Crop Growth Research Articles

Sustaining Soil Health in High Tunnels: A Paradigm Shift toward Soil-centered Management

This review was conducted to synthesize current knowledge, learn producer and Extension specialist perspectives, and identify gaps in understanding of the role of soil health in sustaining production in high tunnel (HT) systems. This synthesis includes findings from scholarly resources related to soil health in HTs, including research and Extension-based literature, perspectives from experienced HT producers and technical assistance providers, and the direct observations of a broad network of university research and Extension personnel working with HTs. Findings are intended to identify knowledge gaps and additional research and Extension resource needs of greatest priority to the HT producer community and technical assistance providers that support them at the time of publication. A review of 68 research articles and 58 Extension resources was conducted. Focus group interviews were conducted with small groups of experienced HT farmers in four regions of the eastern half of the United States, with in-depth farm case studies conducted in individual farmers in three of these regions. Growers across regions identified soil fertility management, soilborne diseases, soil compaction, and lack of consistency of soil analyses specific to HTs as the greatest soil-related challenges to HT production. Research and resources for technical assistance providers on mitigation strategies to remediate yield-limiting HT soil conditions, such as excessive soil salinity and high pathogen populations, were also lacking. As such, process-based research on techniques such as leaching, soil steaming, solarization, and anaerobic soil disinfestation in tunnels that consider short- and long-term costs, benefits, and effects on soil and plant productivity should be prioritized in the future when considering the impact of HT production on soil health. Interviews also indicated a need for networking opportunities for technical assistance providers across agencies (e.g., Natural Resources Conservation Service, Extension, nongovernmental organizations). Despite a high and increasing rate of adoption, there is currently a lack of information about maintaining HT systems. Given that HTs play a critical and growing economic role for specialty crop growers throughout the eastern United States, comprehensive intervention across the research–Extension spectrum to sustain productivity in HT systems is recommended.

The design and implementation of a smart greenhouse control system

Abstract Against the dual backdrop of continuously improving agricultural production levels and the global scarcity of water resources, countries worldwide are actively exploring the topic of water conservation. The development of an intelligent irrigation control system could make a significant contribution to water conservation efforts, while also helping to increase crop yields. This project adopts a modular design approach, utilizing sensors to collect real-time environmental data surrounding the crops. If the data falls outside the predefined optimal range for crop growth, the system automatically initiates irrigation, cooling, and supplemental lighting. The hardware design primarily consists of a data perception module and a control terminal module. After testing, the system runs stably and can accurately obtain information such as soil moisture, light intensity and ambient temperature, and basically realize the digital intelligent control of crop growing environment.

Progress in Research on Deep Learning-Based Crop Yield Prediction

In recent years, crop yield prediction has become a research hotspot in the field of agricultural science, playing a decisive role in the economic development of every country. Therefore, accurate and timely prediction of crop yields is of great significance for the national formulation of relevant economic policies and provides a reasonable basis for agricultural decision-making. The results obtained through prediction can selectively observe the impact of factors such as crop growth cycles, soil changes, and rainfall distribution on crop yields, which is crucial for predicting crop yields. Although traditional machine learning methods can obtain an estimated crop yield value and to some extent reflect the current growth status of crops, their prediction accuracy is relatively low, with significant deviations from actual yields, and they fail to achieve satisfactory results. To address these issues, after in-depth research on the development and current status of crop yield prediction, and a comparative analysis of the advantages and problems of domestic and foreign yield prediction algorithms, this paper summarizes the methods of crop yield prediction based on deep learning. This includes analyzing and summarizing existing major prediction models, analyzing prediction methods for different crops, and finally providing relevant views and suggestions on the future development direction of applying deep learning to crop yield prediction research.

