Long-term Crop Research Articles

Effects of long-term nitrogen and phosphorus fertilization on soil phosphorus forms and dynamics under continuous wheat production in Saskatchewan, Canada

Many agricultural crops require both nitrogen (N) and phosphorus (P) fertilizers to sustain crop yields. However, long-term application of NH4–N fertilizers can cause soil acidification, which alters soil abiotic and biotic processes, including soil P dynamics. Long-term continuous wheat plots in Saskatchewan, Canada, were used to assess effects of N and P fertilization from 1967 and P fertilizer cessation in subplots from 1995. General soil chemical properties and soil P pools and forms were determined and then correlated with soil pH, total N (TN), and total P (TP) concentrations to show the relative importance on soil P dynamics of (a) crop nutrition (TN and TP); (b) soil acidification (pH); or (c) P fertilization/cessation. Fertilization with NH4–N decreased soil pH and altered exchangeable cation concentrations; however, long-term crop growth was poor in no-N plots and was best with both N and P fertilizers, in turn increasing soil carbon and organic matter. Applying P fertilizers without N increased soluble phosphates and the risk of P losses in runoff. Soil organic P (TPo) concentrations were correlated negatively to pH and positively to TN, but the concentrations of P compounds were not correlated to pH. This suggests that TPo accumulation may be from increased long-term crop residue inputs from crops with N and P fertilizers, rather than increased sorption from reduced pH. However, soil pH will continue to decrease with continued NH4–N fertilization, affecting soil chemistry and future P cycling; monitoring with a suite of wet chemistry and spectroscopic techniques is recommended.

Machine learning reveals dynamic controls of soil nitrous oxide emissions from diverse long-term cropping systems.

Soil nitrous oxide (N2O) emissions exhibit high variability in intensively managed cropping systems, which challenges our ability to understand their complex interactions with controlling factors. We leveraged 17 years (2003-2019) of measurements at the Kellogg Biological Station Long-Term Ecological Research (LTER)/Long-Term Agroecosystem Research (LTAR) site to better understand the controls of N2O emissions in four corn-soybean-winter wheat rotations employing conventional, no-till, reduced input, and biologically based/organic inputs. We used a random forest machine learning model to predict daily N2O fluxes, trained separately for each system with 70% of observations, using variables such as crop species, daily air temperature, cumulative 2-day precipitation, water-filled pore space, and soil nitrate and ammonium concentrations. The model explained 29%-42% of daily N2O flux variability in the test data, with greater predictability for the corn phase in each system. The long-term rotations showed different controlling factors and threshold conditions influencing N2O emissions. In the conventional system, the model identified ammonium (>15 kg N ha-1) and daily air temperature (>23°C) as the most influential variables; in the no-till system, climate variables such as precipitation and air temperature were important variables. In low-input and organic systems, where red clover (Trifolium repens L.; before corn) and cereal rye (Secale cereale L.; before soybean) cover crops were integrated, nitrate was the predominant predictor of N2O emissions, followed by precipitation and air temperature. In low-input and biologically based systems, red clover residues increased soil nitrogen availability to influence N2O emissions. Long-term data facilitated machine learning for predicting N2O emissions in response to differential controls and threshold responses to management, environmental, and biogeochemical drivers.

Effect of Eighteen Years of Continuous Crop Residue Application on Crop Yields, Soil P Fractions, and Crop P Uptake in Conservation Tillage Under Semi-Arid Tropical Rainfed Conditions

