Monitoring Of Soil Nutrients Research Articles

A paper-based analytical device for the on-site multiplexed monitoring of soil nutrients extracted with a cafetière

Sustainable agricultural production has the aim to maximise the yield and quality of harvests. For that, farmers need to monitor nutrient levels within soils to apply fertilizers accordingly and to prevent land degradation and soil exhaustion. Current methods involve time-consuming sampling and transport to a laboratory; and most farmers do not have the resources to measure frequently at multiple locations, limiting their sustainable production. In order to address this challenge, a paper-based analytical device (PAD) for the multiplexed detection of soil nutrients, i.e. phosphate, nitrate and pH, extracted with a cafetière-based method, is developed in this work. The compact and easy-to-use platform enables an accurate soil analysis in less than 20min; 3min for extraction and 15min for readout. Two detection channels for nitrate and phosphate analysis, and one circular detection area for pH, including the selective reagents to each analyte, are defined within the PAD. Upon contact with the specific nutrients, the platform produces a colorimetric response that is easily readable by naked eye and smartphone camera. The detection reactions were optimized in the range 1 − 22.5mgL-1, 10 −100mgL-1 and 5.0 – 8.5 for phosphate, nitrate and pH, respectively, in agreement with the relevant levels in soils. The volume of water, the number of pushes of the plunger, the extraction time and the mass of soil were also optimized for the nutrient extraction method with the cafetière. The optimal workflow was validated with commercial soils and compared with the conventional UV-Vis method and the labels from the soil package, showing excellent agreement. This paper-based platform provides the possibility of a cheap, sensitive and specific monitoring of soil nutrients by minimally trained operators, such as farmers, enabling in-the-field analyses of multiple key soil nutrients in resource-limited settings and therefore addressing the challenge of routine monitoring for sustainable agriculture.

Soil Nutrients Inversion in Open‐Pit Coal Mine Reclamation Area of Loess Plateau, China: A Study Based on ZhuHai‐1 Hyperspectral Remote Sensing

ABSTRACTSoil nutrients are crucial to assess land reclamation quality, and the use of various types of remote sensing data for soil nutrient inversion has been a key focus for soil monitoring. However, fewer studies have been conducted using satellite‐based hyperspectral remote sensing. To explore the potential of satellite‐based hyperspectral remote sensing in soil nutrient monitoring, this study selected soil organic matter, total nitrogen, available phosphorus, and available potassium content data from 83 sample sites using ZhuHai‐1 hyperspectral data. After spectral transformation and feature extraction, various inversion models were constructed, including partial least squares regression, support vector machine, recurrent neural network, and random forest. After verification by accuracy, the best spectral‐model combination was used for inversion. The results showed that the R‐squared range of the inversion models was 0.67748–0.78115. High content areas of soil organic matter and available potassium exhibited concentrated and contiguous features, while high content areas of total nitrogen and available phosphorus were more fragmented and fine‐grained. Alfalfa grassland plays a vital role in improving reconstructed soil in the early reclamation stage, and agricultural activities have differential impacts on soil nutrient accumulation. This study provides a theoretical basis for verifying the application capability of ZhuHai‐1 hyperspectral satellite data in soil monitoring.

Quantitative Analysis of Iron Activity in Agricultural Soils Using X-ray Fluorescence Spectrometry: Comparative Study with an Undisturbed Reference Site in Niankhene, Senegal

An essential micronutrient for plant growth and development, iron (Fe) affects a number of physiological processes, including respiration and photosynthesis. This study compare the amounts of iron in agricultural zones and reference zones, describe the geographic distribution of iron, and assess its accessibility to cultures. The aim is to assess the deficiencies and excess soil disturbance in the Niankhène agricultural site while maintaining a stable site. Soil samples were taken at 0–20 cm and 20–40 cm depths from 47 agricultural stations and three reference points using X-ray fluorescence (XRF) spectroscopy. Significant variation in Fe concentrations was found by the research, with an average of roughly 3310.95 ppm and moderate variation between samples. An analysis conducted in comparison with reference locations revealed a widespread lack of Fe in the research area, with 85.71% of samples displaying depletion and only 14.29% displaying accumulation of Fe. This discrepancy emphasizes the necessity of focused soil management techniques to raise Niankhene's agricultural output. The results highlight how crucial it is to use site-specific soil management strategies in order to overcome Fe deficits and raise crop yields. This research highlights the possibility for establishing targeted fertilization and corrective procedures to maximize Fe availability by utilizing XRF technology for reliable soil nutrient monitoring. The study's findings offer insightful information for enhancing fertilization techniques and improving soil management techniques, which will support sustainable farming methods and increased crop yield in the area.