Elevated concentrations of soil carbon dioxide with partial root-zone drying enhance drought tolerance and agro-physiological characteristics by regulating the expression of genes related to aquaporin and stress response in cucumber plants

Water scarcity and soil carbon dioxide elevation in arid regions are considered the most serious factors affecting crop growth and productivity. This study aimed to investigate the impacts of elevated CO2 levels (eCO2 at rates of 700 and 1000 ppm) on agro-physiological attributes to induce drought tolerance in cucumbers by activating the expression of genes related to aquaporin and stress response, which improved the yield of cucumber under two levels of irrigation water conditions [75% and 100% crop evapotranspiration (ETc)]. Therefore, two field experiments were conducted in a greenhouse with controlled internal climate conditions, at the Mohamed Naguib sector of the national company for protected agriculture, during the winter seasons of 2021–2022 and 2022–2023. The treatments included eCO2 in soil under normal and partial root zoon drying (PRD, 100% ETc Full irrigations, and 75% ETc). All the applied treatments were organized as a randomized complete block design (RCBD) and each treatment was replicated six times. Untreated plants were designed as control treatment (CO2 concentration was 400 ppm). The results of this study showed that elevating CO2 at 700 and 1000 ppm in soil significantly increased plant growth parameters, photosynthesis measurements, and phytohormones [indole acetic acid (IAA) and gibberellic acid (GA3)], under partial root-zone drying (75% ETc) and full irrigation conditions (100% ETc). Under PRD condition, eCO2 at 700 ppm significantly improved plant height (13.68%), number of shoots (19.88%), Leaf greenness index (SPAD value, 16.60%), root length (24.88%), fresh weight (64.77%) and dry weight (61.25%) of cucumber plant, when compared to untreated plants. The pervious treatment also increased photosynthesis rate, stomatal conductance, and intercellular CO2 concentration by 50.65%, 15.30% and 12.18%; respectively, compared to the control treatment. Similar findings were observed in nutrient concentration, carbohydrate content, Proline, total antioxidants in the leaf, and nutrients. In contrast, eCO2 at 700 ppm in the soil reduced the values of transpiration rate (6.33%) and Abscisic acid (ABA, 34.03%) content in cucumber leaves compared to untreated plants under both water levels. Furthermore, the results revealed that the gene transcript levels of the aquaporin-related genes (CsPIP1-2 and CsTIP4) significantly increased compared with a well-watered condition. The transcript levels of CsPIP improved the contribution rate of cell water transportation (intermediated by aquaporin’s genes) and root or leaf hydraulic conductivity. The quantitative real-time PCR expression results revealed the upregulation of CsAGO1 stress-response genes in plants exposed to 700 ppm CO2. In conclusion, elevating CO2 at 700 ppm in the soil might be a promising technique to enhance the growth and productivity of cucumber plants in addition to alleviating the adverse effects of drought stresses.

Optimizing Soil Moisture, Mulching, and Spacing for Yield and Water Productivity in Irrigated Elephant Foot Yam (Amorphophallus paeoniifolius)

Aims: To standardize crop spacing and irrigation requirements under different mulching situation for better yield and water productivity. Study Design: The experiment was designed in RBD with two replications. Place and Duration of Study: The experiment was conducted at Agronomic Research Station, Kerala Agriculture University (KAU), Chalakudy for three consecutive years from 2016 -17, 2017 – 18 and 2018 – 2019. Methodology: Study conducted with 18 treatments, includes three levels of irrigation, three types of mulching and with two different crop spacing. Observations on weed count and weed dry matter production were also taken to study the effect of different mulches on weed growth. Biometric observations of crop growth and yield were recorded. Results: Observations on biometric characters revealed that both the height and diameter of the crop canopy were significantly influenced by mulching and found to be highest in the plot where leaf was used as the mulching material and the yield of Amorphophallus during 2016 - 2017 showed that corm weight was greatly influenced by irrigation levels, mulching and spacing. Corm yield was lowest in the plot where irrigation frequency was once in three days (21.02 t/ha). Yield in leaf mulched plot was 38.11 t/ha while in plastic mulched and no mulched plots were 23.50 and 19.50 t/ha. Effect of treatments on water productivity and BC ratio showed that leaf mulching of the crop has significant effect. In leaf mulched plot, water productivity in 2016-17 was 2.03 while it was only 1.854 and 0.886 in 2017-18 and 2018-19. Similarly, BC ratio was highest for leaf mulched plot followed by no mulch and plastic mulch plot. Conclusion: The experimental results from 2016 -17, 2017 – 18 and 2018 – 2019, showed that Amorphophallus planted at a spacing of 90 cm x 90 cm, irrigated at a frequency of once in three days along with leaf mulching can increase the yield and water productivity along with effective control of weed population.