The continuous use of crop residue in soil can enhance the crop yield and potential availability and mobility of P fractions to crops in conservation tillage. A field experiment was conducted to assess the long-term effects of surface crop residue applications on soil P fractions and their relationship with P uptake and crop yields. Field experiment was conducted at ICAR-Central Research Institute for Dryland Agriculture, Hyderabad, India during 2005 to 2022. The experimental treatments applied were: T1 - no crop residue application, T2 - application of crop residue @ 2 t ha-1, T3 - application of crop residue @ 4 t ha-1, and T4 - application of crop residue @ 6 t ha-1 in conservation tillage. The test crops viz. sorghum (Sorghum vulgare) and cowpea (Vigna unguiculata) were grown in a yearly rotation every year in the kharif season in conservation tillage. The results of the long-term study revealed that the per cent increase in sorghum (Sorghum vulgare) grain yield with the application of crop residue at the rate of 2, 4 and 6 t crop residue ha-1was to the tune of 7.9, 16.1 and 26.0%, respectively over no crop residue application. Similarly, the per cent increase in the cowpea (Vigna unguiculata) seed yield was to the extent of 25.2, 43.0 and 64.1% in 2, 4 and 6 t ha-1, respectively over no crop residue application. The sorghum and cowpea stover yield also significantly (p=0.05%) increased with the added levels of the crop residue. Significantly higher P uptake by sorghum and cowpea was recorded in 6 t crop residue ha-1 as compared to the other crop residue treatments. Results of the current study also showed the significant positive response of long-term crop residue application on the P fractions viz., water-soluble phosphorus (WS-P), aluminum bound P (Al-P), iron bound P (Fe-P), calcium bound P (Ca-P) and reductant soluble P (RS-P), and on available P and total P in soil as compared to no crop residue application. The average percent contribution of P fractions toward the sum-total of extracted P was in the order: Fe-P (30.8%)>RS-P (30.7%)>Al-P (24.2%)>Ca-P (9.4%)>WS-P (4.8%). The WS-P and Al-P were found to be the P fractions indicating their specificity by cowpea crop, and WS-P and Ca-P were found to be P fractions indicating their specificity by sorghum crop. The results of the present study will be highly useful in understanding the effect of crop residue application in conservation tillage on the P fractions and their contribution toward P uptake and crop yields.

Long-term continuous cropping reduces greenhouse gas emissions while sustaining crop yields.

Information is needed on the effect of long-term cropping systems on greenhouse gas (GHG) emissions in dryland conditions. The effect of 34 years of dryland cropping system was examined on N2O and CH4 emissions, greenhouse gas balance (GHGB), crop yield, and yield-scaled GHG balance (YSGB) from 2016-2017 to 2017-2018 in the US northern Great Plains. Cropping systems were no-till continuous spring wheat (Triticum aestivum L.) (NTCW), no-till spring wheat-pea (Pisum sativum L.) (NTWP), and conventional till spring wheat-fallow (CTWF). Gases were sampled twice a week to once a month throughout the year using a static chamber and flux determined. Soil C sequestration rate at 0-10cm was determined from samples taken in 2012 and 2019. The N2O emissions occurred immediately after planting, fertilization, and intense rainfall from May to September in both years when the emissions greater for NTCW and NTWP than CTWF. The CH4 emissions were minimal and mostly negative throughout the year. Carbon sequestration rate was positive for NTCW and NTWP due to greater C input, but negative for CTWF due to rapid C mineralization. As a result, GHGB was 170%-362% lower for NTCW than NTWP and CTWF. Annualized crop yield was 23%-60% greater for NTWP than NTCW and CTWF in 2016-2017, but not different among cropping systems in 2017-2018. The YSGB was also 129%-132% lower for NTCW and NTWP than CTWF in both years. Because of greater annualized crop yield, but lower GHG emissions, NTWP is recommended for reducing GHG emissions while sustaining long-term dryland crop yields in the northern Great Plains.

ALIH USAHATANI PADI SAWAH KE TANAMAN JERUK NIPIS (Citrus auratifolia) DI DESA TRIDANA MULYA KECAMATAN LANDONO KABUPATEN KONAWE SELATAN