IoT Based Soil pH Detection and Crop Recommendation System

Agricultural productivity hinges on soil fertility, influenced by key factors like nitrogen, phosphorus, potassium, pH level, and soil moisture. Yet, achieving optimal crop growth is challenging due to limited farmer knowledge and difficulties in determining precise fertilizer quantities. Conventional soil analysis methods involve manual sampling andcostly lab tests, which are subjective. To address this, aproposed solution integrates IoT-enabled soil nutrient monitoring with machine learning algorithms for croprecommendations. Sensors collect data on crucial parameters like nitrogen, phosphorus, and soil temperature, transmitting it to a cloud-based database. Machine learning analyzes this data to suggest ideal crops, minimizing fertilizer use, reducing labor, and enhancing overall productivity. This innovative approach streamlines crop selection, minimizing unnecessary inputs while maximizing yields. By harnessing IoT and machine learning, farmers gain valuable insights into soil health, enabling precise fertilization and crop selection. This not only boosts agricultural productivity but also contributes to economic growth by fostering sustainable practices andincreased yields.

Development of Soil Microbial Fuel Cell for Continuous Real-time Monitoring of Soil Data

The planet is getting hotter due to human activities that release greenhouse gases. Promoting renewable energy, which doesn’t emit carbon, can help mitigate global warming. Farmland, which covers a large portion of the Earth’s land area, can also be used as an energy source through the help of indigenous microorganisms in the soil that transform chemical energy into electrical energy with electrolysis. Real-time monitoring of soil nutrients is necessary to obtain an accurate yield from crops. This is achieved with the use of sensors that are powered by the energy generated from the soil. Zinc and copper electrodes are used to generate power, and a combination of 15x6 cells is used to maximize voltage and current generation. The output powers soil sensors like FC-28 and NPK sensors, and the data is sent to the AWS cloud for real-time monitoring of soil parameters. The experimental results show that a single SMFC cell generates 0.6V, while a series-parallel combination generates approximately 9V. By using a current booster circuit, the efficiency of the setup can be further improved. This technology is not yet widely used in the agricultural industry, but it has the potential to help farmers conveniently monitor soil conditions by utilizing the power generated from the soil itself.

Time‐dependent effects of ecological rehabilitation on soil phosphorus fractions on cut slopes in the mountains of Southwest China

AbstractWhen a cut slope is excavated, the ecological environment in the footprint is destroyed. Soil spray seeding technique is used for the ecological rehabilitation of cut slopes in the mountain areas of Southwest China. However, there have been few studies of the temporal variation in soil phosphorus (P) fractions during the rehabilitation of the cut slopes. In this study, time‐dependent changes in soil inorganic P (Pi) and organic P (Po) fractions of the cut slopes were assessed at selected post‐rehabilitation ages (i.e., 1 year, 1a; 3 years, 3a; 5 years, 5a; and 11 years, 11a). The results showed that the amounts of Pi and Po fractions in soils on rehabilitated cut slopes varied with time. The reduction in the total Po (TPo) content was mainly caused by the change in high concentration hydrochloric acid‐soluble Po (HHCl‐Po) in the soil. The reason for the highest TP content in 3a was the addition of inorganic fertilizer and straw in the artificial soil. The analyses of Pearson correlation and multiple stepwise linear regression showed that TPo and N:P were the main factors affecting the availability of soil P. With the increase in the post‐rehabilitation age, the limitation of soil P gradually weakened, but nitrogen became one of the limiting factors for plant growth. Overall, soil nutrient monitoring is very important for vegetation restoration of the cut slopes. Applying organic fertilizer after 5 years of ecological rehabilitation is conducive to long‐term supply of nutrients required for plant growth.

Vis-NIR Spectroscopy Combined with GAN Data Augmentation for Predicting Soil Nutrients in Degraded Alpine Meadows on the Qinghai-Tibet Plateau.

