Prioritizing Crop Management to Increase Nitrogen Use Efficiency in Australian Sugarcane Crops

Sugarcane/soybean intercropping with reduced nitrogen addition promotes photosynthesized carbon sequestration in the soil

Introduction

Sugarcane/soybean intercropping with reduced nitrogen (N) addition has improved soil fertility and sustainable agricultural development in China. However, the effects of intercropping pattern and N fertilizer addition on the allocation of photosynthesized carbon (C) in plant-soil system were far less understood.

Methods

In this study, we performed an 13CO2 pulse labeling experiment to trace C footprints in plant-soil system under different cropping patterns [sugarcane monoculture (MS), sugarcane/soybean intercropping (SB)] and N addition levels [reduced N addition (N1) and conventional N addition (N2)].

Results and discussion

Our results showed that compared to sugarcane monoculture, sugarcane/soybean intercropping with N reduced addition increased sugarcane biomass and root/shoot ratio, which in turn led to 23.48% increase in total root biomass. The higher root biomass facilitated the flow of shoot fixed 13C to the soil in the form of rhizodeposits. More than 40% of the retained 13C in the soil was incorporated into the labile C pool [microbial biomass C (MBC) and dissolved organic C (DOC)] on day 1 after labeling. On day 27 after labeling, sugarcane/soybean intercropping with N reduced addition showed the highest 13C content in the MBC as well as in the soil, 1.89 and 1.14 times higher than the sugarcane monoculture, respectively. Moreover, intercropping pattern increased the content of labile C and labile N (alkaline N, ammonium N and nitrate N) in the soil. The structural equation model indicated that the cropping pattern regulated 13C sequestration in the soil mainly by driving changes in labile C, labile N content and root biomass in the soil. Our findings demonstrate that sugarcane/soybean intercropping with reduced N addition increases photosynthesized C sequestration in the soil, enhances the C sink capacity of agroecosystems.

Identification and functional characterization of the sugarcane (Saccharum spp.) AMT2-type ammonium transporter ScAMT3;3 revealed a presumed role in shoot ammonium remobilization

Sugarcane (Saccharum spp.) is an important crop for sugar and bioethanol production worldwide. To maintain and increase sugarcane yields in marginal areas, the use of nitrogen (N) fertilizers is essential, but N overuse may result in the leaching of reactive N to the natural environment. Despite the importance of N in sugarcane production, little is known about the molecular mechanisms involved in N homeostasis in this crop, particularly regarding ammonium (NH4 +), the sugarcane's preferred source of N. Here, using a sugarcane bacterial artificial chromosome (BAC) library and a series of in silico analyses, we identified an AMMONIUM TRANSPORTER (AMT) from the AMT2 subfamily, sugarcane AMMONIUM TRANSPORTER 3;3 (ScAMT3;3), which is constitutively and highly expressed in young and mature leaves. To characterize its biochemical function, we ectopically expressed ScAMT3;3 in heterologous systems (Saccharomyces cerevisiae and Arabidopsis thaliana). The complementation of triple mep mutant yeast demonstrated that ScAMT3;3 is functional for NH3/H+ cotransport at high availability of NH4 + and under physiological pH conditions. The ectopic expression of ScAMT3;3 in the Arabidopsis quadruple AMT knockout mutant restored the transport capacity of 15N-NH4 + in roots and plant growth under specific N availability conditions, confirming the role of ScAMT3;3 in NH4 + transport in planta. Our results indicate that ScAMT3;3 belongs to the low-affinity transport system (Km 270.9 µM; Vmax 209.3 µmol g-1 root DW h-1). We were able to infer that ScAMT3;3 plays a presumed role in NH4 + source-sink remobilization in the shoots via phloem loading. These findings help to shed light on the functionality of a novel AMT2-type protein and provide bases for future research focusing on the improvement of sugarcane yield and N use efficiency.