The objective of this study is to ascertain the underlying factors that precipitate the transition from wet-rice farming to lime farming, as well as to examine the impact of such farming conversions among farmers in Tridana Mulya Village. The study population was comprised of two groups: a group of 31 lime farmers and a group of seven rice farmers. The sampling technique employed was the census method, which entailed the inclusion of the entire population, resulting in a research sample of 38 individuals (31 lime farmers and 7 rice paddy farmers). Data were collected through the use of interview techniques, observation, and documentation of media sources in the form of questionnaires. The variables under investigation are the factors that influence the transfer of farming and the impact of such transfer. The data were analyzed using a descriptive method and an income formula. The results demonstrated that the factors that precipitated the transition from paddy rice farming to lime farming were attributable to a confluence of production, economic, and cultivation-related considerations. The production yield factor of lime farming has demonstrated an increase in production compared to paddy rice farming in Tridana Mulya Village. In terms of economic factors, lime farming has been shown to yield higher profits for farmers than paddy rice farming. Additionally, the cultivation factors associated with lime farming are considerably more straightforward, as the land only requires processing once, due to the fact that lime is a long-term crop, in contrast to paddy rice farming, which is dependent on seasonal conditions. The impact of switching farms includes both economic and environmental consequences. From an economic standpoint, farmers' income may change after switching from paddy rice farming to lime crops. This is because lime crops may yield higher profits than paddy rice, depending on various factors. From an environmental standpoint, the lack of use of chemical fertilizers or pesticides in lime farming may reduce the impact on the environment. This is in contrast to the opposite condition observed in paddy rice farming.

Hazards of toxic metal(loid)s: Exploring the ecological and health risk in soil–crops systems with long-term sewage sludge application

Sewage sludge (SS) is commonly used as agricultural fertilizer worldwide. However, the toxic metal(loid)s in SS raises concerns about soil contamination and the potential risks to human health. This study, conducted since 2007 on the North China Plain, examines the impact of SS use on crops. An experiment was designed with five treatments: conventional fertilization (CK) and four levels of SS application (W1, W2, W3, and W4: 4.5, 9.0, 18.0, and 36.0 t ha−1, respectively). Soil concentrations of eight toxic metal(loid)s (Zn, Cu, Cr, Cd, Ni, Pb, As, and Hg) were analyzed to assess pollution risk using various indices. Health risks associated with maize and wheat grains were also evaluated. Additionally, the impact of long-term SS application on crop yield, soil quality, and human health within a wheat-maize rotation system was examined. SS application increased wheat and maize yields by 5.37 to 19.08 % and 6.97 to 17.94 %, respectively, across treatments W2 to W4. Despite the toxic metal(loid)s in the grains remaining within safe limits, their concentrations showed an upward trend, especially under the W4 treatment. Moreover, SS application significantly increased the soil Zn, Cu, Cr, Cd, Pb, and Hg levels (P < 0.05) without exceeding the national standards. The geo-accumulation index values revealed rising pollution levels for Zn, Cu, Cd, and Hg, which shifted from no contamination to moderate contamination and then to moderate-to-high contamination, yet the overall pollution level remained safe. Soil ecological risks increased from moderate to serious, with Hg posing the greatest risk, particularly under the W4 treatment. Long-term crop intake from the area significantly exposed children and adults to As, contributing 42.12 % and 34.62 % to hazard index (HI), respectively. The HI values for toxic metal(loid)s in these grains surpassed one in both age groups, suggesting health risks from long-term SS cultivated crops.

Pendampingan dan Penguatan Kapasitas Masyarakat dalam Pemulihan Kerusakan Lingkungan di Provinsi Sulawesi Barat

Community empowerment begins with understanding that every individual and group has potential and abilities that can be developed. In Mamuju Regency, precisely in Tommo District, there is peat but it is small which if damaged and not managed properly will result in land fires, floods, and soil pollution. This assistance aims to position the community as a party that plays an active role in environmental recovery. One of the initial stages of assistance or empowerment activities carried out is Problem Identification and Situation Analysis. It is hoped that the problems faced can be clearly identified, the related situation can be analyzed comprehensively, and the next steps can be designed to plan effective and sustainable interventions. Strengthening the understanding of problem identification and location analysis is carried out using the IMAS tool through survey methods, interviews, and FGDs. The results of problem identification and situation analysis found several problems that can be used as references in formulating systematic and effective planning for community empowerment. Based on the results of the problem identification and situation analysis in Buana Sakti Village, Tamemongga Village, Tamejarra Village, West Leling Village and North Leling Village, problems were found in flooding, lack of fertilizer availability and the distance of the village from the city which makes it difficult to get fresh fish to meet the protein needs of the community. From the results of the problem identification and situation analysis, a Community Work Plan formulation was formed such as freshwater fish farming, long-term crop planting, horticultural planting, and livestock farming. The proposed work plan is expected to be able to help the community in meeting needs, improving the community's economy, and can answer problems that occur in each village.