Soil nutrients play vital roles in vegetation growth and are a key indicator of land degradation. Accurate, rapid, and non-destructive measurement of the soil nutrient content is important for ecological conservation, degradation monitoring, and precision farming. Currently, visible and near-infrared (Vis-NIR) spectroscopy allows for rapid and non-destructive monitoring of soil nutrients. However, the performance of Vis-NIR inversion models is extremely dependent on the number of samples. Limited samples may lead to low prediction accuracy of the models. Therefore, modeling and prediction based on a small sample size remain a challenge. This study proposes a method for the simultaneous augmentation of soil spectral and nutrient data (total nitrogen (TN), soil organic matter (SOM), total potassium oxide (TK2O), and total phosphorus pentoxide (TP2O5)) using a generative adversarial network (GAN). The sample augmentation range and the level of accuracy improvement were also analyzed. First, 42 soil samples were collected from the pika disturbance area on the QTP. The collected soils were measured in the laboratory for Vis-NIR and TN, SOM, TK2O, and TP2O5 data. A GAN was then used to augment the soil spectral and nutrient data simultaneously. Finally, the effect of adding different numbers of generative samples to the training set on the predictive performance of a convolutional neural network (CNN) was analyzed and compared with another data augmentation method (extended multiplicative signal augmentation, EMSA). The results showed that a GAN can generate data very similar to real data and with better diversity. A total of 15, 30, 60, 120, and 240 generative samples (GAN and EMSA) were randomly selected from 300 generative samples to be included in the real data to train the CNN model. The model performance first improved and then deteriorated, and the GAN was more effective than EMSA. Further shortening the interval for adding GAN data revealed that the optimal ranges were 30-40, 50-60, 30-35, and 25-35 for TK2O, TN, TP2O5, and SOM, respectively, and the validation set accuracy was maximized in these ranges. Therefore, the above method can compensate to some extent for insufficient samples in the hyperspectral prediction of soil nutrients, and can quickly and accurately estimate the content of soil TK2O, TN, TP2O5, and SOM.

Spatial distribution and quantitative source identification of nutrients and beneficial elements in the soil of a typical suburban area, Beijing.

Source identification and quality monitoring of soil nutrients and beneficial elements (NBEs) are crucial for agricultural production and environmental protection. In this study, grid sampling (223 topsoil samples and 223 subsoil samples) was carried out in the Tongzhou District of Beijing. The concentration level of representative NBEs (N, P, K, Ca, Mg, Se, V, Ge, Mn, Zn) and some typical soil properties representing indicators (total organic carbon, TFe2O3, Al2O3/SiO2, and pH) in soils and their spatial distribution were analyzed. The major sources contributing to these NBEs were assessed by principal component analysis (PCA), redundancy analysis (RDA), and positive matrix factorization (PMF) analysis. The results suggested that the soil parent material contributed 40.09-69.84% to Zn, V, Ge, Mn, F, and K in soils; the local external source contributed 54.89-75.04% to N, Se, and TOC; and the hydrous system contributed 40.67-77.31% to Ca and Mg. The enrichment degree of each NBE was calculated using the standardized concentration ratio method. These indices exhibited the influence and mixing process of different sources on the target NBEs in topsoils. The individual concentrations of the target NBEs and the combined concentrations of N, P, and K were used to evaluate the soil quality. Our study estimated the relative contributions from dominant sources to NBEs in soils from a typical suburban area, providing a basis for agricultural activities and environmental protection.

Growing season grazing promotes the shallow stratification of soil nutrients while non-growing season grazing sequesters the deep soil nutrients in a typical alpine meadow