Optimizing foliar N-fertilization in sugarcane depends on plant genotype and nitrogen concentration

Foliar N-fertilization (FNf) has emerged as a promising approach to synchronize plant nitrogen (N) demands and application timing, reducing the N losses to the environment associated with traditional soil-based fertilization methods. However, limited information exists regarding the effectiveness of FNf in sugarcane. This study aimed to optimize FNf in sugarcane by evaluating N-fertilizer recovery by the plant (NRP) and assessing potential toxicity effects. Four sugarcane genotypes were subjected to FNf using 15 N-urea at five nitrogen concentrations. NRP was assessed at five time points for roots, stalk, old leaves, 15 N-urea-fertilized leaves (15 NL), and unexpanded leaves (UEL). Leaf scorching, indicating FNf toxicity, was analyzed using morpho-anatomical and histochemical techniques. The results showed that FNf promoted high NRP, with an average recovery of 62.3%. Surprisingly, the redistribution of 15 N-urea did not follow the nitrogen uptake rate by sugarcane leaves, with an average of 41.3% of the total-NRP. The stalk emerged as the primary sink for 15 N-urea, followed by the UEL. Genotypes differed in the leaf scorching intensity, which increased with higher concentration of 15 N-urea. Genotypes also differed in the 15 N-urea uptake rate, down-regulated by the N content in the 15 NL. These findings emphasize that by carefully choosing the appropriate genotype and nitrogen concentration, FNf can significantly enhance N-fertilizer uptake, resulting in potential environmental and economic benefits.

Sugarcane productivity and sugar yield improvement: Selecting variety, nitrogen fertilizer rate, and bioregulator as a first-line treatment

The improvement of sugarcane productivity depends on the crop varieties, growth environments, and management practices. In particular, the selection of the most productive variety and the use of an optimal fertilizer rate and plant bioregulator are critical for increasing sugarcane productivity and sugar yield. This study aimed to determine the high-performing sugarcane variety, optimal nitrogen rate, and potential bioregulator for improved sugarcane production, juice quality, and sugar yield. Two sugarcane varieties (D42/58 and NCo-334), three nitrogen (N) fertilizer rates (0, 100, and 150 kg/ha), and two bioregulators (Agrostemin and Crops®) were used for the study. The study revealed that sugarcane variety had a significant effect on all growth, yield, and quality parameters. Plant height was significantly influenced by variety and bioregulators, while stalk population was significantly influenced by two- and three-way interactions of varieties, bioregulators, and N fertilizer rates. Cane weight was significantly affected by variety, N fertilizer rate, and bioregulators, whereas cane yield was significantly affected by variety, N fertilizer, and their interaction effects. Sugar yield was similarly influenced by variety, bioregulator, and their interaction. The three main factors, as well as their two- and three-way interactions, had a considerable influence on cane quality parameters. Sugarcane variety D42/58 significantly outperformed variety NCo-334 in terms of sprouting, number of tillers, plant height, number of millable canes, and sucrose percentage by 7.49%, 9.50%, 12.80%, 10.50%, and 9.10%, respectively. The use of the D42/58 variety with N fertilizer (at 100 kg/ha) and/or the Agrostemin bioregulator also led to higher performance in cane population (107126), cane yield (153.34 tons/ha), Pol % (15.81%), and sugar yield (10.25 tons/ha). Most sugarcane growth, yield, juice quality, and sugar yield parameters were positively correlated; hence, high-performing varieties, appropriate N rates, and plant bioregulators could boost sugarcane productivity and sugar yield. Overall, the selection and combination of sugarcane variety D42/58 with 100 kg N/ha and/or Agrostemin bioregulator could maximize sugarcane production, juice quality, and sugar yield. To confirm the current findings, however, more research needs to be conducted across different agroecologies and seasons.

Fertilizer source and application method influence sugarcane production and nutritional status

INTRODUCTION

The contrasting weather conditions throughout the sugarcane harvest period in south-central Brazil (April to November) influence fertilization management in sugarcane ratoon.

METHODS

Through field studies carried out over two cropping seasons, we aimed to compare the performance of sugarcane at sites harvested in the early and late periods of the harvest season as a function of fertilizer sources associated with application methods. The design used in each site was a randomized block in a 2 x 3 factorial scheme; the first factor consisted of fertilizer sources (solid and liquid), and the second factor consisted of application methods (above the straw, under the straw, and incorporated into the middle of the sugarcane row).