Redundancy in microbiota-mediated suppression of the soybean cyst nematode

BackgroundSoybean cyst nematodes (SCN) as animal parasites of plants are not usually interested in killing the host but are rather focused on completing their life cycle to increase population, resulting in substantial yield losses. Remarkably, some agricultural soils after long-term crop monoculture show a significant decline in SCN densities and suppress disease in a sustainable and viable manner. However, relatively little is known about the microbes and mechanisms operating against SCN in such disease-suppressive soils.ResultsGreenhouse experiments showed that suppressive soils (S) collected from two provinces of China and transplantation soils (CS, created by mixing 10% S with 90% conducive soils) suppressed SCN. However, SCN suppressiveness was partially lost or completely abolished when S soils were treated with heat (80 °C) and formalin. Bacterial community analysis revealed that the specific suppression in S and CS was mainly associated with the bacterial phylum Bacteroidetes, specifically due to the enrichment of Chitinophaga spp. and Dyadobacter sp., in the cysts. SCN cysts colonized by Chitinophaga spp. showed dramatically reduced egg hatching, with unrecognizable internal body organization of juveniles inside the eggshell due to chitinase activity. Whereas, Dyadobacter sp. cells attached to the surface coat of J2s increased soybean resistance against SCN by triggering the expression of defence-associated genes. The disease-suppressive potential of these bacteria was validated by inoculating them into conducive soil. The Dyadobacter strain alone or in combination with Chitinophaga strains significantly decreased egg densities after one growing cycle of soybeans. In contrast, Chitinophaga strains alone required more than one growing cycle to significantly reduce SCN egg hatching and population density.ConclusionThis study revealed how soybean monoculture for decades induced microbiota homeostasis, leading to the formation of SCN-suppressive soil. The high relative abundance of antagonistic bacteria in the cyst suppressed the SCN population both directly and indirectly. Because uncontrolled proliferation will likely lead to quick demise due to host population collapse, obligate parasites like SCN may have evolved to modulate virulence/proliferation to balance these conflicting needs.BVs6NXuQzznnTv7j41Q5n6Video

Validated simulation of a long-term cropping experiment reveals a pathway for improved productivity

Long-term farming system experiments with comprehensive soil, plant and meteorological data combined with well-validated dynamic farming system models are a powerful combination to evaluate the production and environmental implications of novel innovations in agriculture. A current deficiency is the lack of adequate comprehensive validations for long term crop sequences that capture the dynamics of soil and crop responses without resetting soil conditions, especially for soil mineral nitrogen (Min-N). This reduces confidence in the outcome of scenario analyses for proposed improvements in productivity and sustainability given the central role played by nitrogen (N) dynamics in both processes. We used data from a 30-year long-term experiment (LTE) to validate the APSIM model and achieved excellent predictions for soil and crop responses including the dynamics of Min-N without resetting. A critical step was to ensure that the parameters required for the pools of soil organic matter matched those measured at the site over the full rooting depth (1.6 m) rather than limiting measured values to surface layers and relying on default parameters in deeper layers. In subsequent scenario analyses of agronomic innovations including fallow weed control, earlier sowing and improved N fertiliser strategies, the validated model predicted potential increases in average annual productivity of 1.2 t ha-1 (30%), WUE of 2.0 kg ha-1 mm-1 (30%) and NUE of 13 kg kg-1 (21%) and reductions in average annual N leaching of 8 kg N ha-1 (-33%) and soil organic matter loss of 3.1 t ha-1 (31%) (0–10 cm) could be achieved with specific combinations of synergistic innovations previously investigated separately in shorter-term experiments. Our study represents a rare case of model validation capturing the dynamics of soil water, Min-N, biomass and grain yield in a long-term diverse crop sequence to provide confidence in scenario analyses of production and environmental consequences of agronomic innovations. LTEs provide a valuable resource for such validation, while conclusions drawn from simulation studies that lack comprehensive validation must be considered with caution.