Navigating the Landscape of Precision Horticulture: Sustainable Agriculture in the Digital Age

Automation, autonomy, and precision play vital roles in modern technology and procedures, especially in response to the rising global population and the need for improved fruit production technologies. The quality criteria for fruit yield are becoming increasingly complex, necessitating fundamental upgrades. Sensor-based technologies pave the way for more rational and efficient soil usage. Precision farming, an advanced agricultural approach, employs software technologies and principles to optimize various aspects of horticultural production. Its goal is to enhance crop yields and promote environmental sustainability by managing spatial and temporal variations. Precision horticulture, a cutting-edge farming method, focuses on increasing crop yields and quality while minimizing environmental impact. This approach leverages advanced technology and data-driven decision-making. By utilizing sensors, robots, drones, and other innovative tools for yield mapping, irrigation control, robotic harvesting, nutrient and pesticide application, soil sensing, and crop growth analysis, growers can monitor plant growth and health, identify potential issues, and make informed crop management decisions. Tailoring practices to specific plant needs can lead to higher yields, improved product quality, and reduced environmental impact. Overall, precision horticulture holds significant promise for promoting sustainable agricultural practices while meeting the increasing demand for food production.

Climatic suitability and development potential of facility agriculture at county-level in China

Facility agriculture is a modern cultivation system that utilizes certain facilities and engineering techniques to create a suitable environment for crops growth, which can ensure China's national food security and human nutrition. Both beneficial and limited climatic conditions have influenced the development for facility agriculture. In this study, 12 dominant factors were distilled by using Maximum Entropy model (MaxEnt) to quantify climatic suitability of facility agriculture and its variation in counties across China in 1991–2020. The climatic suitable areas for facility agriculture were mainly distributed in the southern part of Northeast China, North China, central China, southern part of Southwest China, and northern part of East China, especially during 2000–2020. There was a general fluctuating upward trend in the climatic suitability of facility agriculture in traditional advantageous production areas such as Jiangsu, Shandong, Hebei, and Liaoning. Positive trends in the changes of climatic suitability were detected in central and eastern China where rapid development of facility agriculture could be realized through scientific planning and layout. Western provinces such as Gansu, Shaanxi, and Inner Mongolia were highlighted as considerable development potential for facility agriculture, with the perspective of developing energy-saving solar greenhouses in especial. These distribution characteristics and potential changes of climate suitability would help to optimize production layout and achieve green and sustainable development of facility agriculture.

Improving the simulation accuracy of summer maize growth and yield by pixel-based parameterization based on assimilating upscaled MODIS LAI

Accurately simulating maize (Zea mays L.) yield at the regional scale is of paramount importance for making informed policy adjustments and for ensuring food security. Sobol sensitivity analysis was used in this study to screen sensitive parameters of a process-based crop model (Chinese Agricultural Meteorological Model, CAMM). An upscaling approach was utilized to reduce the intra-pixel heterogeneity error of MODIS LAI. Then upscaled MODIS LAI data were assimilated into the CAMM model through a 4DVar assimilation algorithm to optimize pixel-level sensitive parameters, thereby improving the simulation accuracy of the summer maize growth process and yield. Specific leaf area (SLATB_0, SLATB_1) during the period from emergence to tasseling of summer maize exhibited the strongest impact on summer maize yield. Additionally, the average LAI value within the 85–95 % range of ordered LAI values for small pixels within large pixels effectively reduced the intra-pixel heterogeneity error of MODIS LAI, and pixel-based parameterization of SLATB_0 and SLATB_1 at a larger pixel scale (0.0625°) was achieved. Based on yields recorded at agrometeorological stations from 2015 to 2020, assimilated yields in both data assimilation scheme 1 (DA1, optimization of only the sensitive parameter SLATB_0) and scheme 2 (DA2, simultaneous optimization of sensitive parameters SLATB_0 and SLATB_1) exhibited higher accuracy than schemes without data assimilation (with r values of 0.41–0.72 and NRMSE values of 19–30 %). Furthermore, DA2 showed greater simulation accuracy (r: 0.64–0.93, NRMSE: 9–21 %) than DA1 (r: 0.61–0.91, NRMSE: 12–23 %). Upscaling remotely sensed LAI products can significantly reduce the uncertainties of LAI data at a larger pixel scale, and assimilating these LAI data into crop models can effectively increase the simulation accuracy of crop growth and development processes at the regional scale.