RESULTS

The fertilizer source and application method interacted at the site harvested in the early period of the sugarcane harvest season. Overall, the highest sugarcane stalk and sugar yields at this site were obtained with the incorporated application applying liquid fertilizer and under straw applying solid fertilizer, with increments of up to 33%. For the site harvested in the late period of the sugarcane harvest season, the liquid fertilizer promoted a 25% higher sugarcane stalk yield compared to the solid fertilizer in the crop season with low rainfall in the spring, while in the crop season with normal rainfall, there were no differences between treatments.

DISCUSSION

This demonstrates the importance of defining fertilization management in sugarcane as a function of harvest time, thereby promoting greater sustainability in the production system.

Effect of Rational Fertilizer for Eggplants on Nitrogen and Phosphorus Pollutants in Agricultural Water Bodies

Excessive fertilizer application in the cropping industry leads to excessive nitrogen and phosphorus in surrounding water bodies, which causes farmers to increase economic cost and damage the environment. To address the problem, we built a crop-soil runoff soil column test system, setting eight fertilizer application levels for eggplants. Then, crop yield, soil fertility and pollutant concentrations in the receiving water bodies were measured. The process of fertilizer application on the water quality of surrounding receiving water bodies and the rationality of fertilizer application were analyzed. The results showed that crop yield, soil fertility, and pollutant concentrations in the receiving water increased with the increase in fertilizer application. The crop yield stabilized when the fertilizer application amount was higher than 0.12 kg/m2; the concentrations of total nitrogen (TN) and total phosphorus (TP) in the water increased significantly with the increase in fertilizer application, where particulate nitrogen (PN) and organic phosphorus (OP) were the key pollutants. In addition, crop growth had an interception effect on pollutant migration. The concentration of pollutants in the water was significantly lower in the late crop growth period (after flowering) than in the early. The crop had the best interception effect on pollutants when the fertilizer application was 0.12 kg/m2. The concentrations of TN and TP in the water were 29.7% and 22.3% after the flowering period, being lower than those before the flowering period. Therefore, a reasonable value of 0.12 kg/m2 is recommended for fertilizer application in this article. It can provide a reference for the fertilization system of eggplant planting in North China and theoretical support for the realization of clean production in small rural watershed planting.

Driving forces of nitrogen use efficiency in Chinese croplands on county scale

Nitrogen use efficiency (NUE, defined as the fraction of N input harvested as product) is an important indicator to understand nitrogen use and losses in croplands as an element of determining sustainable food production. China, as the country with the largest amount of nitrogen fertilizer use globally, research into NUE consistently finds it to be much lower than that in developed countries. Understanding the driving forces of the underlying causes of this low NUE is thus crucial to improve nitrogen use and reduce losses in China. Here we applied the CHANS model to estimate cropland NUE for over 2800 counties in China for the year 2017. Results showed that in most counties NUE ranged between 20% and 40%, while an NUE >50% was mainly found in Northeastern China, likely as a result of large-scale, modern agriculture operations. The source of N input and crop types significantly affected NUE in our assessment. Nitrogen deposition, straw recycling, and biological nitrogen fixation (BNF) could improve NUE, while chemical nitrogen fertilizer and manure inputs reduce NUE. Grain crops have a much higher NUE compared to vegetables, which are often over-fertilized. Moreover, NUE in Southern China is strongly influenced by natural factors such as temperature and precipitation. Specifically, NUE in the Yangtze River Delta (eastern coastal region of China) is associated with socio-economic factors including GDP and the degree of urbanization, while in North-central China, NUE is mainly determined by nitrogen input sources. These examples illustrate that approaches aiming at improving NUE need to be location-specific with consideration of multiple natural and socioeconomic factors.