The impact of climate and potassium nutrition on crop yields: Insights from a 30-year Swiss long-term fertilization experiment

Climate change will strongly influence agricultural practices in the future. In order to promote resource-efficient agriculture, it is important to analyse the impact of climate variation on crop yields. In this study, we report yields of spring wheat, winter barley, maize, potato and sugar beet from the long-term crop rotation and fertilization experiment Demo in Switzerland and analyze their response to different climate variables (e.g., annual and seasonal temperature, precipitation, evapotranspiration, number of heat days and days of heavy rainfall). In addition, we investigate the impact of readily plant-available soil potassium (K) on the relationship of crop yields and precipitation. Annual and summer temperatures increased by 1 °C and 1.5 °C, respectively, over the observation period, and both the number of heat days and days of heavy rainfall increased in summer. Rising summer temperatures have a negative impact on all crop yields, which was most prominent for spring wheat, potato and maize. Annual, spring and summer precipitation show varying effects on different crops. For maize, soil K has a mediating effect on yield reductions under low spring precipitation. Yields are significantly reduced by 1 t ha−1 per 100 mm reduction of precipitation below a soil K threshold of 7 mg K kg−1 soil. Based on these results and the future climate scenarios for Switzerland, crop rotations with less heat-sensitive species and early-maturing varieties should be considered. In order to keep future irrigation demands and costs as low as possible, the soil K fertility classes in the Swiss K fertilization guidelines might need to be revisited. Our study is one of a few long-term observations that show the impact of climate variation on crop yields and highlights the potential of K management as a climate change adaptation measure.

EFFECTS OF TEA (CAMELLIA SINENSIS) CULTIVATION ON SOIL QUALITY IN THE LAM DONG, VIETNAM

The objectives of the study were to assess soil quality and its relationship to the sustainability of tea cultivation in the Lam Dong, Vietnam. Overall soil quality declined with increasing age of the tea plantations as evidenced by decreases in soil OC, total N, K and S, available P and K, mean weight diameter of aggregates. As well, total P, bulk density and mechanical resistance increased with increasing cultivation intensity. Because these soil properties were sensitive to cultivation effects, they were considered to be good indicators of soil quality. Soil properties that were less sensitive to change, and limited as soil quality indicators included texture, clay mineralogy and sesquioxides, and effective cation exchange capacity. Soil quality changes were greatest during the first 10 years of cultivation and were generally greatest in the surface 0- to 40-cm of soil. Soil and crop management factors were considered to be the most important factors affecting soil quality. Decreases in long-term crop yields were found to correspond with decreases in soil quality. In terms of crop productivity, the most important soil quality indicators (based on a multiple regression analysis) were OC, available P, total K and PAWC. Economic analysis of the yield and production cost data indicated that, under current conditions, tea cultivation in the Lam Dong province is sustainable for periods of about 20 years. Thus, measured values of soil quality indicators in the 20-yr tea soils were considered to represent the "critical levels" for economic sustainability of tea cultivation.

The Effect of Long-Term Crop Rotations for the Soil Carbon Sequestration Rate Potential and Cereal Yield

Depending on the type of agricultural use and applied crop rotation, soil organic carbon accumulation may depend, which can lead to less CO2 fixation in the global carbon cycle. Less is known about organic carbon emissions in different crop production systems (cereals, grasses) using different agrotechnologies. There is a lack of more detailed studies on the influence of carbon content in the soil on plant productivity, as well as the links between the physical properties of the soil and the absorption, viability, and emission of greenhouse gases (GHG) from mineral fertilizers. The aim of this study is to estimate the long-term effect of soil organic carbon sequestration potential in different crop rotations. The greatest potential for organic carbon sequestration is Norfolk-type crop rotation, where crops that reduce soil fertility are replaced by crops that increase soil fertility every year. Soil carbon sequestration potential was significantly higher (46.72%) compared with continuous black fallow and significantly higher from 27.70 to 14.19% compared with field with row crops and cereal crop rotations, respectively, intensive crop rotation saturated with intermediate crops. In terms of carbon sequestration, it is most effective to keep perennial grasses for one year while the soil is still full of undecomposed cereal straw from the previous crop. Black fallow without manure fertilization, compared to crop rotation, reduces the amount of organic carbon in the soil up to two times, the carbon management index by 2–5 times, and poses the greatest risk to the potential of carbon sequestration in agriculture.