Grazing management and climate are known to be important drivers influencing soil nutrient accumulation. The change of soil nutrients in pasture depends on the excreta return and the vegetation regeneration. Livestock activities significantly affect plant growth and soil nutrients through feeding, trampling, and excretion. At the same time, grazing time and climate change are stimulating plant growth and altering plant composition. How long-term specific grazing management will affect soil nutrient storage and movement under a warming-humid climate trend needs further study. In 20-year grazing management trial, conducted in a typical alpine meadow in the Qilian Mountains on the Qinghai-Tibet Plateau, sampled and analyzed the soil from under a non-growing season graze pasture (WP) and a growing season graze pasture (SAP) in August 1999 and August 2019 along grazing gradients (GG) at different distances from the pasture entrance (0, 300, 600, 900, 1200, and 1500 m). The experimental results of 2019 compared to 1999 show that SAP and WP increased soil available nitrogen density (SAND) and availability (SAND:soil total nitrogen density [STND] ratio) in the first 300 m along the grazing gradient soil, while SAP showed a decrease in soil available phosphorus density (SAPD) and availability (SAPD:soil total phosphorus density [STPD] ratio), and WP had no significant difference between gradients. Grazing in spring and autumn increased soil organic carbon density (SOCD), and STND in the first 300 m along the gradient soil, whereas it had the reverse effect in WP. At the same time, STPD has no obvious changing trend along the gradient. Growing and non-growing season grazing increased the SOCD:STND ratio in the first 300 m along the grazing gradient but resulted to a lower STND:STPD ratio. The comparison found that long-term grazing from 1999 to 2019 increased the SAND and SAPD. SAP improved soil total C, N, and P density in the topsoil (0–10 cm), but WP improved it throughout the profile (0–40 cm). These findings indicate that time of grazing and the grazing gradient affect the accumulation and migration of different elements under long-term grazing. Furthermore, SAP and WP had a positive effect on the accumulation of topsoil and deep soil nutrients, respectively. We suggest that periodic pasture exchange in SAP and WP should be carried out to maintain the sustainability of the ecosystem. At the same time, for different gradients, especially the first 300 m, regular soil nutrient monitoring and human intervention (such as fertilization) should be carried out to eliminate potential element restrictions and focus on the development of possible problems caused by the livestock locked in the pens at night, such as nutrient enrichment (the excreta as the organic fertilizer and soil improvement material for farmland) and loss (element footprint) in pens, which are of important guiding significance for the grazing system’s stable development of alpine meadow.

Estimation of Soil Nutrient Content Using Hyperspectral Data

Soil nutrients play a vital role in plant growth and thus the rapid acquisition of soil nutrient content is of great significance for agricultural sustainable development. Hyperspectral remote-sensing techniques allow for the quick monitoring of soil nutrients. However, at present, obtaining accurate estimates proves to be difficult due to the weak spectral features of soil nutrients and the low accuracy of soil nutrient estimation models. This study proposed a new method to improve soil nutrient estimation. Firstly, for obtaining characteristic variables, we employed partial least squares regression (PLSR) fit degree to select an optimal screening algorithm from three algorithms (Pearson correlation coefficient, PCC; least absolute shrinkage and selection operator, LASSO; and gradient boosting decision tree, GBDT). Secondly, linear (multi-linear regression, MLR; ridge regression, RR) and nonlinear (support vector machine, SVM; and back propagation neural network with genetic algorithm optimization, GABP) algorithms with 10-fold cross-validation were implemented to determine the most accurate model for estimating soil total nitrogen (TN), total phosphorus (TP), and total potassium (TK) contents. Finally, the new method was used to map the soil TK content at a regional scale using the soil component spectral variables retrieved by the fully constrained least squares (FCLS) method based on an image from the HuanJing-1A Hyperspectral Imager (HJ-1A HSI) of the Conghua District of Guangzhou, China. The results identified the GBDT-GABP was observed as the most accurate estimation method of soil TN ( of 0.69, the root mean square error of cross-validation (RMSECV) of 0.35 g kg−1 and ratio of performance to interquartile range (RPIQ) of 2.03) and TP ( of 0.73, RMSECV of 0.30 g kg−1 and RPIQ = 2.10), and the LASSO-GABP proved to be optimal for soil TK estimations ( of 0.82, RMSECV of 3.39 g kg−1 and RPIQ = 3.57). Additionally, the highly accurate LASSO-GABP-estimated soil TK (R2 = 0.79) reveals the feasibility of the LASSO-GABP method to retrieve soil TK content at the regional scale.

Assessment of status and distribution of available micronutrients in soils under different land uses of savannah North Central Region of Nigeria

This study examines the availability of micronutrients under different land uses: natural vegetation, tree plantations (orange and cashew) and arable crops (maize and guinea corn). Available zinc (Zn), copper (Cu), iron (Fe) and manganese (Mn) were analysed in one hundred and fifty (150) randomly selected soil samples. Iron at the topsoil and subsoil under tree plantations and natural vegetation was rated marginal, under arable crops it was marginal at topsoil and deficient at subsoil. Available Mn and Zn at the topsoil and subsoil was adequate under all the land uses, with the exception of maize which fell under marginal ranking at topsoil. Copper was rated deficient under arable crops and orange, marginal under cashew, while natural vegetation was marginal at subsoil and adequate at topsoil. The results revealed that arable crops unlike tree plantations statistically differed on all occasions when their mean scores were compared with those of the natural vegetation. Copper-enriched inorganic fertilizers should be used by farmers. Monitoring of soil nutrients should be carried out regularly, in order to improve upon sustainable farming.