Polyvinyl chloride microplastics and drought co-exposure alter rice growth by affecting metabolomics and proteomics

Microplastics, interacting with drought stress, have become threat to crops by altering soil environment. Currently, the effect of combined microplastic and drought stress on crop growth remain poorly understood. In this work, the mechanism of multi-stress responses was investigated under the exposure of polvinylchloride microplastic (PV) and drought (D) individually and in combination (DPV) on rice varieties Hanyou73 and Q280 through proteomics and metabolomic analysis. All treatments negatively affect chlorophyll content, antioxidant enzyme activities, rice grain composition, metabolome and proteomic profiling of both rice varieties. Full rice grain yield was decreased under all treatments except PV treatment in which it was increased in both rice varieties. DPV treatment shows the lowest grain yield and more adverse effects on metabolome by affecting glycerophospholipid metabolism, tryptophan metabolism and alanine, aspartate and glutamate metabolism. Soluble sugar contents were decreased in H73 but in Q280 increased by 159 % under DPV and 123 % in PV treatment, compared to their control group. The results from metabolomics illustrate that glycerophospholipid metabolism is commonly altered in both rice types under all treatments. PV and drought alone and in combination induce extensive alterations in proteomics of rice leaves especially impacting proteins related to binding, translation and photosynthetic process. The results reveal that PV and DPV treatments highly distort the abundance of metabolites and proteins in both rice types, demonstrating that microplastic toxicity effects on rice plants become more severe when combined with drought stress.

Spatial and Temporal Patterns of Maize Phenology in China From 2001 to 2020

AbstractClimate change has significantly altered crop phenology, which has further impacted crop growth and yield. Accurate monitoring of crop phenology is essential for managing agricultural production in response. However, regional monitoring requires high spatial resolution distribution data, as medium resolution data suffers from mixed pixel issues. This study based on a long‐term high spatiotemporal resolution fusion data set of Normalized Difference Vegetation Index and an annually updated maize distribution data set, used the relative threshold method to identify the maize phenology in 22 provinces of China from 2001 to 2020. We further analyzed the trend of maize phenology and assessed its responses to climate change. The results reveal large inter‐annual fluctuations and spatial variability in maize phenology from 2001 to 2020. The length of the growth season (LOS) of spring maize has prolonged by 4.28 days in the northern maize zone and has shortened by 4.90 days in the southern maize zone. Additionally, the LOS of summer maize in the Huang‐Huai‐Hai region has shortened by 2.24 days. We also found a positive correlation between the length of the vegetative growth stage and the mean temperature and a negative correlation between the length of the reproductive growth stage and accumulated precipitation. This study utilized large‐scale, high‐resolution maize phenology data to analyze the trend of maize phenology and its response to climate change. These findings are expected to provide valuable support for assessing maize growth status and developing agricultural adaptive practices.