Influence of Decomposed Stubble Return on the Soil Microbial Community Under Perennial Crop Rotation

The aim of this study was to understand how the application of decomposed stubble return (DSR), a type of bio-organic fertilization, affects soil microbial communities under crop rotation. The changes in microbial composition and diversity related to DSR were investigated based on metagenomic sequencing and comparative analysis of two groups of soil samples after a 3-year tomato-pepper-papaya rotation: the DSR and no-DSR (i.e., without DSR) groups, with the soils before crop rotation as the control group. Inter-group comparisons of the crop performance (growth and yield) and physicochemical soil properties (pH value, nutrient elements, and heavy metals) were also conducted to reveal the effects of DSR application on the soil. The relative abundance of bacteria was higher than 90% in all soil samples. Proteobacteria and Actinobacteria in the DSR group and Proteobacteria and Firmicutes in the no-DSR group, whereas Acidobacteria and Proteobacteria in the control, were the two most abundant phyla. The abundance of Proteobacteria decreased, whereas that of Actinobacteria increased, in the DSR-amended soil compared to the no-DSR soil. At genus level, Acidobacterium dominated in the control and genera Pseudomonas, Burkholderia, and Bacillus in the no-DSR group, while Burkholderia, Pseudomonas, and Bacillus in the DSR-amended soil comprised the majority of their microbiomes. The DSR soil had higher microbial diversity and relative abundance of Ascomycota fungi than the no-DSR group after the crop rotation. Along with higher diversity of microbial community, more favorable soil pH, better crop growth, higher crop yields, higher abundance of soil nutrient elements, and lower accumulation of heavy metals in the soil were found in the DSR group compared to the no-DSR one. Furthermore, the DSR soil had more similarities with the control than with the No-DSR soil, in aspects of microbial composition and microbe-derived potential gene functions. It was indicated that decomposed stubble return may improve soil conditions or prevent them from degradation incurred by long-term crop cultivation. It was suggested that the application of the compost derived from fermented post-harvest plant residue may be a general strategy for developing more sustainable agricultural systems.

Cover Crop and Crop Rotation Effects on Tissue and Soil Population Dynamics of Macrophomina phaseolina and Yield Under No-Till System.

The effects of crop rotation and winter cover crops on soybean yield and colony-forming (CFU) units of Macrophomina phaseolina, the causal agent of charcoal rot (CR), are poorly understood. A field trial was conducted from 2011 to 2015 to evaluate (i) the impact of crop rotation consisting of soybean (Glycine max [L.] Merr.) following cotton (Gossypium hirsutum L.), soybean following corn (Zea mays L.), and soybean following soybean over a 2-year rotation and its interaction with cover crop and (ii) the impact of different cover crops on a continuous soybean crop over a 5-year period. This trial was conducted in a field with 10 subsequent years of cover crop and rotation treatments. Cover crops consisted of winter wheat (Triticum aestivum L.) and Austrian winter pea (Pisum sativum L. subsp. sativum var. arvense), hairy vetch (Vicia villosa Roth), and a fallow treatment was evaluated with and without poultry litter application (bio-cover). Tissue CFU of M. phaseolina varied significantly between crop rotation treatments: plots where soybean was grown following cotton had significantly greater tissue CFU than plots following soybean. Poultry litter and hairy vetch cover cropping caused increased tissue CFU, though this effect differed by year and crop rotation treatment. Soil CFU in 2015 was substantially lower compared with 2011. However, under some crop rotation sequences, plots in the fallow treatment had significantly greater soil CFU than plots where hairy vetch and wheat was grown as a cover crop. Yield was greater in 2015 compared with 2011. There was a significant interaction of the previous crop in the rotation with year, and greater yield was observed in plots planted following cotton in the rotation in 2015 but not in 2011. The result from the continuous soybean planted over 5 years showed that there were no significant overall effects of any of the cover crop treatments nor was there interaction between cover crop treatment and year on yield. The lack of significant interaction between crop rotation and cover crop and the absence of significant differences between cover crop treatments in continuous soybean planting suggest that cover crop recommendations for midsouthern soybean growers may need to be independent of crop rotation and be based on long-term crop needs.

