查看更多>>摘要：? 2022Sustainably increasing organic vegetable crop productivity is needed to meet growing demands, considering replacement of conventional animal manures with alternative fertilizers. We investigated the effects of intercropping (IC) and different organic fertilization strategies, and their interactions, on the plant-soil system. A 2-year IC field experiment with white cabbage and beetroot was conducted with two compost-supplemented fertilization strategies (animal-based AF+C; plant-based PF+C) and one control with pig slurry (CONT). Root growth was measured with the minirhizotron method. Overall productivity of intercropping (IC) was lower or similar to that of monocropping (MC) systems with a land equivalent ratio of 0.8 in 2018 and 1.0 in 2019. IC affected rooting intensity in only few soil layers: at harvest (2018), beetroot IC had higher rooting intensity compared to beetroot MC in 0.25–0.75 m soil layer. Mycorrhizal colonization of beetroot roots was increased by 37 % under IC. CONT crops had the highest yield and nitrogen (N) accumulation in 2018. In 2019, yield, N and phosphorous (P) accumulation and soil enzyme activity were higher in the PF+C and CONT conditions than with AF+C. Potential N mineralization was 24–37 % higher under PF+C compared to CONT and AF+C, whereas hot water extractable P was highest under animal-based fertilization strategies (CONT: 8.66 mg kg?1, AF+C: 8.56 mg kg?1) compared to PF+C: 7.99 mg kg?1. Benefits of productivity and N-use-efficiency from complementary root growth and resource use were not found in cabbage-beetroot IC. Instead, displacement of sowing/planting dates in the second year decided the dominating species, supported by mycorrhiza in beetroot. This management practice reduced the level of competition and increased the overall productivity of the IC system compared to 2018. The plant-based fertilization strategy had higher soil fertility as indicated by potential N mineralization and similar P use efficiency and can replace pig slurry. The methods of IC and fertilization strategy interacted only on potential N mineralization. Long-term improvements are expected with compost-supplemented fertilization strategies owing to their high organic carbon and N inputs.
查看更多>>摘要：? 2022 Elsevier B.V.Present studies have shown that near-infrared spectroscopy (NIRS) could be used to identify the producing area of apple. However, we still do not know whether the producing area affects the optical properties of apple, whether it affects the relationship between optical properties and internal qualities, and whether the optical parameters could be used to predict the apple-producing area. To answer these questions, the apples produced in three areas with different temperatures, precipitations, and altitudes in the Loess Plateau region, China, were used as samples to obtain the optical properties of apple pulp by a single integrating sphere system, analyze the differences in optical properties of apples produced in different areas, analyze the correlations between optical properties (absorption coefficient (μa) and reduced scattering coefficient (μs')) and internal quality indices (soluble solids content (SSC), moisture content and firmness), and investigate the feasibility of discriminating the apples produced in different areas and predicting the internal qualities using NIRS. The results showed that the apples produced in Luochuan had the highest SSC while Yangling apples had the highest moisture content. The μa had three absorption peaks at around 985, 1200, and 1430 nm, and the μs' of apples from three areas showed a similar trend with wavelength. The best correlation of μa with SSC and moisture content was found in Yangling apples with a correlation coefficient of ?0.90 and 0.79, respectively. The built linear discriminant analysis based on μa spectra performed better in discriminating producing area. The established partial least squares regression models based on μa spectra had the best prediction performance for SSC and moisture content, while the model built with μs' had the best prediction performance for firmness. This study is helpful to understand the differences in optical property of ‘Fuji’ apple produced in different areas and offers information for identifying the producing area of fruit using NIRS technology.