Straw management and fertilization improve soil aggregate stability by inducing biological binding agents and specific keystone genera

Improving soil aggregate stability through proper fertilization management is essential for crop growth. However, how different fertilization regimes affect soil aggregate stability driven by microorganisms and biological binding agents remains largely unexplored. For this purpose, we conducted a 9-year field experiment involving two soil textures (i.e., loam and clay soils) and five fertilization regimes (i.e., no fertilizer or crop straw return (CK), crop straw return (S), chemical fertilization (N), crop straw return with chemical fertilizer (SN), and crop straw return with chemical fertilizer and 20% nitrogen substituted with chicken manure (SNM)). Mean weight diameter (MWD) of soil aggregates, glomalin-related soil protein (GRSP) content, and microbial community composition were investigated. The SN and SNM treatments had similar MWD, which was 70.08–76.45% higher than the CK, and the S and N treatments had similar MWD, which was 20.35–34.76% higher than the CK, indicating better effects of SN and SNM on the improvement of the soil aggregate stability than the S or N treatment. High easily extractable GRSP and total GRSP contents contributed to the improved MWD. Meanwhile, some specific keystone genera identified from the keystone modules (co-occurring groups of soil biota including arbuscular mycorrhizal fungi, bacteria, and nonmycorrhizal fungi) were recognized as the important factors regulating the MWD, though the selected specific genera in the loam soil differed from the clay soil. Altogether, our results highlighted the fundamental role of the GRSP and selected specific keystone microbial taxa in improving the soil aggregate stability and provided a list of microbial taxa linking to MWD in different soils, which could be specifically targeted in specific soil.

Phenological Adaptation Is Insufficient to Offset Climate Change-Induced Yield Losses in US Hybrid Maize.

Climate change is projected to decrease maize yields due to warmer temperatures and their consequences. Studies using crop growth models (CGMs), however, have predicted that, through a combination of alterations to planting date, flowering time, and maturity, these yield losses can be mitigated or even reversed. Here, we examine three assumptions of such studies: (1) that climate has driven historical phenological trends, (2) that CGM ensembles provide unbiased estimates of yields under high temperatures, and (3) that the effects of temperature on yields are an emergent property of interactions between phenology and environment. We used data on maize phenology from the United States Department of Agriculture, a statistical model of maize hybrid heat tolerance derived from 80 years of public yield trial records across four US states, and outputs of an ensemble of CMIP6 climate models. While planting dates have advanced historically, we found a trend toward later planting dates after 2005 and no trend for silking or maturity, shifting more time into the reproductive period. We then projected maize yields using the historical model and crop calendars devised using three previously proposed adaptation strategies. In contrast to studies using CGMs, our statistical yield model projected severe yield losses under all three strategies. Finally, we projected maize yields accounting for historical genetic variability for heat tolerance, discovering that it was insufficient to overcome the negative effects of projected warming. These projections are driven by greater heat stress exposure under all crop calendars and climate scenarios. Combined with analysis of the internal sensitivities of CGMs to temperature, our results suggest that current projections do not adequately account for the effects of increasing temperatures on maize yields. Climate adaptation in the US Midwest must utilize a richer set of strategies than phenological adaptation, including improvements to heat tolerance and crop diversification.

Multi-functional PGPR Serratia liquefaciens confers enhanced resistance to lead stress and bacterial blight in soybean (Glycine max L.)

Lead toxicity and bacterial blight disease caused by Pseudomonas savastanoi pv. glycinea have destructive impacts on soybean growth and productivity. Plant growth-promoting rhizobacteria have been used as an eco-friendly approach for augmenting crop growth and stress resistance. The current study investigated the efficacy of Serratia liquefaciens ZM6 strain in enhancing soybean resistance to lead (Pb) stress and bacterial blight. Two pot experiments were performed. In the first pot experiment, soybean plants were inoculated with S. liquefaciens ZM6 and grown under variable Pb stress levels (0, 200 and 400µM of Pb(NO3)2). In the second experiment, S. liquefaciens-inoculated soybean plants were infected with P. savastanoi pv. glycinea, and disease severity was assessed two weeks post infection. The results revealed that S. liquefaciens strain resisted Pb stress up to 400µM Pb(NO3)2 and exhibited the highest levels of solubilized phosphate, solubilized zinc, siderophore, indole acetic acid, exopolysaccharide, trehalose and antioxidant enzymes at 400µM Pb compared to the other treatments. Moreover, Pb stress (200 and 400µM) significantly decreased the growth, yield, nutrient uptake, gas exchange, and contents of chlorophyll, soluble proteins, sugars, and phenolics of soybean plants. Pb stress also induced the levels of proline, glycine betaine, Pb, oxidative stress markers, antioxidant enzymes, ascorbate, glutathione and expression of stress-responsive genes (CAT, APX, POD, Fe-SOD, CHS7, CHI1A, PAL, IFS2, P5CS and WRKY54) in soybean plants. On the other hand, S. liquefaciens application markedly boosted the growth, yield and levels of nutrients, gas-exchange, chlorophyll, osmolytes, antioxidant enzymes and expression of stress-tolerant genes of Pb-stressed soybean plants. The bacterial inoculation significantly diminished oxidative stress indicators and Pb content in stressed plants. Inoculation of soybean plants with S. liquefaciens also caused significant reductions in blight disease symptoms in P. savastanoi pv. glycinea-infected plants, indicating the efficiency of this strain in controlling harmful blight disease. Overall, this study demonstrated S. liquefaciens ZM6 effectiveness in enhancing soybean resistance to Pb stress and bacterial blight.

