Crop Nutrient Requirements Research Articles

Development of Integrated Fertilizer Prescription Based on STCR- IPNS for Cotton through Inductive Cum Targeted Yield Model in Thirunallar Soil Series of Karaikal, Puducherry, India

The Soil Test Crop Response (STCR) approach within the Integrated Plant Nutrient System (IPNS) is a targeted yield-based strategy that balances immediate crop nutrient needs with long-term soil health, aiming to optimize yield, fertilizer efficiency, and sustainability. Field trials on Typic Haplusterts soils in Karaikal used an inductive cum targeted yield model to develop fertilizer prescription equations (FPE) based on the nutrient requirement (NR) of crops and the contributions from soil (Cs), fertilizers (Cf), and farmyard manure (Cfym). For cotton, desired yield targets of 31, 33, and 35 q ha⁻¹ were set, and nomograms were created to determine precise fertilizer applications based on soil test values. When FYM was applied at 12.5 t ha⁻¹, it contributed 52 kg of nitrogen (N), 30 kg of phosphorus (P2O5), and 48 kg of potassium (K2O), which complemented the calculated NPK fertilizer needs. These values allowed for precise adjustments of nutrient inputs, aligning with both crop demands and the soil’s nutrient-supplying capacity, and improving efficiency while maintaining soil health. This approach provides a practical framework for farmers, enhancing yields and profitability while promoting the sustainable use of resources by balancing "fertilizing the crop" with "fertilizing the soil."

Site Specific Nutrient Management (SSNM): Principles, Key Features and its Potential Role in Soil, Crop Ecosystem and Climate Resilience Farming

As the world population expands, farming practices have intensified to meet increased food demand. Modern crop varieties now require higher levels of fertilization compared to traditional organic methods, which are insufficient to meet these new demands. However, inefficient nutrient management and imbalances in field nutrient levels have led to various crop issues. To achieve higher agricultural output and productivity, there has been a notable increase in the application of chemical fertilizers, which unfortunately contributes to soil and water pollution, degradation of soil fertility, and nutrient imbalances. In response, modern technologies are being leveraged to promote sustainable food production and foster balanced agricultural development. Site specific nutrient management (SSNM) aims to empower farmers to adjust fertilizer application dynamically to meet the nutrient requirements of high-yielding crops, bridging the gap between natural nutrient sources like soil, crop residues, manure, and irrigation water. It is based on the principles of 4Rs: right product, right dose, right time and right place. Modern technologies like Optical sensors, Crop Manager, Remote Sensing, Nutrient Expert®, fertility mapping, Active Canopy Sensors, Variable rate technologies etc. are used to enhance the potential of SSNM to higher level. The focus is on optimizing nutrient application timing and rates to maximize crop yield and nutrient efficiency, thereby enhancing the economic value of harvest per unit of fertilizer used, rather than simply increasing or decreasing fertilizer use.

Numerical Data Based Fertilizer Recommendation System for Farmer

In modern agriculture, optimizing fertilizer use is crucial for maximizing crop yields, maintaining soil health, and reducing environmental impact. The Numerical Data-Based Fertilizer Recommendation System (NDFRS) for farmers addresses these needs by leveraging data-driven approaches to provide precise fertilizer recommendations tailored to specific crop and soil conditions. This system integrates soil nutrient analysis, crop nutrient requirements, and environmental factors to generate customized fertilizer plans. The NDFRS employs advanced machine learning algorithms to analyze extensive datasets, including soil test results, historical crop yield data, weather patterns, and geographical information. By incorporating these variables, the system can predict the optimal type and amount of fertilizers required for different crops at various growth stages. This ensures that nutrients are supplied efficiently, enhancing crop productivity while minimizing excess fertilizer use and associated environmental risks. The user- friendly interface of the NDFRS allows farmers to input relevant data easily and receive actionable recommendations. Additionally, the system offers real-time updates and adaptive recommendations based on changing environmental conditions and crop growth stages. Field trials and validation studies demonstrate the system's efficacy in improving crop yields and promoting sustainable farming practices. Keywords: Tensor Flow, Deep Learning.