Functional characterization of the sugarcane (Saccharum spp.) ammonium transporter AMT2;1 suggests a role in ammonium root-to-shoot translocation

AMMONIUM TRANSPORTER/METHYLAMMONIUM PERMEASE/RHESUS (AMT) family members transport ammonium across membranes in all life domains. Plant AMTs can be categorized into AMT1 and AMT2 subfamilies. Functional studies of AMTs, particularly AMT1-type, have been conducted using model plants but little is known about the function of AMTs from crops. Sugarcane (Saccharum spp.) is a major bioenergy crop that requires heavy nitrogen fertilization but depends on a low carbon-footprint for competitive sustainability. Here, we identified and functionally characterized sugarcane ScAMT2;1 by complementing ammonium uptake-defective mutants of Saccharomyces cerevisiae and Arabidopsis thaliana. Reporter gene driven by the ScAMT2;1 promoter in A. thaliana revealed preferential expression in the shoot vasculature and root endodermis/pericycle according to nitrogen availability and source. Arabidopsis quadruple mutant plants expressing ScAMT2;1 driven by the CaMV35S promoter or by a sugarcane endogenous promoter produced significantly more biomass than mutant plants when grown in NH₄ ⁺ and showed more ¹⁵N-ammonium uptake by roots and nitrogen translocation to shoots. In A. thaliana, ScAMT2;1 displayed a K_m of 90.17 µM and V_max of 338.99 µmoles h^-1 g^-1 root DW. Altogether, our results suggest that ScAMT2;1 is a functional high-affinity ammonium transporter that might contribute to ammonium uptake and presumably to root-to-shoot translocation under high NH₄ ⁺ conditions.

Filtered mud improves sugarcane growth and modifies the functional abundance and structure of soil microbial populations

BACKGROUND

Exploring high-quality organic amendments has been a focus of sustainable agriculture. Filtered mud (FM), a sugar factory waste derived from sugarcane stems, could be an alternative organic amendment for sugarcane production. However, the effects of its application proportions on soil fertility, nutrient cycling, structure of soil bacterial and fungal communities, and the growth of sugarcane in clay-loam soils remain unexplored.

METHODS

Three application proportions of FM: (FM1-(FM: Soil at 1:4), FM2-(FM: Soil at 2:3), and FM3-(FM: Soil at 3:2)) were evaluated on sugarcane growth and soil nutrient cycling. High throughput sequencing was also employed to explore soil microbial dynamics.

RESULTS

We observed that FM generally increased the soil's nutritional properties while improving NO₃ ^- retention compared to the control, resulting in increased growth parameters of sugarcane. Specifically, FM1 increased the concentration of NH₄ ⁺-N, the N fraction preferably taken up by sugarcane, which was associated with an increase in the plant height, and more improved growth properties, among other treatments. An increase in the proportion of FM also increased the activity of soil nutrient cycling enzymes; urease, phosphatase, and β-glucosidase. High throughput sequencing revealed that FM reduced the diversity of soil bacteria while having insignificant effects on fungal diversity. Although increasing FM rates reduced the relative abundance of the phyla Proteobacteria, its class members, the Gammaproteobacteria and Betaproteobacteria containing some N-cycling related genera, were stimulated. Also, FM stimulated the abundance of beneficial and lignocellulose degrading organisms. These included the bacterial phyla Actinobacteria, Bacteroidetes, Acidobacteria, Chloroflexi, and the fungal phylum Ascomycota. The distribution of the soil microbial community under FM rates was regulated by the changes in soil pH and the availability of soil nutrients. Since FM1 showed more promise in improving the growth properties of sugarcane, it could be more economical and sustainable for sugarcane production in clay-loam soils.

Ten years of monitoring dissolved inorganic nitrogen in runoff from sugarcane informs development of a modelling algorithm to prioritise organic and inorganic nutrient management

Reducing nitrogen (N) losses from cropping systems to aquatic ecosystems is a global priority. In Australia, N losses from sugarcane production in catchments adjacent to the Great Barrier Reef (GBR) are threatening the health of this World Heritage-listed coral reef ecosystem. N losses from sugarcane can be reduced by improving fertiliser management. However, little is known about the contribution of organic sources of N, such as mill mud. We used more than 10 years of data from two of the main Australian sugarcane regions, a high (Wet Tropics) and moderate (Mackay Whitsundays) rainfall area, to calibrate and validate a model to predict dissolved inorganic nitrogen (DIN) losses in runoff from both inorganic and organic fertilisers. DIN losses in runoff were well simulated (RMSE = 0.37 and 2.0 kg N ha^-1 for the Wet Tropics and Mackay Whitsunday regions, respectively). Long-term simulations of rate and fertiliser deductions to account for N from organic sources showed that adopting best management practices for organic fertiliser (applying ≤50 wet t ha^-1 mill mud) can significantly reduce DIN in runoff losses compared with applications of 150 wet t ha^-1. Simulations of typical farmer practices in relation to fallow management (bare fallow vs. legume fallow) and organic fertiliser placement (buried in a fallow but surface applied to a green cane trash blanket in ratoons) showed that inorganic fertiliser rates need to be adjusted to account for N inputs from both mill mud and legume crops. Rates of application of organic N had a larger impact on DIN runoff losses than placement or timing of application. This work presents a DIN in runoff modelling algorithm that can be coupled with nitrogen models readily available in agricultural models to assess the impact of nutrient management on the quality of water leaving agricultural systems.