Assessment of Growth and Yield Characteristics of a Greenhouse Hybrid and a Dual-Purpose Tomato Cultivar under Different Microclimatic Conditions

Tomato (Solanum lycopersicum L., family Solanaceae) represents one of the most cultivated horticultural crops worldwide. It contains various nutrients, providing health benefits. For better crop management strategies, especially with global warming, it is crucial to investigate how varieties or cultivars bred for different purposes respond to the changing macro or microenvironmental conditions. This research aimed to assess the growth, reproductive development and selected quality parameters of two tomato varieties, ‘Sylviana’ (a greenhouse hybrid) and ‘Bolseno’ (a dual-purpose variety), under a greenhouse environment. The study was conducted in the mid-country wet zone of Sri Lanka where the intensive-control greenhouse (T1) maintained a favourable air temperature (<33°C) for crop growth compared to high daytime temperatures of semi-intensive (T2) and less-intensive (T3) greenhouses (up to 36°C). In ‘Bolseno’, vegetative growth parameters were significantly affected (P<0.05) by different environments but not in ‘Sylviana’ (P>0.05). T1 resulted in the highest mean fruit weight and mean fruit diameter in both varieties. Since ‘Sylviana’ performed well in all three growing environments, the fruit quality was assessed by measuring the antioxidant activity (AOX) and total phenolic content (TPC) using 1, 1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging assay and Folin–Ciocalteu method, respectively. Significantly higher AOX (P<0.05) was reported in T1 while T2 had a higher TPC. The results revealed that different tomato genotypes respond differently to changes in micro environmental conditions in terms of growth and some reproductive traits, and the same variety grown in different conditions had different TPC and AOX.

Proline Priming Enhances Seed Vigour and Biochemical Attributes of Rice (Oryza sativa L.) during Germination.

Seed vigour is a desirable trait especially for direct seeded rice (DSR) cultivation. Seeds with high vigour could improve seed germination, support seedlings in competing with weeds for water and nutrients, and improving seedling establishment throughout the early stages of crop growth. The success of DSR system which account for more 25% of world cultivation areas is highly dependent on the seed vigour and seedling establishment. Seed priming is a promising technique to improve seed vigour. Proline is an amino acid that has been well studied for its roles in plants under different environmental stress conditions. Nevertheless, the effect of proline as a seed priming agent in improving seed vigour in rice remain elusive. In this research, the effect of 24 h of proline priming at various concentrations (0 mM, 1 mM, 2 mM, 10 mM and 20 mM) on rice seed vigour, amylase activity, and total soluble sugar (TSS) content of a Malaysia indica rice variety, MR269 was investigated. Results showed that seeds primed with lower concentration of proline (0 mM, 1 mM and 2 mM) had better germination responses while priming at high concentrations (10 mM and 20 mM) reduced seed germination. Among the concentration tested, priming with 1 mM proline enhanced seed vigour with significantly higher germination percentage (GP), germination rate index (GRI) and seedling vigour index (SVI). In addition, proline primed seeds also exhibited increased amylase activity and TSS content as compared to unprimed seeds. However, priming seed with 20 mM proline was detrimental to the seed vigour and seedling growth whereby lower GP, GRI and SVI and higher mean germination time (MGT) were observed. In short, this study shows that proline could be a potential seed priming agent to improve seed vigour in rice.