A nutrient optimization method for hydroponic lettuce based on multi-strategy improved grey wolf optimizer algorithm

Hydroponic agriculture, as a modern agricultural technology, not only enables crops to better realize their growth potential but also frees them from the traditional agricultural constraints of land resources. Currently, the nutrient solutions for hydroponic crops are mostly prepared using generic formulas, lacking precise ratios based on the specific needs of different crop types and growth stages. It is of great significance to study the precise nutrient requirements of specific crops at different growth stages to enhance yield. To this end, a multi-strategy improved Grey Wolf Optimization algorithm is proposed in this paper to optimize the fertilizer model for hydroponic lettuce at different growth stages, providing more accurate nutrient requirements for hydroponic lettuce at different growth stages. Firstly, to solve the problems of the traditional GWO algorithm, such as insufficient exploration and the tendency to fall into local optima, non-linear functions, Symbiotic Organisms Search (SOS), and Opposition-Based Learning (OBL) were integrated into the GWO algorithm. Secondly, the objective was to minimize the residual function of the nitrogen, potassium, and calcium ternary fertilizer effect equation, the proposed algorithm was used to optimize the coefficients of the equation. Lastly, the optimal concentrations of NO3−, K+, and Ca2+ for each growth stage of lettuce were calculated based on the optimized fertilizer effect equations. The proposed algorithm was compared with five other excellent metaheuristic algorithms in optimizing fertilizer model coefficients. Experimental results indicate that the proposed algorithm outperforms the other algorithms used in the experiments. For the nutrient models of three growth stages, the proposed algorithm achieves improvements compared to the GWO algorithm, with R2 increasing by 0.73 %, 0.66 %, and 0.51 %, and RMSE decreasing by 8.53 %, 5.70 %, and 3.83 % respectively. This contributes to providing more accurate nutrient requirements for hydroponic lettuce.

Soil Test Crop Response on Soil Health Parameters and Yield Attributes of Okra (Abelmoschus esculentus L.) var. Kuber

The investigation was conducted on Soil Test Crop Response (STCR) based Integrated Plant Nutrient System (IPNS) technology, where the fertilizer doses are customized according to the anticipated crop yield, considering the crop's nutrient requirements and the contributions from soil, fertilizers, and organic manures. The field trial took place at the Soil Science research farm of Sam Higginbottom University of Agriculture, Technology and Sciences, Prayagraj, during the zaid season of 2023. The soil under experimentation had a sandy loam texture. The setup followed a randomized block design with varying levels of NPK (0%, 50%, & 100%), FYM (20, 25, & 30 t ha-1), Fe and Zn (15, 20, & 25 kg ha-1) respectively. The outcomes from the T9 treatment - [115:112:75 Kg ha-1 + 25 t ha-1 FYM + 25 kg ha-1 Fe and Zn] exhibited superior plant height, number of branches plant-1, number of leaves plants-1, number of fruits plant-1, and overall fruit yield. No significant differences were noted in the yield and growth of okra under the control conditions. The application of organic manures alone or in combination with full NPK substantially enhanced the growth and total yield parameters of okra. Among all treatments, the simultaneous application of 100% NPK, 100% FYM, and 100% Fe & Zn displayed the most remarkable influence on the growth of okra.

Mitigating water pollution by nitrogen fertilizers through amending ammonium sorption in an acid soil using Calciprill and sodium silicate