Vis–NIR-based optical sensor system for estimation of primary nutrients in soil

A Vis–NIR-based optical sensor system for monitoring of soil nutrients has been developed in this work. This instrument allows the measurement of three nutrients: nitrogen, phosphorous and potassium in soil. The sensing is based on the diffused reflectance obtained from the sample when illuminated with source of appropriate wavelength. Based on extensive experimentation and analysis, the selectivity of the nutrients to specific wavelengths was found to be 850 nm for nitrogen, 620–630 nm for phosphorous and 460–470 nm for potassium. These three wavelength ranges have been selected considering the cross-sensitivity issue such that the sensor response to a target nutrient does not interfere with other nutrients present in the sample. Distinct mathematical models were developed for each of the three nutrients based on the reflectance characteristics curves of the nutrients. A full description of the instrument, methodology adopted, mathematical modelling and characterization has been carried out and is reported here. The response behavior of the system was studied based on parameters such as repeatability, reproducibility, sensitivity, linearity, R2, root-mean-square error, standard error of estimate and limit of detection. The results obtained validate the satisfactory performance of the system in monitoring soil nutrients and the promising future application in precision agriculture and site-specific crop management systems.

Effectiveness of Trichoderma harzianum in soil and yield conservation of tomato crops under saline irrigation

Protected horticultural crops in the Mediterranean region are typically under deficit irrigation and intensive cultivation practices and must cope with poor irrigation and soil quality due to salinization. The effects of variable irrigation water quality and use of the beneficial fungus Trichoderma harzianum on the evolution of soil salinization and yield during a single cropping season are examined at a small-scale Solanum lycopersicum L. cv Elpida greenhouse experiment. The experiment simulates typical coastal Mediterranean greenhouse cultivation conditions of the RECARE Project soil salinization Case Study in Greece (Timpaki basin in Crete). Local NaCl-free but highly calcareous planting soil as well as local cultivation practices were used to replicate prevailing conditions at the Case Study. Tomato plants were drip irrigated with NaCl solutions of low (L) (ECw = 1.1 dS m−1) and high (H) (ECw = 3.5 dS m−1) concentration to emulate a typical “good quality” and “marginal quality” irrigation water, respectively. T. harzianum (T) was selectively applied resulting in a total of 2 treatments colonized with the fungus (LT, HT) and two not (N) colonized (LN, HN). For high salinity irrigation treatments HN and HT, sodium adsorption ratio (SAR) values settled at 22.2 and 13.4, respectively, showing that T. harzianum reduced the effect salinity significantly. Monitoring of soil nutrients showed a significant decrease of P-Olsen in non-T. harzianum treatments versus no change in P-Olsen in T. harzianum treatments. Final total and marketable tomato yield for treatment HN were reduced compared to LN by 28% and 42%, respectively, with in T. harzianum treatments having no significant effect. Fruit quality characteristics were overall less sensitive to higher irrigation salinity than to timing of harvest. We conclude that, under high salinity irrigation, an early harvest and termination of the cultivation has no significant impact on tomato yield while obviating pressure on soil resources and conserving agricultural input.

Degradation of soil nutrients and slow recovery of biomass following shifting cultivation in the heath forests of Sarawak, Malaysia

Heath forests which are tropical forests on sandy soils are widely distributed in Borneo and provide many ecosystem services, such as carbon storage and non-timber forest products. Over the past several decades, such forests have been disturbed by non-traditional shifting cultivation, which is usually conducted in unsuitable land with short fallow duration. Anthropogenic disturbances in forests growing on sandy soils that have low nutrient retention capacities may promote further reductions in soil fertility. Long-term monitoring of soil nutrients and biomass accumulation is rare in degraded tropical rainforests growing on sandy soils despite the known negative effects of non-traditional shifting cultivation practices on soil fertility, vegetation and biomass recovery, and the growth of trees planted to rehabilitate forests. The objective of the current study was therefore to elucidate changes in soil fertility and biomass recovery potential in degraded forests on sandy soils in Borneo. We monitored soil nutrients and chemical properties in fifty-four 12 × 12 m plots located on different topographical positions along upper and lower slopes. Samples were collected in plots aged 7 and 14 years after abandonment of shifting cultivation. The biomass of secondary forest trees in all plots 12 years after the abandonment was also measured to determine the relationship between biomass accumulation and changes in soil nutrients. We found that soil pH and cation exchange capacity, and the concentrations of most nutrients, including nitrogen, magnesium, and phosphorus, had decreased significantly 7–14 years after abandonment; biomass accumulation in the plots was also limited 12 years after abandonment (<0.8 Mg ha−1 year−1). These changes in soil traits within the study plots were similar regardless of topographical position, and the changes were not related to the amount of biomass. Soil nutrients in the plots may have leached out as a result of removal of thick root mats in the surface soil, high sand content, and large amounts of rainfall in the area rather than uptake by recovering trees. These results indicate that it may be difficult to recover soil fertility on steep slopes in sandy soil conditions because of high leaching rates and erosion when the soil surface layer is destroyed by shifting cultivation. It is therefore important to carefully manage shifting cultivation practices in tropical forests on sandy soils in Borneo.