Resistance Mechanisms of Plant Pathogenic Fungi to Fungicide, Environmental Impacts of Fungicides, and Sustainable Solutions

The significant reduction in agricultural output and the decline in product quality are two of the most glaring negative impacts caused by plant pathogenic fungi (PPF). Furthermore, contaminated food or transit might introduce mycotoxins produced by PPF directly into the food chain. Eating food tainted with mycotoxin is extremely dangerous for both human and animal health. Using fungicides is the first choice to control PPF or their toxins in food. Fungicide resistance and its effects on the environment and public health are becoming more and more of a concern, despite the fact that chemical fungicides are used to limit PPF toxicity and control growth in crops. Fungicides induce target site alteration and efflux pump activation, and mutations in PPF result in resistance. As a result, global trends are shifting away from chemically manufactured pesticides and toward managing fungal plant diseases using various biocontrol techniques, tactics, and approaches. However, surveillance programs to monitor fungicide resistance and their environmental impact are much fewer compared to bacterial antibiotic resistance surveillance programs. In this review, we discuss the PPF that contributes to disease development in plants, the fungicides used against them, factors causing the spread of PPF and the emergence of new strains, the antifungal resistance mechanisms of PPF, health, the environmental impacts of fungicides, and the use of biocontrol agents (BCAs), antimicrobial peptides (AMPs), and nanotechnologies to control PPF as a safe and eco-friendly alternative to fungicides.

METHODS OF FORECASTING GRAIN CROP YIELD INDICATORS TAKING INTO ACCOUNT THE INFLUENCE OF METEOROLOGICAL CONDITIONS IN THE INFORMATION-ANALYTICAL SUBSYSTEM

Forecasting crop yields is one of the key challenges for the agricultural sector, especially in the context of a changing climate and unstable weather conditions. Kazakhstan, possessing significant territories suitable for growing grain crops, faces many challenges related to the effective management of agricultural activities. In this regard, yield forecasting becomes an integral part of planning and decision-making processes in agriculture. Information and analytical subsystems that integrate yield forecasting methods allow agribusinesses to estimate future production more accurately, minimise risks associated with climate change and optimise resource use. An important component of such systems is the consideration of weather conditions, as weather factors have a direct impact on crop growth and development. The purpose of this article is to develop and evaluate modern methods of forecasting grain yields taking into account the influence of weather conditions, as well as their integration into information-analytical subsystems to improve the accuracy of agricultural forecasting. To achieve this goal, the article addresses the following tasks: to analyse existing methods of yield forecasting and identify their advantages and disadvantages, to develop forecasting models, including machine learning methods such as gradient bousting and recurrent neural networks, to validate the developed models on the basis of historical data using cross-validation methods, to evaluate the effectiveness of the proposed methods and compare them with basic models such as linear regression and simple average, to evaluate the effectiveness of the proposed methods and to compare them with the basic models such as linear regression and simple average. This article reviews modern methods of forecasting grain crop yields in Kazakhstan, as well as technologies used in information-analytical subsystems. Particular attention is paid to the analysis of the influence of meteorological conditions on yields and the development of models that take this factor into account. The presented review and research results are aimed at improving the existing approaches to the management of agricultural processes under conditions of growing uncertainty caused by climate change. The article explores an important scientific task related to the development of methods for step-by-step forecasting of agrometeorological factors and grain yields, relying on the principle of analogy.