Use of nitrogen (N) fertilizers is gaining popularity to meet crop nutrient requirement for sustaining the food security of the increasing global population. However, improper management of N fertilizers in acid soils causes leaching and surface runoff because of excessive rainfalls and poor N retention in the tropics in particular. This results in N pollution in water bodies (also known as eutrophication), which degrades water quality to the detriment of aquatic ecosystems near farms. Thus, there is a need for using inorganic soil amendments such as Calciprill and sodium silicate to improve soil N adsorption because of the alkalinity and ability of these amendments to retain N for mitigating excessive N contamination in water bodies. To this end, this N sorption study was conducted to determine the effects of Calciprill and sodium silicate on ammonium (NH4+) adsorption and desorption in an acid soil (Bekenu series, Typic Paleudults). The soil was co-applied with different rates of Calciprill (80 %, 90 %, and 100 % Ca saturations) and sodium silicate (90, 105, 120, 135, and 150 kg ha−1), followed by the NH4+ adsorption capacity determination through the additions of NH4+ isonormal solutions at the five concentrations (0, 25, 50, 75, and 100 mg L−1) to establish a linear relationship between the amount of NH4+ absorbed (qe) and the amount of NH4+ left in the solution (Ce) after 24 h of equilibration. Apart from the soil only without any amendment (C0S0), there were another two additional treatments where the soil was added with Calciprill (100 % Ca saturation) (C3) and sodium silicate only (150 kg ha−1) (S5) to determine their respectively effects on N sorption. The collected data were fitted to the Langmuir and Freundlich isotherms. Thereafter, NH4+ desorption was determined using the same soil samples added with 2 mol dm−3. Compared with the soil without any amendment (C0S0), the Calcirpill alone (C3) and the combined use of Calciprill and sodium silicate significantly increased NH4+ adsorption at the NH4+ addition of 250 mg L̶1, suggesting that Calciprill is the amendment which dominantly increases NH4+ adsorption and the effects of amendments are more pronounced at the lower soil NH4+ concentration. The results also revealed that the NH4+ adsorption in the soils following the co-application of Calciprill and sodium silicate followed the assumption of Freundlich isotherm. Regardless of the NH4+ concentration used, the effects of Calciprill and sodium silicate on the NH4+ desorption remain unclear, which could be because of the ability of sodium silicate to stabilize the soil structure. This stabilization reaction might have impeded the dissolution of Calciprill and temporarily fixed the absorbed NH4+. These findings suggest that it is possible to use the amendments to amend NH4+ sorption in Bekenu series for mitigating NH4+ leaching and runoff to prevent eutrophication.

An Evaluation of Potato Fertilization and the Potential of Farmers to Reduce the Amount of Fertilizer Used Based on Yield and Nutrient Requirements

Unreasonable fertilization often fails to match crop yield and nutrient requirements, leading to low crop yield, the waste of mineral resources, and increased costs for farmers. A survey of the potato yield and fertilization of farmers was conducted in Haidong City of Qinghai Province for three consecutive years (2017–2019) torecommend reasonable fertilizer application. The results showed that the required amount of NPK fertilizer per ton of potato was 4.85 kg N, 1.26 kg P2O5, and 6.98 kg K2O, respectively. The potato yields ranged from 7500 to 66,429 kg ha−1, with an average of 26,069 kg ha−1. The average N, P, and Kfertilizers (in the form of N, P2O5, and K2O, respectively) applied by the farmers were 213 kg N ha−1, 202 kg P2O5ha−1, and 43 kg K2O ha−1. More than 60% of the farmers appliedtoo much Nand Pfertilizers and too little Kfertilizer. Therefore, the farmers with lowyieldsshould reduce the application of Nand P fertilizers by a range of 41–220 kg ha−1 and 24–265 kg ha−1. Allthe farmers should increase Kfertilizer use by 7–273 kg ha−1. Reasonable fertilization could effectively conserve resources, improve economic efficiency, and reduce environmental impact.

The Deep Learning-Crop Platform (DL-CRoP): For Species-Level Identification and Nutrient Status of Agricultural Crops.

Precise and timely detection of a crop's nutrient requirement will play a crucial role in assuring optimum plant growth and crop yield. The present study introduces a reliable deep learning platform called "Deep Learning-Crop Platform" (DL-CRoP) for the identification of some commercially grown plants and their nutrient requirements using leaf, stem, and root images using a convolutional neural network (CNN). It extracts intrinsic feature patterns through hierarchical mapping and provides remarkable outcomes in identification tasks. The DL-CRoP platform is trained on the plant image dataset, namely, Jammu University-Botany Image Database (JU-BID), available at https://github.com/urfanbutt. The findings demonstrate implementation of DL-CRoP-cases A (uses shoot images) and B (uses leaf images) for species identification for Solanum lycopersicum (tomato), Vigna radiata (Vigna), and Zea mays (maize), and cases C (uses leaf images) and D (uses root images) for diagnosis of nitrogen deficiency in maize. The platform achieved a higher rate of accuracy at 80-20, 70-30, and 60-40 splits for all the case studies, compared with established algorithms such as random forest, K-nearest neighbor, support vector machine, AdaBoost, and naïve Bayes. It provides a higher accuracy rate in classification parameters like recall, precision, and F1 score for cases A (90.45%), B (100%), and C (93.21), while a medium-level accuracy of 68.54% for case D. To further improve the accuracy of the platform in case study C, the CNN was modified including a multi-head attention (MHA) block. It resulted in the enhancement of the accuracy of classifying the nitrogen deficiency above 95%. The platform could play an important role in evaluating the health status of crop plants along with a role in precise identification of species. It may be used as a better module for precision crop cultivation under limited nutrient conditions.