A multi-model approach to assessing the impacts of catchment characteristics on spatial water quality in the Great Barrier Reef catchments

Water quality monitoring programs often collect large amounts of data with limited attention given to the assessment of the dominant drivers of spatial and temporal water quality variations at the catchment scale. This study uses a multi-model approach: a) to identify the influential catchment characteristics affecting spatial variability in water quality; and b) to predict spatial variability in water quality more reliably and robustly. Tropical catchments in the Great Barrier Reef (GBR) area, Australia, were used as a case study. We developed statistical models using 58 catchment characteristics to predict the spatial variability in water quality in 32 GBR catchments. An exhaustive search method coupled with multi-model inference approaches were used to identify important catchment characteristics and predict the spatial variation in water quality across catchments. Bootstrapping and cross-validation approaches were used to assess the uncertainty in identified important factors and robustness of multi-model structure, respectively. The results indicate that water quality variables were generally most influenced by the natural characteristics of catchments (e.g., soil type and annual rainfall), while anthropogenic characteristics (i.e., land use) also showed significant influence on dissolved nutrient species (e.g., NO_X, NH₄ and FRP). The multi-model structures developed in this work were able to predict average event-mean concentration well, with Nash-Sutcliffe coefficient ranging from 0.68 to 0.96. This work provides data-driven evidence for catchment managers, which can help them develop effective water quality management strategies.

The potential for refining nitrogen fertiliser management through accounting for climate impacts: An exploratory study for the Tully region

Increasing the precision of nitrogen (N) fertiliser management in cropping systems is integral to increasing the environmental and economic sustainability of cropping. In a simulation study, we found that natural variability in year-to-year climate had a major effect on optimum N fertiliser rates for sugarcane in the Tully region of north-eastern Australia, where N discharges pose high risks to Great Barrier Reef ecosystems. There were interactions between climate and other factors affecting crop growth that made optimum N rates field-specific. The regional average optimum N fertiliser rate was substantially lower than current industry guidelines. Likewise, simulated N losses to the environment at optimum N fertiliser rates were substantially lower than the simulated losses at current industry fertiliser guidelines. Dissolved N discharged from rivers is related to fertiliser applications. If the reductions in N applications identified in the study occurred in the Tully region, the reduction in dissolved N discharges from rivers in the region would almost meet current water quality improvement targets. Whilst there were many assumptions made in this exploratory study, and there are many steps between the study and a practically implemented dynamic N fertiliser recommendation system, the potential environmental benefits justify field validation and further development of the concepts identified in the study.

Depth-dependent influence of biochar application on the abundance and community structure of diazotrophic under sugarcane growth

Despite progress in understanding diazotrophic distribution in surface soils, few studies have investigated the distribution of diazotrophic bacteria in deeper soil layers. Here, we leveraged high-throughput sequencing (HTS) of nifH genes obtained to assess the influence of biochar amended soil (BC) and control (CK), and soil depths (0–20, 20–40 and 40–60 cm) on diazotrophic abundance and community structures, soil enzyme activities and physio-chemical properties. Multivariate ANOVA analysis revealed that soil depth had profound impact on majority of the soil parameters measured than fertilization. Although soil physio-chemical properties, enzymes activities, diazotrophic genera and enriched operational taxonomic units (OTUs) were significantly influenced across the entire soil profiles, we also observed that BC amended soil significantly increased cane stalk height and weight, nitrate (NO₃^-), ammonium (NH₄⁺), organic matter (OM), total carbon (TC) and available potassium (AK), and enhanced diazotrophic genera in soil depth 0–20 cm compared to CK treatment. Soil TC, total nitrogen (TN), OM and NH₄⁺ were the major impact factors shifting diazotrophic community structures in soil depth 0–20 cm. Overall, these results were more pronounced in 0–20 cm soil depth in BC than CK treatment.