ORGANIC FERTILIZER: NEED OF INDIA

Organic fertilizers are naturally available mineral sources that contain moderate amount of plant essential nutrients. They are capable of mitigating problems associated with synthetic fertilizers. They reduce the necessity of repeated application of synthetic fertilizers to maintain soil fertility. They gradually release nutrients into the soil solution and maintain nutrient balance for healthy growth of crop plants. They also act as an effective energy source of soil microbes which in turn improve soil structure and crop growth. Organic fertilizers are generally thought to be slow releasing fertilizers and they contain many trace elements. They are safer alternatives to chemical fertilizers. However, the improper use of organic fertilizers leads to overfertilization or nutrient deficiency in the soil. Hence, controlled release of organic fertilizers is an effective and advanced way to overcome these impacts and maintain sustainable agriculture yield.[a]

Effects of Metribuzin on Soil Microbiome and Weed Management Under Varying Planting Practices and Potato Seed Dormancy

AbstractWeed infestation in potato field has become a major concern to smallholder farmers and environment, requiring sustainable intervention. This study aimed to determine (i) whether metribuzin application rate (0, 0.5, 1 (standard), 1.5, and 2 kg ai ha−1) has effects on soil microbes and soil nutrients in the short term using potted soil and (ii) the influence of potato seed dormancy (short; Shangi variety and long; Unica variety) and planting technique (surface, ridge, or furrow planting) on the efficacy of weed management practice (metribuzin (480 g L−1) herbicide and hoeing) in the field. Bacterial colony counts were recorded upon isolation from the potted soil. Soil nutrients were also analysed before and after metribuzin treatment. Data on crop growth (height and stem count), weed abundance, yield, costs, and revenues were recorded from a field experiment. Morphologically distinct bacterial strains were tested for Gram reaction and response to carbon utilization using analytical profile index kits (API 50 CH and 20 NE). In total, nine distinct bacterial strains were isolated and all were Gram positive, with variation in response to carbon substrates. Concentration of 2.0 kg a.i ha−1 significantly (p ≤ 0.05) reduced bacterial count in the first day, followed by an increase in the subsequent incubation days, while 1.0 and 1.5 kg a.i ha−1 concentrations had the highest colony development index and species richness. Significant effects of metribuzin on soil pH, total N, and total organic C in the short term were revealed. Notably, weedy plots had the highest Shannon weed index. Weeds reduced stem count and height growth by 57% and 62% respectively. Plots with Shangi had 9.8% lower weed count than those with Unica and hence higher yield was recorded from the former. While surface planting had the lowest weed control efficacy, crop growth attributes, and yield, furrow and ridge planting were not significantly different. Weed abundance and crop growth attributes in metribuzin and hand-hoed plots did not differ significantly, yet hoeing resulted in 5.30 t ha−1 above that obtained from plots managed using metribuzin. Higher dry matter and tuber yield were observed from hoed plots with Shangi planted in furrow or ridge. Use of metribuzin resulted in higher net benefit ratio and marginal rate of return than hand hoeing. The results reveal that use of metribuzin early and later in the potato growing phase can minimize weed infestation, but the efficacy depends on planting method and seed dormancy.

Investigating the Influence of Inorganic and Organic Fertilizers on the Growth and Yield of Three Varieties of Okra (<i>Abelmoschus esculentus</i>)

Fertilizers play an important role in enhancing crop yield, growth, and fertility of the soil. This research was conducted at the Faculty of Agriculture teaching and research farm, University of Port Harcourt, Nigeria to investigate the influence of inorganic fertilizer (urea) and organic manure (spent mushroom substrate and poultry manure) on the yield and growth parameters of three okra cultivars (Clemson Spineless, Perkin Long Pod and the Local Assertion). The urea was applied at the rate of 4g per 10kg of soil, while spent mushroom substrate and poultry manure were applied at the rates of 200g and 150g per 10kg of soil respectively at 4 weeks after planting. The treatments were laid in a completely randomized design (CRD) with 3 replications. The results revealed that the okra cultivars responded positively to both organic manures when compared with urea and the control group where no fertilizer was applied. Furthermore, varieties grown with poultry manure generally had the highest fresh fruit weight, plant height, fruit length, number of fruits, and fresh fruit yield. Spent mushroom substrate influenced the number of fruits and fruit yield while urea influenced the leaf area, number of leaves, and leaf area index. Poultry manure was recorded as the best organic manure for okra growth and yield and is recommended to be used to grow okra plants. Also, the Perkin Long Pod variety is recommended to be the best for cultivation.