Shaping the succession patterns of different soil nutrients, enzyme stoichiometry, and microbial communities through rotation systems

The ecological environment and function of farmland soil are strongly affected by crops. However, there is still a lack of understanding of how the soil microbial environment responds to crop changes in rotation systems. Therefore, we studied wheat–maize (W–M) and garlic–maize (G–M) crop rotation systems to explore the responses in terms of soil nutrients and the microbial community to different tillage systems. The results showed that the W–M cropping system was continuously limited by phosphorus nutrition, and the G–M cropping system was alternately affected by nitrogen and phosphorus nutrition due to the different nutrient requirements of crops. The bacterial communities were significantly affected by the cropping systems and crop types, whereas the fungal communities were only affected by the crop types. Compared with W–M, G–M increased the abundances of Nitrospirae, Bacteroidetes, and Rokubacteria in the bacterial community, and decreased the abundance of Basidiomycota in the fungal community, as well as increasing the nodes and links between bacterial communities but weakening the links between fungal communities. Compared with W-M, G-M decreases the contents of soil organic carbon and total nitrogen, increases the diversity and abundance of bacteria, and decreases the diversity of fungi, thereby reducing extracellular enzyme C/N and N/P, and increasing the activity ratio of C/P, ultimately reduces C and P limitations and increases N limitations. Differences in crop types result in greater changes in soil bacteria than fungi in crop rotation systems. Our study provides more insights into the relationship between soil nutrient limitation and microenvironment in rotation systems.

Optimizing polyhalite (POLY-4) use in the maize-wheat system: A comparative case study from upper and Trans Indo-Gangetic plains of India

Increasing complexity in crop nutrient requirement in intensive crop production systems needs alternate multi-nutrient sources. Polyhalite (POLY-4) which contains 14% K2O along withcalcium (17% CaO), magnesium (6% MgO), and sulfur (19% S) can be a possible recourse in this regard. In maize-wheat systems, it was evaluated for productivity, profitability, nutrient usage, and nutrient use efficiency under Indo-Gangetic plain (IGP) zones for consecutive two years (2018-19 and 2019-20). The results revealed that 150% K through POLY-4 produced the maximum maize grain yield under the Trans Indo-Gangetic plains (TGP). The maize grain yield increased by 20.8% and 26.2% under 100% K (POLY-4) and 150% K (POLY-4) over No–K, respectively. But statistically, 100% K (POLY-4) stands similar with both 150% K (POLY-4) and 150% K through muriate of potash (MOP) and equivalent. The trends were noticed under upper Indo-Gangetic plain zones (UGP) also. Similarly, the maximum wheat grain yield (6.12 and 6.29 t/ha under TGP and UGP, respectively) was obtained under 150% K (POLY-4), and remained statistically at par with 100% K (POLY-4), but significantly higher than 150% K (MOP). Under both agro-ecologies i.e. TGP and UGP, the highest system productivity was obtained with recommended N, P, and 150% K application through POLY-4. The added return over NPK remained highest with 150% K (POLY-4) for both maize and wheat. However, higher partial factor productivity for N and S, agronomic, physiological, and translocation efficiencies were noticed under 150% K (POLY-4), and remained at par with 100% K (POLY-4). Increased system yield, added returns, partial factor productivity, agronomic, physiological, and translocation efficiencies under 100% K through POLY-4 (along with recommended N and P) proved its effectiveness as multi-nutrient source for the maize-wheat system under TGP and UGP.