Piezoresistive microcantilever based lab-on-a-chip system for detection of macronutrients in the soil

Monitoring of soil nutrients is very important in precision agriculture. In this paper, we have demonstrated a micro electro mechanical system based lab-on-a-chip system for detection of various soil macronutrients which are available in ionic form K+, NO3−, and H2PO4−. These sensors are highly sensitive piezoresistive silicon microcantilevers coated with a polymer matrix containing methyltridodecylammonium nitrate ionophore/ nitrate ionophore VI for nitrate sensing, 18-crown-6 ether for potassium sensing and Tributyltin chloride for phosphate detection. A complete lab-on-a-chip system integrating a highly sensitive current excited Wheatstone’s bridge based portable electronic setup along with arrays of microcantilever devices mounted on a printed circuit board with a liquid flow cell for on the site experimentation for soil test has been demonstrated.

In Situ Soil Phosphorus Monitoring Probe Compared with Conventional Extraction Procedures

In this work, selective chemical sensors of phosphorus (PO4 3−) installed in PVC probes and their associated instrumentation were evaluated in soil solution phosphorous monitoring. The evaluation was carried out with the addition of a 0.1 mol L−1 P‐PO4 3− solution in the soil, followed by data acquisition supplied by the probes; by collecting soil samples in the region where the probes were installed; and by phosphorus determination through conventional laboratory techniques. The phosphorus amounts were determined by spectrophotometry after the following extraction methodologies: Mehlich 1, Mehlich 3, and ionic exchange resin. The results, compared with the potentials registered by the probes, express the best correlation with the results obtained with the resin method. The results indicate good response of the sensors and the potential applicability of these probes to assist in the monitoring of soil nutrients, helping to establish rational processes in the use of fertilizers in crops.

Ecological and agro-economic study of small farms in sub-Saharan Africa

Land degradation, rising population and poverty in sub-Saharan Africa threatens the agricultural sustainability and productivity, quality of the environment and socio-economic wellbeing of rural populations. We studied farm ecological, economic and social sustainability, productivity and production risks in the Mbeere District of Eastern Kenya. We used a soil nutrient monitoring methodology to collect data from 30 households. Ecological sustainability was threatened by soil nutrient decline at rates of 1.7 kg P and 5.4 kg K ha−1 half year−1 while N was nearly balanced in soils. Soil phosphorus and potassium stocks, in the cultivated soils, declined at rates of 0.3% and 0.1% half year−1, respectively. Farm economic returns were positive, albeit low, and could not sustain the livelihoods of the households. All the 30 households were living below the poverty line of 1 US dollar a day. Farm productivity was low, with livestock and yields of major staple food crops below on-farm target yields. To spread out the risks of production, farming households were cultivating an average of 4.7 crop fields, keeping more than two types of livestock and practising intercropping systems. Intercropping maize-beans reduced nutrient decline and raised household incomes compared with monocropping of either of the two crops. Despite the low rates of nutrient decline, high risks of production and the low crop yields, the livestock productivity and farm economic performance put the sustainability of these farming systems into question. The low levels of nutrient decline in small farms averaging at 1.7 kg P and 5.4 kg K ha−1 half year−1 contrasts with the high nutrient depletion rates on macro-scale levels, e.g. 20–40 N, 3.5–6.6 kg P and 20–40 kg K ha−1 year−1 for Eastern African countries and 22 kg N, 2.5 kg P and 15 kg K ha−1 year−1 for sub-Saharan Africa. These findings indicate that the extent of nutrient decline and conservation differs across sub-Saharan Africa. The positive contribution of intercropping to nutrient balances suggests the need to encourage farmers to adopt such systems rather than monocropping.