Land use change in the river basins of the Great Barrier Reef, 1860 to 2019: A foundation for understanding environmental history across the catchment to reef continuum

Land use in the catchments draining to the Great Barrier Reef lagoon has changed considerably since the introduction of livestock grazing, various crops, mining and urban development. Together these changes have resulted in increased pollutant loads and impaired coastal water quality. This study compiled records to produce annual time-series since 1860 of human population, livestock numbers and agricultural areas at the scale of surface drainage river basins, natural resource management regions and the whole Great Barrier Reef catchment area. Cattle and several crops have experienced progressive expansion interspersed by declines associated with droughts and diseases. Land uses which have experienced all time maxima since the year 2000 include cattle numbers and the areas of sugar cane, bananas and cotton. A Burdekin Basin case study shows that sediment loads initially increased with the introduction of livestock and mining, remained elevated with agricultural development, and declined slightly with the Burdekin Falls Dam construction.

Long-term N fertilization reduces uptake of N from fertilizer and increases the uptake of N from soil

Long-term supply of synthetic nitrogen (N) has the potential to affect the soil N processes. This study aimed to (i) establish N response curves to find the best balance between inputs and outputs of N over four ratoons; (ii) use ¹⁵N-labeled fertilizer to estimate the N recovery efficiency of fertilizer applied in the current season as affected by the N management in the previous three years. Nitrogen rates (control, 60, 120, and 180 kg ha⁻¹ N) were applied annually in the same plots after the 1st, 2nd, 3rd, and 4th sugarcane cycles. Sugarcane yield, N uptake, and N balance were evaluated. In the final season, 100 kg ha⁻¹ of ¹⁵N was also applied in the microplots to evaluate the effect of previous N fertilization on N derived from fertilizer (NDF) and N derived from soil (NDS). Sugarcane yields increased linearly with the N rates over the four sugarcane-cycles. The best balance between the input of N through fertilizer and N removal by stalks was 90 kg ha⁻¹ N in both the 1st and 2nd ratoons, and 71 kg ha⁻¹ N in both the 3rd and 4th ratoons. Long-term application of N reduced NDF from 41 to 30 kg ha⁻¹ and increased NDS from 160 to 180 kg ha⁻¹ N. A key finding is that long-term N fertilization has the potential to affect soil N processes by increasing the contribution of soil N and reducing the contribution of N from fertilizer.

Retrieval of aboveground crop nitrogen content with a hybrid machine learning method

Hyperspectral acquisitions have proven to be the most informative Earth observation data source for the estimation of nitrogen (N) content, which is the main limiting nutrient for plant growth and thus agricultural production. In the past, empirical algorithms have been widely employed to retrieve information on this biochemical plant component from canopy reflectance. However, these approaches do not seek for a cause-effect relationship based on physical laws. Moreover, most studies solely relied on the correlation of chlorophyll content with nitrogen, and thus neglected the fact that most N is bound in proteins. Our study presents a hybrid retrieval method using a physically-based approach combined with machine learning regression to estimate crop N content. Within the workflow, the leaf optical properties model PROSPECT-PRO including the newly calibrated specific absorption coefficients (SAC) of proteins, was coupled with the canopy reflectance model 4SAIL to PROSAIL-PRO. The latter was then employed to generate a training database to be used for advanced probabilistic machine learning methods: a standard homoscedastic Gaussian process (GP) and a heteroscedastic GP regression that accounts for signal-to-noise relations. Both GP models have the property of providing confidence intervals for the estimates, which sets them apart from other machine learners. Moreover, a GP-based sequential backward band removal algorithm was employed to analyze the band-specific information content of PROSAIL-PRO simulated spectra for the estimation of aboveground N. Data from multiple hyperspectral field campaigns, carried out in the framework of the future satellite mission Environmental Mapping and Analysis Program (EnMAP), were exploited for validation. In these campaigns, corn and winter wheat spectra were acquired to simulate spectral EnMAP data. Moreover, destructive N measurements from leaves, stalks and fruits were collected separately to enable plant-organ-specific validation. The results showed that both GP models can provide accurate aboveground N simulations, with slightly better results of the heteroscedastic GP in terms of model testing and against in situ N measurements from leaves plus stalks, with root mean square error (RMSE) of 2.1 g/m². However, the inclusion of fruit N content for validation deteriorated the results, which can be explained by the inability of the radiation to penetrate the thick tissues of stalks, corn cobs and wheat ears. GP-based band analysis identified optimal spectral settings with ten bands mainly situated in the shortwave infrared (SWIR) spectral region. Use of well-known protein absorption bands from the literature showed comparative results. Finally, the heteroscedastic GP model was successfully applied on airborne hyperspectral data for N mapping. We conclude that GP algorithms, and in particular the heteroscedastic GP, should be implemented for global agricultural monitoring of aboveground N from future imaging spectroscopy data.