Impact of Irrigation and Fertigation Levels on Growth, Yield Components and Yield of Aerobic Rice (Oryza sativa L.) under Drip System

Back ground: More than half of the world’s population depends on rice, which is grown in transplanting conditions. Due to the global water crisis, irrigated rice systems are no longer sustainable. Therefore, cultivating aerobic rice with drip irrigation and fertigation meets the crop water and nutrient requirements, results in the optimal yield. Method: A field experiment was conducted during summer 2022 and 2023 at Research Farm of Wetland in Tamil Nadu Agricultural University, Coimbatore, to evaluate the performance of aerobic rice under drip irrigation and fertigation levels on growth and yield of Co-51 variety. The experiment was laid out in randomized complete block design with combination of thirteen treatments, replicated thrice. Results: Among different treatments, drip fertigation @ 100% PE up to 30 DAS+150% PE up to 60 DAS+ 200% PE up to 90 DAS with 125% RDF (25% through NF+75% through WSF) resulted significantly superior growth characters viz., higher plant height (92.54 and 95.95 cm), no. of tiller m-2(469.78 and 478.42), total drymatter production m-2 (988.21 and 1025.42 g m-2), no. of filled grains panicle-1 (107.5 and 114.5), total no. of grains panicle-1 (122.6 and 127.1), fertility percentage (87.7% and 90.1%) and lower no. of ill filled grains panicle-1 (15.1 and 12.6), grain yield (4316 and 4446 kg ha-1) and straw yield (5528 and 5775 kg ha-1) as compared to others, during summer 2022 and 2023, respectively.

Layered-Strip Fertilization Improves Nitrogen Use Efficiency by Enhancing Absorption and Suppressing Loss of Urea Nitrogen

Appropriate deep application of fertilizer is the key basis for improving nitrogen use efficiency (NUE). However, the effects of different deep application methods and fertilizer types on nutrient migration, NUE and biomass in wheat season are unclear. Therefore, in this study, a barrel planting test with multilayer fertilization (15N labeled urea (U) and coated urea (CU)) was conducted in a long-term positioning trial of winter wheat in the North China Plain (NCP). We quantified the migration of fertilizer N (Ndff) in soil–plant–atmosphere and its effects on wheat biomass and NUE based on surface (Usur, CUsur), layered-strip (Ustr, CUstr) and layered-mix fertilization (Umix, CUmix) of U and CU. Compared with surface fertilization, the concentration of mineral N in root zone (0–40 cm) was increased by Ustr and Umix (8.6–50.3%), and the concentration of ammonium N was decreased by CUstr and CUmix (49.6–76.0%), but there was no change in the nitrate N. The biomass and total N absorption of wheat tissues (straw and root) were increased by 12.3–38.9% under Ustr and CUstr. Meanwhile, the distribution of Ndff in the 0–10 cm soil was decreased under Ustr and CUstr, but it was increased in the 10–30 cm soil, thereby promoting the absorption of Ndff in wheat tissues by 12.3–28.7%. The rates of absorption and loss of Ndff were the highest (57.6–58.5%) and the lowest (4.5%) under Ustr and CUstr, respectively, compared with other treatments. Consequently, layered-strip fertilization optimized the migration and utilization of Ndff within the soil–plant–atmosphere system. This approach equalized distribution, enhanced absorption and minimized losses of Ndff, resulting in an increase in NUE by 9.6–16.7%. Under the same treatment, CU was more suitable for crop nutrient requirements than U, which was more conducive to the improvement of NUE. Our findings will provide a scientific basis for the precise directional fertilization of winter wheat in the NCP.