Fungal Communities Associated with Corn in a Diverse Long-Term Crop Rotation in Ohio

Crop rotation is a cultural practice in disease management used to break the disease cycle, resulting in a reduction of inoculum. In Ohio, crop rotations have been reduced in diversity, with many farmers shifting to corn-soy rotations from more diverse rotations featuring wheat. We investigated the impact of this shift on soil fungal communities under corn by conducting synthetic long-read amplicon sequencing. DNA was extracted from soil sampled during the corn-growing season at two locations in Ohio with replicated long-term rotation plots in a corn–soybean (CS) and corn–soybean–winter wheat (CSW) rotation in 2018, 2019, and 2020. 18s-ITS amplicons were sequenced using Illumina paired with Loopgenomics technology. PERMANOVA analysis revealed that fungal communities were significantly impacted by location, rotation, and time. Shannon and Simpson diversity indices implied fungal species diversity was significantly higher in the CS rotation. Indicator species analysis revealed 20 species indicative of the CSW rotation, including Mortierella, Hymenoschyphus, Ascobolus, and Saitozyma species, and 36 species indicative of the CS rotation, including Fusarium, Neoaschocyta, Zalerion, and Trichoderma species, among others. Indicator species amplicon sequencing variant reads for the CSW rotation were not correlated with the decline in corn yield or soil nitrogen, carbon, or active carbon. However, they were positively correlated with soil organic matter. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY 4.0 International license .

Application of superabsorbent natural polymers in agriculture

To meet global food demand, reduce waste, and minimise environmental impact, the agricultural sector must improve its current practices on soil amendment, fertiliser encapsulation, and seed and crop protection. Super absorbent polymers (SAPs) are a class of polymeric materials that can absorb and retain large quantities of liquids/aqueous solutions compared to their own mass. Typically, SAPs are cross-linked to form three-dimensional hydrophilic networks, commonly known as hydrogels. Although SAPs can be synthesised from both synthetic and naturally sourced materials, for agricultural applications they are generally composed of synthetic polymers, due to their advantageous properties. These include higher water absorption rate and capacity, low cost, availability, durability, and mechanical performance. However, many of these systems utilise polyacrylic acid (PAA) and polyacrylamide (PAM) monomers which may have toxic effects on the nervous and respiratory systems of humans and animals. To ensure sustainable agricultural practices and maintain healthy long-term crop output, synthetic SAP usage must be greatly reduced. This review article aims to investigate alternative natural SAPs for agriculture and critically rationalise their adoption into the industry. Specific applications investigated include (i) soil amendment, (ii) fertiliser encapsulation, (iii) seed coating, and (iv) crop protection.

Effects of long-term monocropping, rotation cropping, and fertilization on energy and fuel requirements for fall moldboard plowing in a clay-loam soil

With recent increases in energy costs, information on energy inputs is becoming a more important aspect in management decisions on selection of crop production systems. The effects of long-term (45–55 years) monocropping, rotation cropping, and fertilization on tillage energy (implement draft and tractor fuel consumption) were determined for a Brookston clay-loam soil in southwestern Ontario, Canada. Treatments included fertilized and unfertilized monocrop (continuous) corn (Zea mays L.), and a four year fertilized and unfertilized corn – oat (Avena sativa L.) – alfalfa (Medicago sativa L.) – alfalfa rotation with all phases of the rotation present in each year. The corn and second year alfalfa plots were moldboard plowed each fall after crop harvest, and then spring-tilled (disc, harrow) prior to planting; oat and first year alfalfa plots were not fall plowed or spring-tilled. Moldboard plow draft and tractor fuel consumption were measured annually from 2004 to 2014 using an instrumented tractor and the same plow and settings.Monocrop unfertilized corn consistently exhibited the greatest plow draft and tractor fuel consumption. Draft averaged over ten years was 13.0% higher for unfertilized than fertilized rotation corn, and 15.5% higher for fertilized than unfertilized second year alfalfa; fuel consumption was 10.4% higher for unfertilized than fertilized rotation corn and 5.1% higher for fertilized than unfertilized second year alfalfa. These differences were attributed to treatment-induced changes in soil strength. Both plow draft and fuel consumption were lower in rotation corn relative to monocrop corn, while plow draft was greater in fertilized alfalfa relative to unfertilized alfalfa due to greater root growth. This study demonstrated that long-term cropping systems can have substantial impacts on the energy required for tilling a clay loam soil.