Assessment of Diazotrophic Proteobacteria in Sugarcane Rhizosphere When Intercropped With Legumes (Peanut and Soybean) in the Field

Several factors influenced the sugarcane production, and among them, higher use of nitrogen and depletion of soil nutrient constitutes a significant concern in China. Sugarcane-legume intercropping may help to regulate the microbial structure and functions. In the present study, sugarcane rhizosphere soils of three cropping systems: Sugarcane only (S-only), sugarcane with peanut (S + P), and sugarcane + soybean (S + S) were sampled in tillering, elongation, and maturation stages from two different experimental fields. High-throughput sequencing technologies applied to assess the effects of different cropping systems on the structure of nitrogenase (nifH) gene communities. A total of 3818 OTUs (operational taxonomic units) were acquired from all soil samples. Intercropping systems noticeably increased the relative abundance of Proteobacteria in the tillering stage. The increased microbial diversity in the rhizosphere was mainly due to soil organic carbon and total soil N. In contrast, intercropping has no significant negative impact on microbial abundance, but sugarcane growth stages influence it significantly, and two bacteria (Bradyrhizobium and Pseudacidovorax) showed significant shift during plant growth. The results provide insight into the microbial structure of Proteobacteria in the sugarcane legume-intercropping field, and how microbial community behaves in different growth stages. It can boost the microbial activity of the soil, and that could be a new strategy to stimulate soil fertility without causing any negative impact on crop production.

Liming Positively Modulates Microbial Community Composition and Function of Sugarcane Fields

Liming combined with an optimum quantity of inorganic fertilizer, as a soil amendment in intensive agriculture, is a viable agricultural practice in terms of improving soil nutrient status and productivity, as well as mitigating soil degradation. The chief benefits of this strategy are fundamentally dependent on soil microbial function. However, we have limited knowledge about lime’s effects on soil microbiomes and their functions, nor on its comprehensive influence on soil nutrient status and the productivity of sugarcane plantations. This study compares the impacts of lime application (1-year lime (L1), 2-year lime (L2), and no lime (CK) on microbial communities, their functions, soil nutrient status, and crop yield in a sugarcane cropping system. We employed Illumina sequencing and functional analysis (PICRUSt and FUNGuild) to decipher microbial communities and functions. In comparison with CK, lime application (L1 and L2) mitigated soil acidity, increased the level of base cations (Ca2+ and Mg2+), and improved soil nutrient status (especially through N and P) as well as soil microbial functions associated with nutrient cycling and that are beneficial to plants, thereby improving plant agronomic parameters and yield. Liming (L1 and L2) increased species richness and stimulated an abundance of Acidobacteria and Chloroflexi compared to CK. In comparison with CK, the two functional categories related to metabolism (amino acid and carbohydrate) increased in the L1 field, whereas cofactors and vitamin metabolites increased in the L2 field. Turning to fungi, compared to CK, liming enriched symbiotrophs (endophytes, ectomycorrhizae, and arbuscular mycorrhizae) and led to a reduction of saprotrophs (Zygomycota and wood saprotrophs) and pathotrophs. The observed benefits of liming were, in turn, ultimately reflected in improved sugarcane agronomic performance, such as increased stalk height and weight in the sugarcane planting system. However, the increase in the above-mentioned parameters was more prominent in the L2 field compared to the L1 field, suggesting consecutive liming could be a practical approach in terms of sustainable production of sugarcane.