Perceptions and attitudes of farmers and landowners on soil salinity management and use of elemental sulphur in Oman

AbstractSoil salinity threatens agricultural sustainability globally and is a significant challenge in Oman. Previous studies in Oman focused on examining the causality and spatiotemporal variation of groundwater and soil salinity, neglecting farmers' perceptions and attitudes towards salinity management. Therefore, this study evaluates (i) perceptions and attitudes of landowners and farmers towards soil salinity and its management, and (ii) determinants of willingness to use elemental sulphur to alleviate soil salinity in Oman. A questionnaire survey (122 responses) assessed perceptions, attitudes and knowledge using Likert scales and qualitative questions. Binary Logistic Regression analysed determinants of willingness to use elemental sulphur. Results reveal variations in perceptions, attitudes, knowledge and management practices. Most of the respondents were aware of adequate nutrient and water requirements for crops (p < .05). Respondents rely on social media (38.5%), fellow farmers (32.1%) and personal experiences (11.5%) for knowledge acquisition about soil salinity management. Half of the respondents did not monitor soil salinity, while the other half relied primarily on visual observation. A substantial number (62.6%) of the respondents did not implement any techniques to alleviate soil salinity, while among those who acted, a majority preferred cultivating date palms (55%) or fodders (29.4%). Awareness of the national salinity management strategy and commercial products is lacking. However, when introduced to elemental sulphur as a soil amendment for salinity, 74.8% of the respondents demonstrated a willingness to utilize it. Most (82.4%) preferred elemental sulphur products within the lowest price range. Being a full‐time farmer, owning a farm, awareness of the national strategy and low‐price preferences were positive determinants, while <1 year of farming experience was a negative determinant of willingness to use elemental sulphur. These findings inform future research on socio‐economic perceptions of salinity in Oman, the Gulf region and similar arid areas facing food production limitations.

Nanofertilizers as an alternative to inorganic fertilizers: A review

The population of the world is steadily increasing, in contrast to the natural resources which are limited and subjected to further depletion. This induces pressures to develop effective agricultural production systems to meet the growing demands on food and, thus, to mitigate hunger and poverty worldwide. Generally, inorganic fertilizers play a crucial role in maintaining soil fertility and improving crop yield and quality. Inorganic chemical fertilizers are regarded as the main source to supply crops with their needs of nutrients. Proper nutrient management of crops is a major challenge worldwide as it relies predominantly on chemical fertilizers. However, inorganic fertilizers are not only costly but may be harmful and pose risks to human health and have negative impacts on the environment. About half of the amount of applied fertilizers is used by the crop, whereas the remaining fertilizers are lost through leaching and gaseous emissions. The lost nutrients contribute to environmental pollution, global warming and climate change. Moreover, high application rates of chemical fertilizers can deteriorate soil fertility and raise soil salinity and thus lower crop production and quality will occur. This creates a need to invent smart fertilizers that are friendly to the environment, particularly those of high nutrient use efficiency and low leaching potential. Nanotechnology has a vital role in the construction of such fertilizers (nanofertlizers). In these fertilizers, nutrients are bound to nano-dimensional adsorbents (nanomaterials), which release nutrients very slowly as compared to conventional chemical fertilizers. Nanofertilizers are nutrients coated or encapsulated with different types of nanomaterials. They have unique properties like large surface area, slow-release profile, and controlled delivery of nutrients to the targeted sites to meet the nutrient requirements of crops. Nanofertilizers are emerging as a promising alternative to conventional chemical fertilizers, as they offer great opportunities to improve plant nutrition under harsh environments. The benefits associated with the use of nanofertlizers are opening new approaches toward the development of sustainable agriculture. However, further studies are needed for a sound and safe application of nanofertlizers. In this review, researchers’ attempts to produce and use nanofertlizers for sustainable crop production have been presented. The advantages and limitations of the application of these smart fertilizers have also been discussed. Key words: Nanoparticles, Sustainable agriculture, Phytotoxicity, Slow and controlled release, Metal oxides

Effect of Different Levels of Controlled Release Fertilizers on Growth, Yield and Quality of Red Okra (Abelmoschus esculentus) Var Kashi Lalima under Prayagraj Agro-climatic Condition

About 40-70% of conventional fertilizer is wasted due to leaching causing environmental issues. Controlled release fertilizers provide a promising solution as they gradually release nutrients to match the crop's nutrient requirements, improving nutrient uptake efficiency and reducing nutrient losses. The Experiment was carried out During March To June 2021-22, using a randomized block design with three replications and eight treatments, including a control using the recommended dose of fertilizer (RDF). The statistical analysis of the variance showed that the use of CRF had a significant effect on the growth, yield, and quality of red okra. Among the different levels of CRF used, treatment T7 (11g CRF/plant) performed the best in terms of growth parameters such as plant height and number of leaves. Treatment T2 (7g CRF/plant) was found to perform the best in terms of earliness parameters. Treatment T5 (9g CRF/plant) had the highest yield with 14.30 t/ha. Treatment T6 (10g CRF/plant) was found to be the best for quality parameters. The highest benefit-cost ratio was recorded in treatment T5 (9g CRF/plant) which is 4.7. From the present investigation, it is concluded that, CRF can be used efficiently for higher crop production.