Evaluation of data assimilation strategies on improving the performance of crop modeling based on a novel evapotranspiration assimilation framework

Recently, data assimilation (DA) has garnered significant attention. Integration of DA approaches and crop models could diminish model uncertainties and improve the precision of model simulations. While previous research extensively focused on assimilating leaf area index (LAI) or soil moisture (SM), the feasibility and effectiveness of assimilating evapotranspiration (ET) have been rarely explored. In this study, we proposed a novel framework of ET assimilation. Then, together with commonly assimilated LAI and SM, we evaluated the performance of this new method in simulating the key indicators (i.e., LAI and ET in daily and interannual scales, and the crop yield) based on the long-term eddy covariance observations and well-calibrated crop model. DA strategies we utilized to evaluate consist of two approaches (i.e., Ensemble Kalman filter (EnKF) and EnKF with simultaneous state-parameter estimation (EnKF-SSPE)) and combinations of three assimilated observations (i.e., LAI, SM, and ET).Our results demonstrate that joint assimilation of LAI and ET with EnKF-SSPE performs best for wheat while joint assimilation of SM and ET with EnKF-SSPE is the best for maize. For a single observation, LAI and ET play a dominant role in DA for wheat and maize, respectively. This is because the interannual variability of wheat growth is primarily influenced by agricultural management (e.g., cultivar change) and can be represented by LAI. For maize which is mostly rainfed, water stress usually occurs. Therefore, ET, with its ability to reflect the water stress status, proves to be effective. EnKF-SSPE outperforms EnKF, exhibiting potential in revealing the parameter evolution during long-term crop modeling, especially when crop cultivars are regularly renewed. This study evaluates different observations and methods through DA based on a newly proposed sequential ET assimilation framework, which might be illuminating for future applications of DA.

Parametric seasonal-trend autoregressive neural network for long-term crop price forecasting.

Crop price forecasting is difficult in that supply is not as elastic as demand, therefore, supply and demand should be stabilized through long-term forecasting and pre-response to the price. In this study, we propose a Parametric Seasonal-Trend Autoregressive Neural Network (PaSTANet), which is a hybrid model that includes both a multi-kernel residual convolution neural network model and a Gaussian seasonality-trend model. To compare the performance of the PaSTANet, we used daily data from the Garak market for four crops: onion, radish, Chinese cabbage, and green onion, and performed long-term price forecasts for one year in 2023. The PaSTANet shows good performance on all four crops compared to other conventional statistical and deep learning-based models. In particular, for onion, the (mean absolute error (MAE) for the long-term forecast of 2023 is 107, outperforming the second-best Prophet (152) by 29.6%. Chinese cabbage, radish, and green onion all outperform the existing models with MAE of 2008, 3703, and 557, respectively. Moreover, using the confidence interval, the predicted price was categorized into three intervals: probability, caution, and warning. Comparing the percentage of classified intervals about the true prices in our test set, we found that they accurately detect the large price volatility.

Intelligent crop yield prediction system using neural networks and databases

Machine learning plays an important role in decision support and yield forecasting. This is an effective tool for determining strategies during the growing season of plants. The article proposes a method for predicting yield using a complex system consisting of a convolutional neural network (CNN), a feedforward neural network (FNN), and a SQLiteStudio database. The system includes several stages of data processing, starting with the collection and analysis of images and digital data obtained from various sources, and ending with yield forecasting based on this data. A convolutional neural network (CNN) is used to analyze images and video streams to recognize and count fruits on trees, providing accurate data about the status of the crop. Feedforward neural network (FNN) is used to analyze digital data, such as weather station data and long-term crop yield data, to subsequently predict crop yields. The received data is stored in a relational database, which ensures their structured storage and access for subsequent processing. Used SQL language to perform various database operations. To automate the process of counting fruits on trees, the YOLOv8 convolutional neural network model is used, which allows recognizing objects in real time. A Python script has been developed to process images using YOLOv8 and save the results to a database. An integrated system combines various methods and technologies to predict yields and automate data collection and analysis processes. The developed model showed a mean square error (MSE) of 7.33 and a mean absolute percentage error (MAPE) of 6.27%.