A Spatiotemporal Analysis of Nitrogen Pollution in a Coastal Region with Mangroves of the Southern Gulf of Mexico

Nitrogen pollution is a growing problem in many rivers and estuaries of the Southern Gulf of Mexico. In Costa Esmeralda, a tourist destination in Veracruz, the increasing nitrogen pollution is causing severe environmental damage. However, very few studies addressed nitrogen pollution and its consequences for beaches and mangroves. In this study, a spatiotemporal evaluation of nitrogen concentrations was performed along two rivers discharging into Costa Esmeralda and the associated mangrove and coastal areas. The data used was obtained from the local government, which measured ammonium, nitrate and organic nitrogen concentrations between 2013 and 2016 with four annual measurements. Clustering analysis was used to detect the nitrogen concentration differences between riverine and coastal sites. Additionally, Mann-Kendall test was used to detect the trends throughout the study period. The Mann-Whitney W-test determined the difference in the median concentrations between the dry and the wet season. The results indicate that organic nitrogen concentrations are increasing in river mouths and coastal waters. Nitrogen pollution caused an intrusion of water hyacinths in touristic beaches and completely covered mangroves. The decomposition of these plants in saline waters was identified as the main potential source of increasing organic concentrations, driven by nitrogen pollution from wastewater, deforestation and fertilizers, and causing many environmental and socio-economic damage to the area. The results shed light on the prevailing water pollution problems in the Southern Gulf of Mexico.

Estimating economic and environmental trade-offs of managing nitrogen in Australian sugarcane systems taking agronomic risk into account

Use of chemical agricultural inputs such as nitrogen fertilisers (N) in agricultural production can cause diffuse source pollution thereby degrading the health of coastal and marine ecosystems in coastal river catchments. Previous reviewed economic assessments of N management in agricultural production seldom consider broader environmental impacts and uncertain climatic and economic conditions. This paper presents an economic risk framework for assessing economic and environmental trade-offs of N management strategies taking into account variable climatic and economic conditions. The framework is underpinned by a modelling platform that integrates Agricultural Production System sIMulation modelling (APSIM), probability theory, Monte Carlo simulation, and financial risk analysis techniques. We applied the framework to a case study in Tully, a coastal catchment in north-eastern Australia with a well-documented N pollution problem. Our results show that switching from managing N to maximise private net returns to maximising social net returns could reduce expected private net returns by $99 ha^-1, but yield additional environmental benefits equal to $191 ha^-1. Further, switching from managing N to maximise private returns in years with the highest profit potential (hereafter, good years) to maximising mean social net returns could reduce expected private profits in good years by $277 ha^-1, but yield additional environmental benefits equal to $287 ha^-1. We contend that it is essential to incorporate farmer risk behaviour and environmental impacts in analyses that inform policies aimed at enhancing adoption of management activities for mitigating deterioration of the health of coastal and marine ecosystems due to diffuse source pollution from agricultural production.

Ground reference data for sugarcane biomass estimation in São Paulo state, Brazil

In order to make effective decisions on sustainable development, it is essential for sugarcane-producing countries to take into account sugarcane acreage and sugarcane production dynamics. The availability of sugarcane biophysical data along the growth season is key to an effective mapping of such dynamics, especially to tune agronomic models and to cross-validate indirect satellite measurements. Here, we introduce a dataset comprising 3,500 sugarcane observations collected from October 2014 until October 2015 at four fields in the São Paulo state (Brazil). The campaign included both non-destructive measurements of plant biometrics and destructive biomass weighing procedures. The acquisition plan was designed to maximize cost-effectiveness and minimize field-invasiveness, hence the non-destructive measurements outnumber the destructive ones. To compensate for such imbalance, a method to convert the measured biometrics into biomass estimates, based on the empirical adjustment of allometric models, is proposed. In addition, the paper addresses the precisions associated to the ground measurements and derived metrics. The presented growth dynamics and associated precisions can be adopted when designing new sugarcane measurement campaigns.