查看更多>>摘要：? 2022 Elsevier B.V.Understanding the components that shape the rhizosphere community is vital for sustainable disease management. This study evaluated an integrated Verticillium wilt management in eggplant and its influence on the soil microbiome. Six treatments; Self-rooted (control; CLA) and sole grafted (CLB) eggplants, Brassica + Self-rooted plant (BrA), and Brassica + Grafted plants (BrB), with Biochar (10 t/ha) + Brassica + Self-rooted plant (BBrA) and Biochar (10 t/ha) + Brassica + Grafted Plant (BBrB) were used. Soil microbiome was characterized using high-throughput sequencing. The grafted treatments significantly reduced the Verticillium abundance, disease index and improved the yield of eggplant compared with CLA (18.13 t/ha), with BBrB (41.54 t/ha) as the best treatment. Results showed that treatments CLB, BrB, and BBrB stimulated more beneficial microbes, especially Arthrobacter, Bacillus, and Sphingomonas for bacteria; and Mortierella, Tausonia, and Chaetomium for fungi. Treatment BBrB was biomarked by phylum Chloroflexi (o_SBR1031), Acidobacteria, Planctomycetes, and Patescibacteria, but only Chloroflexi (o_SBR1031) was found in BrB, and none of them in CLB and treatment BBrB also contained more biomarkers than other treatments. Similarly, the Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) analysis revealed that treatment BBrB contained more genes (17.5%) regulating disease resistance followed by BrB (17.3%) and CLB (16.6%) treatments. In conclusion, grafting with Brassica (biofumigation) under a biochar regime could reduce eggplant Verticillium wilt. This study expands knowledge on how soil microbiota can be enhanced using integrated disease management practices to exploit sustainable food production.
查看更多>>摘要：? 2022 The AuthorsThe warming of the climate and shrinking freshwater resources pose serious challenges to European agriculture. Meeting these challenges demands a thorough knowledge of the major trends in soil moisture patterns across the continent over time. Charting the available soil water (ASW) content (m3 m-3) derived from the ERA5 Land dataset in grid cells of 0.1° × 0.1°, the highest values occurred in the Alpine, Baltic and West Balkan countries, as well as in North Western Europe. However, a major part of the Mediterranean and the Carpathian-Balkan regions and Eastern Europe recorded the driest soils over recent decades. The annual average ASW decreased over almost the entire continent from 1981 to 2007, but to the greatest degree in Eastern Europe, while Northern Europe suffered least of all. For the summer half of the year, the available water content of the top 28 cm soil significantly decreased in 45.5 % of European croplands, while only 1.0% showed a significant moisture increase. Summer half-year moisture declined across almost the entirety of Eastern Europe, threatening the reproductive stage of wheat and maize vegetation period. Soil water content had a significant positive impact on wheat yields in an estimated 64.3 % of European wheat fields, and a negative one in 5.7 %. In the case of maize yields the positive impact of ASW was present in an estimated 89.4 % of maize-growing areas, explaining an estimated 46–72 % of maize yield variances in the majority of top European maize-producing countries. In contrast to wheat, negative soil water content impact for maize in the continent was not observed. Significant ASW - wheat and ASW - maize yield relationships were found with decreasing summer half year ASW in 32.0 % and 35.2 % of European croplands, respectively. The coexistence of the crop yield dependence on soil moisture and the decrease in available soil water content pose a considerable threat to grain production stability over extensive regions of Eastern and Western Europe. These warning signs call for an effective intervention on behalf of soil water conservation in European croplands.
查看更多>>摘要：? 2022 Elsevier B.V.Cotton (Gossypium hirsutum L.) yield is decreased under low radiation, but there are few reports on possible interactions of N fertilizer application and light limitation on cotton production. The objective of this work was to evaluate growth, yield components, and boll distribution in cotton as affected by N rates under light restriction. Three experiments were conducted for two years in Central (Primavera do Leste and Chapad?o do Sul) and Southeastern (Itapeva) Brazil. Cotton plants were shaded at early flowering to a 42 % reduction in global radiation for 16–25 days. Four N rates were used in Primavera do Leste and Itapeva; and three N rates and two genotypes, an early- (FM 906GLT) and a late-maturing (FM 983GLT) cultivar, were used in Chapad?o do Sul. Shading decreased lint yield by 10 % in Primavera do Leste and by 12 % in Chapad?o due to 24 % and 32 % reduction in boll number at the lower third of the plant, respectively. In Itapeva, the number of bolls at the lower fruiting branches was decreased 19% by shading, but a 10% lint yield reduction was observed only with 35 kg ha?1 of N. As to the main effects, lint yield and number of bolls increased with N rates up to 155, 142 and 105 kg ha?1, depending on the site. Lint yield of shaded plants was more responsive to higher N rates, which also increased plant height, number of bolls and the main stem node number of the last fruiting branch. Cotton cultivars had similar lint yields despite differences in boll distribution. At lower fruiting branches, the early-maturing cultivar showed an average boll number 59 % higher, but the late one produced 81 % and 63 % more bolls on the upper branches at 105 and 185 kg ha?1 of N, respectively. We concluded that N-deficiency inhibited the recovery of cotton from losses caused by shading, whereas a high-N availability minimizes damages after shading during blooming.
