928, and RB036066 were analyzed in the 1998–2006, 2008, 2018 and 2019 harvest years. Stepwise multiple linear regression analysis with repeated cross-validation was developed to estimate sugarcane yield given climate and soil water storage variables for crop growth phases. The accumulated degree days in Phases I and II and soil water storage in Phase II of development significantly impacted sugarcane yield. The multiple linear regression model, with accumulated degree days and soil water storage in Phases I and II of development, successfully predicted sugarcane yield for analyzed varieties. Sugarcane production models like the one we developed can improve crop management for greater sustainability and climate change adaption in Brazil and other areas.

Опыт водосбережения при поливах овощных культур открытого грунта

Abstract. Purpose: on the basis of study and analysis of scientific sources to summa-rize the experience of water saving and to determine the features of modern irrigation regimes for vegetable crops in open ground. Discussion. Tomatoes and cucumbers are popular vege-table crops. The main areas of their cultivation in the country are the Southern and North Caucasian Federal Districts, where it is impossible to obtain yields without irrigation. The re-quirements of vegetable crops for moisture increase significantly during the periods of flower-ing, fruit setting and formation. Its deficiency during these periods leads to a decrease in productivity and a shortage of output. At present, both intensive irrigation with full irrigation rates and differential irrigation are practiced where irrigation is carried out with reduced irri-gation rates and the inter-irrigation periods and the number of watering are changed. An anal-ysis of the results of studies on tomato and cucumber cultivation on irrigated lands made it possible to determine that as a rule, under full irrigation, pre-irrigation soil moisture sill for these crops are maintained at least 80 % of the minimum moisture capacity. With differentiat-ed regimes, water saving is achieved by reducing the amount of irrigation water used. In this case, the differentiation criteria are the pre-irrigation soil moisture sill, the phases of crop growth and development, the depth of the calculated soil layer, the magnitude of irrigation rates, and the total evapotranspiration. The disadvantage of differentiated irrigation regimes is the lack of production, which can reach 14 % compared to the intensive irrigation regimes. Conclusions. An analysis of the water-saving experience during irrigating vegetable crops in open ground confirmed the effectiveness of differentiated irrigation regimes. Under such re-gimes, the yield decrease is not so significant, however, the most efficient use of irrigation water and higher product quality are noted. The combination of the optimal soil water regime and fertilization system contributes to the increase in the efficiency of production process of vegetable crops.

Почвенные влагозапасы и водный баланс посевов ячменя ярового на эрозионно опасном склоне

Purpose: to determine the influence of soil cultivation methods on the value of soil water storage, water balance and water consumption deficit of spring barley on an erosion-hazardous slope on ordinary chernozems. Materials and methods. During the research, the methodological approaches by S. A. Vorobyev, A. N. Kostyakov, S. I. Kharchenko, A. N. Postnikov were used. The experimental design provides for three options of soil cultivation: moldboard plowing, non-moldboard (chiseling) and combined (slotted) plowing. Results. As a result of the research, the advantage of chisel primary cultivation was revealed in terms of moisture reserves accumulation in snow: in the fall-plow it allowed accumulating on average 16.6 % more water than with moldboard tillage. Research has shown that the main flow component of water balance is the total water consumption of spring barley, which varied during the growing season depending on the phase of crop growth and development and on the method of soil cultivation; differences in the productive moisture reserves with the advantage of non-moldboard methods of soil cultivation were noted. The greatest differences were observed on the date of barley sowing; at this time, the excess in water storage in the meter layer was 9.9 % with combined tillage and it was 10.6 % with chiseling, relative to the same indicator with moldboard treatment. Conclusions. It was found that the intensity of the decrease in water storage rose, starting from the earing phase, especially during moldboard cultivation. In the longest period from sowing to booting (97–110 days), an average of approximately 50 % of the total moisture is consumed, from the booting phase to the earing and from the earing phase to milky-wax ripeness by 20 %, and in the last period from milky-wax ripeness to the complete ripeness of corn is only 10 % moisture. In general, during the growing season, non-moldboard cultivation allowed reducing the water consumption deficit of spring barley to 4.7–5.4 % compared to the control, which is very significant under the conditions of a moisture deficit amounting to 276 mm during this period.

Влияние основных приемов и способов возделывания ярового ячменя на площадь ассимиляционной поверхности и индекс листовой поверхности посевов в почвенно-климатических условиях Курской области

Purpose: to determine the influence of the cultivar, seeding rate and application of mineral fertilizers when cultivating spring barley on the assimilation surface area of one plant and the leaf surface index of crops according to the crop growth phases in the soil and climatic conditions of Kursk region. Materials and methods. The studies were conducted in 2022 and 2023 in the field experience at Federal Agricultural Kursk Research Center in grain-fallow crop rotation. The experimental scheme includes the study of three cultivars – Suzdalets, Prometheus, Despina. The second factor is seeding rates: 3, 4, 5, 6 million units of viable seeds per 1 ha. The third factor is the levels of mineral fertilization: control without fertilizers and N₃₀P₃₀K₃₀. Results. It was found that the assimilation surface area of one spring barley plant in the seedling stage depended to a greater extent on the cultivar (by 40 %), and it also increased under the influence of mineral fertilization (by 16 %). The leaf area index of spring barley in the seedling stage depended by 89 % on the seeding rate. During the tillering stage, the leaf area depended by 72 % on the year conditions. Research during the crop blooming stage revealed that the main factor influencing the assimilation surface area and leaf area index was the year of study (31 and 44 %, respectively), the cultivar factor provided 23 and 27 % of the indicator variation, respectively, and the mineral fertilization – 20 and 30 %, respectively. During the milk-ripe stage, due to the leaves dying off, a decrease in the photosynthetic parameters of spring barley is observed. Conclusion. It has been determined that the assimilation surface area of one plant and the leaf area index are very dynamic indicators and largely depend on the year of research, the cultivar and the mineral fertilization. During the initial period of crop growth, the leaf area index is affected by the seed application rate.

Utilization Pattern of Weather Based Agro-advisory Services among the Farmers of Nellore District of Andhra Pradesh

The success or failure of agricultural production is determined mainly by weather as it effect on every phase of crop growth, development and yield. Weather abnormalities during the crop season, would affect the crop growth and finally the quality and quantity of the yield. The advent of forecasting technologies and decision-making skills have not yet spread among small and marginal farmers who constitute major part of farming community in the country. Now a step further the Indian Council of agricultural Research (ICAR) and India Meteorological Department (IMD jointly planned to provide Agrometeorological Advisory Services (AAS) at block level in every district in both English and local language across the country for the benefit of farming community by setting up of District Agro-Meteorological Units (DAMUs) in the premises of KVKs to provide AAS to farmers. To understand the utilization pattern of the mobile AAS offered by the DAMU by the Krishi Vigyan Kendra (KVK), Nellore, Andhra Pradesh a survey was conducted. Sample size of 150 respondents was selected by employing proportionate random sampling method. The survey was carried out in terms of dimensions viz., technology adoption, information processing behaviour, information storage behaviour and information sharing behaviour. Results of the survey showed that nearly two-third of the respondents adopted Pest management practices and harvesting time information disseminated through agromet advisory system. Medium level of information processing behaviour was seen among the 66% of respondents, 48% of the respondents have medium information storage behaviour and around three-fourth (74%) of the respondents have medium level of information sharing behaviour.