Effects of organic fertilizers on yield, soil physico-chemical property, soil microbial community diversity and structure of Brassica rapa var. Chinensis.

The amount of chemical fertilizer for vegetables is on the high level in China. The use of organic fertilizers to meet the nutrient requirement of crops will be an inevitable practice in sustainable agriculture. In this study, we compared the effects of pig manure fertilizer, rabbit manure fertilizer and chemical fertilizer on yield, quality of Brassica rapa var. Chinensis, soil physico-chemical properties and microbial community by using two consecutive seasons of three fertilizers in a pot experiment. The results were as follows: (1) In the first season, the fresh yield of Brassica rapa var. Chinensis applying chemical fertilizer was significantly (p ≤ 5%) higher than those of applying the pig manure and rabbit manure fertilizer, and the results were the opposite in the second season. The total soluble sugar concentration of fresh Brassica rapa var. Chinensis applying rabbit manure fertilizer was significantly (p ≤ 5%) higher than those of applying pig manure fertilizer and chemical fertilizer in the first season, and the NO3-N content of fresh Brassica rapa var. Chinensis on the contrary. (2) The organic fertilizer increased the concentration of total nitrogen, total phosphorus and organic carbon in soil in both two seasons. Rabbit manure fertilizer increased the soil pH and EC and significantly (p ≤ 5%) reduced the soil NO3-N content. (3) The pig manure and rabbit manure fertilizer significantly (p ≤ 5%) increased the diversity and abundance of soil bacterial of Brassica rapa var. Chinensis, but had no significant effect on soil fungi. Pearson correlation analysis showed that soil TN, TP, organic carbon content and EC were significantly correlated with soil bacterial α - diversity. There were significant differences (p ≤ 5%) in the bacterial community structures between three treatments in two seasons, and significant differences (p ≤ 5%) in the fungal community structures between fertilizer treatments while not between two seasons. Pig manure and rabbit manure fertilizer decreased the relative abundance of soil Acidobacteria and Crenarchaeota, rabbit manure fertilizer significantly increased the abundance of Actinobacteria in the second season. Distance-based redundancy analysis (dbRDA) showed that soil EC, TN, and organic carbon content were key physico-chemical factors in determining bacterial community structure in Brassica rapa var. Chinensis soil, and soil NO3-N, EC, SOC concentration and soil pH in the fungal community structure.

A Systematic Review of the Effects of Fecal Sludge Derived Amendments on Crop Growth and Soil Health

The use of human excreta in agricultural settings has the potential to meet crop nutrient requirements and improve soil health, while also providing a sustainable end use for fecal material. Previous reviews have focused on sewage sludge biosolids from wastewater treatment plants, but with on-site sanitation systems overtaking sewers as the leading sanitation system worldwide, greater attention to fecal sludge is warranted. This systematic Review is the first to compile the results of crop trials which utilized fecal amendments from on-site sanitation systems and includes 47 experiments. Overall, fecal amendments increased crop growth compared to unamended control plots and also produced comparable yields to synthetic fertilizers. Biological and physical soil parameters were underrepresented in the literature, which made a holistic assessment of soil health impossible. However, some improvements in chemical characteristics were observed, most notably for soil organic carbon. Inconsistent experimental design made aggregation of results and detailed statistical analysis difficult, highlighting the need for a more standardized approach for testing the efficacy of amendments and reporting results. Regardless, this Review compiles our collective existing knowledge to provide tentative results for the effect of fecal amendments on crop growth and soil health and offers recommendations for future work.