查看更多>>摘要：? 2022 The AuthorsThe intensification of agricultural systems has caused a noticeable impact on agro-ecosystem services. Thus, the adoption of more sustainable agricultural practices such as crop diversification and reduction of external inputs represent an alternative strategy to minimize the impacts of intensive agricultural systems to the environment. This study aimed at evaluating the effects of crop rotation, conservation tillage, and low-input strategies on soil quality and farming performance using a set of 7 indicators based on a fuzzy logic approach. Data were collected from three Mediterranean long-term field experiments (LTEs) mostly oriented on cereal-based and vegetables cropping systems, located in Spain and Italy. The selected agro-environmental indicators clearly discriminated both from a geographical point of view and between monoculture and diversification, showing their suitability for the evaluation of diversified cropping systems. Such indicators highlighted that implementing crop diversification and reducing soil disturbance and chemical inputs enhanced soil quality. In this context, the most significant effects of diversified cropping strategies were the increase of crucial variables such as soil organic carbon (SOC), total nitrogen (TN), available phosphorus (Pav), and bulk density (BD) maintaining a stability of yields in all the three LTEs. These results provide strong evidence for the benefits of crop diversification in Mediterranean areas, highlighting that diversification represents a very promising strategy for more sustainable land management. Simple and composite indicators calculated using fuzzy method can be proposed as tool to assess the effects of diversification strategies on cropping systems performance. This approach can be used to define local solutions to help the re-design of cropping system through crop diversification transition across Europe.
查看更多>>摘要：? 2022 Elsevier B.V.Fruit tree orchards are an important land-use type in the Mediterranean regions despite limited information on their potential role as carbon sinks to mitigate climate change and their capacity to store soil organic carbon (SOC). The objective of this study was to evaluate the ability of peach orchards (Prunus persica (L.) Batsch) to fix and accumulate carbon (C) in three contrasting management systems. The first system was representative of the current management recommended to French producers with high yield objectives (REF). The second system was managed with a Low-Input strategy (LI-1) for chemical pesticide application (?70%), nitrogen fertilization and water irrigation (~?25%). Lastly, the third system (LI-2) had the same low-input strategy but included a higher planting density (~2-fold) and a new tree shape training system. The experiment was conducted in the South of France for 7 years from planting (2013–2019). The aboveground biomass and C repartitions in various components of systems (tree organs and grass growing in alleys) were carried out by destructive measurements each year to determine Net Primary Production (NPP), Net Ecosystem Production (NEP) and Net Ecosystem Carbon Balance (NECB). The REF system had very high productivity during the mature tree period with 45.9 Mg ha-1 yr-1 of fresh fruit yield and 16.8 Mg ha-1 yr-1 of aboveground biomass, corresponding to 7379 kg C ha-1 yr-1 (738 g C m-2 yr-1). Orchard NPP (tree and grass) reached 11,003 ± 353 kg C ha-1 yr-1 (1100 ± 35 g C m-2 yr-1) and soil respiration was 3366 ± 776 kg C ha-1 yr-1 (337 ± 78 g C m-2 yr-1) leading to an NEP of 7637 ± 853 kg C ha-1 yr-1 (764 ± 85 g C m-2 yr-1) and an NECB of 4919 ± 858 kg C ha-1 yr-1 (492 ± 86 g C m-2 yr-1). Carbon accumulation was distributed 53% in perennial biomass, and the soil had an annual SOC stock change of 3.8‰. In the LI-system, the reduction of inputs and chemical pesticides did not impact the average NEP and NECB, even though pest infestations reduced biomass in 2015 and 2019. The same input reductions in the LI-2 system but with increased planting density provided significant increases in NPP (+10.5%) and NEP (+20.0%), leading to an NECB of 5876 ± 890 kg C ha-1 yr-1 (588 ± 89 g C m-2 yr-1), or 19.4% greater than the REF system during the mature tree period. This positive C accumulation was distributed 46% in the perennial biomass, which could reach 35.5 Mg C ha-1 (3550 g C m-2) after 15 years of orchard life. The SOC stock change was 10.0‰ in the LI-2 system, greater than the 4‰ initiative of the Paris COP21. Innovative peach orchards with agroecological management can mitigate environmental impacts by combining high-quality fruit production with enhanced CO2 sink capacity objectives.
查看更多>>摘要：? 2022 The AuthorsEfficient irrigation in viticulture requires objective and representative monitoring of the vineyard water status variability. In this work the combination of multispectral, environmental and thermal data (using an infrared radiometer) acquired simultaneously on-the-go (at midday), from a ground moving vehicle (moving at 3 km/h) was tested to assess the vineyard stem water potential (Ψs) and its spatial variability (three different irrigation treatments were imposed) over two seasons in north Spain. Partial least squares (PLS) cross-validation regression models involving the canopy temperature (Tc), environmental and spectral variables yielded determination coefficients (R2cv) of ~ 0.63 and root mean square error of cross-validation (RMSECV) between 0.124 MPa and 0.206 MPa in the two seasons. Linear discriminant analysis (LDA) involving only the variables used to build the regression models was run to distinguish among low, medium and high water stressed vines, yielding an average percentage of correct classification samples of 74%. The satisfactory performance of the multivariate models involving thermal, environmental and spectral data to either estimate or classify the plant water status within a vineyard supports the approach towards the combination of different data source to improve the capabilities of thermography itself. The inclusion of vegetative spectral indices in the regression and classification models of grapevine water status may provide real-time feedback on grapevine water use as influenced by actual vegetative growth, abiotic and/or biotic stress patterns. This combined approach can be seen as an advancement from existing solutions to assess plant water status variability given the simplicity and potential to automation of the thermal sensor employed and the integration of environmental and canopy vigour data into the model.
查看更多>>摘要：? 2022 Elsevier B.V.The vertical leaf nitrogen (N) distribution in summer maize is believed to be an important adaptive reaction to crop physiology and ecosystem functions. Therefore, it is of great significance to understand the vertical characteristics of leaf N concentration (LNC) across summer maize canopies for crop growth and production. However, the effect of vertical canopy position on LNC and subsequently leaf hyperspectral characteristics of the entire spectrum (350–2500 nm) for summer maize is poorly understood. The purpose of this work was to quantitatively study the effects of the N nutrition on vertical distribution of LNC, identify the sensitive layer and effective wavelength of leaves, and establish a in situ leaf spectrum monitoring model considering vertical distribution of LNC. Six N field trials were conducted for four consecutive years (2017–2020). In addition, the data of 30 farmers' conventional farmland management in 2020 were collected to check the robustness of the constructed optimal estimation model for LNC prediction. Leaf spectral measurements together with LNC were studied at three vertical leaf positions on the crop stem: upper, middle and lower. Spectral reflectance was processed by continuous wavelet transform (CWT); partial least square (PLS) was used to analyze the relationships between LNC of different layers and spectral reflectance. Field sampling indicated that LNC had a vertical distribution pattern and an evident decline from the upper to lower layer. CWT technique can significantly increase the prediction accuracy of LNC at different layers, and the best decomposition scale is CWT-1. The CWT-1-PLS model for predicting vertical LNC distribution had achieved relatively higher accuracy than that based on the full range of the raw hyperspectral reflectance (R), the LNC determination coefficient (R2val) of the validation dataset was 0.832, 0.857 and 0.811 for the upper, middle and lower layer, and the relative percentage deviations (RPDval) were 2.444, 2.432, and 2.181, respectively. Eventually, ten bands were selected as the effective wavelengths for predicting the vertical LNC distribution in the upper, middle and lower layer, respectively. Newly developed CWT-1-PLS model using the effective wavelengths for LNC prediction in different layers also performed well (RPDval>2.0) based on the field experiments validation. Moreover, the validation at the farmers’ fields also showed fine precision for upper (RPDval=2.012), middle (RPDval=2.137) and lower (RPDval=1.881) layer LNC prediction. These results are of great significance for the study of summer maize leaf reflectance modelling, especially for the studies of integrating hyperspectral measurements and leaf traits data.
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