Anaerobic Fluidized-Bed Membrane Bioreactor for Treatment of Liquid Fraction of Sludge Digestate: Performance and Agricultural Reuse Analysis

The treatment of sludge digestion liquid is a big challenge in wastewater treatment. If treated as normal wastewater, large amounts of nitrogen and phosphorus present in the sludge digestion liquid might be wasted when they could be reused in agricultural irrigation and reduce the consumption of artificial fertilizers. Thus, it is of utmost importance to deliver a simple and feasible strategy to treat sludge digestion liquid for agricultural reuse. In this study, a novel type of anaerobic fluidized bed membrane bioreactor system (US-AnFMBR) was developed by combining an ultrasonic processing unit and biochar in AnFMBR. The improvement of sludge properties, removal of pollutants performance and membrane fouling mitigation were achieved in this novel system. The optimal dose of BC (biochar) was 2.5 g·L−1, and the optimal ultrasonic treatment conditions were 30 min at 26 W. The main contribution of ultrasound was to improve the activity of sludge microorganisms to adsorb and degrade more organic matter present in sewage. The system achieved the removal efficiencies of COD, NH4+-N and PO43−-P up to 89.41%, 49.29% and 54.83%, respectively, and had a better mitigation effect in terms of membrane fouling. On the one hand, the biochar addition for COD removal performance was mainly manifested in membrane rejection performance. On the other hand, the combination of low-cost biochar and AnFMBR can also provide new ideas for the recycling of agricultural waste for biochar production. However, regarding the removal efficiency of NH4+-N and PO43−-P, the US-AnFMBR system promoted the activity of starved sludge to preferentially absorb NH4+-N compared with PO43−-P by statistical analysis. The US-AnFMBR can reduce the viscosity of sludge and release more small molecular substances, thus better mitigating membrane fouling. Long-term operation performance also revealed the excellent stability of the sludge digestion liquid treatment. The US-AnFMBR system achieves the recovery of nitrogen and phosphorus resources for subsequent agricultural recycling, and avoids the eutrophication of water ecosystems. Reclaimed water meets the nutrient requirements of typical crops during the growing season. To a certain extent, carbon emission reductions in agriculture can be achieved.

Can crop modelling, proximal sensing and variable rate application techniques be integrated to support in-season nitrogen fertilizer decisions? An application in corn

Nitrogen (N) fertilization in corn is often based on uniform rates and yield goals without considering the spatial and temporal variability of yield potential. It is well documented how uniform N rates lead to low N use efficiencies and environmental issues, resulting in reduced profit for farmers. Several site-specific approaches have been proposed to capture the yield spatial variability and adjust N rates to the actual crop nutrient requirements. The current study presents two original, site-specific N fertilization approaches, where two approaches at integrating crop simulation models, seasonal forecast and proximal sensing were tested across two corn seasons (2019 and 2020) in a field with significant spatial variability. In the first approach, top dressing N prescription maps were determined using the DSSAT crop model run with historical weather data, while in the second one, the maps were determined coupling DSSAT with seasonal forecasts and proximal sensing. Compared to the uniform fertilization treatment, both model-based approaches led to higher yields, N efficiency and gross margin in 2019 but not in 2020. The 2020 season was characterized by several major rainfall events, which were not present in the historical or seasonal forecast datasets. This inconsistency led to a substantial underestimation of the N leaching events in both model-based methodologies and consequently to higher-than-needed N fertilizer recommendations. Future studies should therefore focus on identifying ways to provide accurate seasonal estimates of extreme weather events to enable crop models to provide better N recommendations. In addition, the integration of proximal and remote sensing data into the crop model should be tested later in the season when spatial variability in crop N status peaks.

UAV‐Based Prediction of Sugarbeet Yield and Quality

In Idaho, nitrogen (N) and water management are two major factors affecting sugarbeet yield and quality. If sugarbeet crop yield potential can be accurately predicted early in the growing season, then the crop can be topdressed based on crop nutrient requirements. This approach has the potential to improve the economic returns to sugarbeet growers and processors. The objective of this study was to assess the feasibility of predicting root yield and estimated recoverable sugar using UAV-based normalized difference vegetation index (NDVI) in sugarbeets grown under varied N and water rates. Earn 0.5 CEUs in Crop Management by reading the article and taking the quiz at https://web.sciencesocieties.org/Learning-Center/Courses.