Petiole NO3 – , an indicator of recent N status in conventionally-produced vegetables, was measured in the most recently-matured leaves. Petiole NO3 – changes rapidly with growth stage, so the data are graphed by post-transplanting growing degree day to account for phenological differences among fields as a result of slightly different sampling times relative to transplanting.Root RNA was extracted using Trizol reagent according to the manufacturer’s guidelines followed by DNase digestion using RQ1 RNase-free DNase . Total RNA was purified using the RNeasy Plant Mini Kit . RNA concentrations and quality were assessed using the Agilent Nanodrop and the RNA 6000 Nano Assay . Only RNA samples with RNA integrity numbers of at least 7.0 were used for subsequent analyses. These RNA were used for cDNA synthesis for qRT-PCR analysis. cDNA was synthesized from 0.5 μg DNase-treated total RNA using the Superscript III kit . Quantitative real-time RT-PCR was performed as described in previous work , using the primer pairs tested and reported therein and using a Step OnePlus Real-Time PCR system . Seven key genes involved in root N uptake and assimilation that had previously been shown to be responsive to an N pulse in an organic soil were assessed: high-affinity NH4 + transporters AMT1.1 and AMT1.2 ; high-affinity NO3 – transporter NRT2.1 ; nitrite reductase Nii ; cytosolic and plastidic glutamine synthetases GS1 and GS2 ; and NADH-dependent glutamate synthase NADHGOGAT . The tomato actin and ubiquitin genes were used as reference control genes as they did not exhibit differential expression among N treatments in previous field experiments. Relative expression was analyzed according to the ΔΔCT method with multiple reference control genes and using inter-run calibration.Means for variables in all tables, figures,strawberry gutter system and the text are expressed with 95% confidence intervals .

CIs can assist with means comparisons based on the “inference by eye” method. Roughly, 95% CIs that overlap with another mean are not different but when the overlap of intervals is no more than half of one interval arm, then the means are different at p  0.05. Intervals that barely touch are significant at p  0.01 and intervals that are separated by at least half of one interval arm are different at p  0.001. Soil NH4 + and NO3 – showed positive skewing and thus were log transformed prior to calculation of means and CIs. Back-transformed means and 95% CIs are shown for these variables. Fields were clustered based on 28 plant, soil, and microbial variables using the k-means method implemented in R. The optimal number of groups chosen was based on the Calinski-Harabasz criterion and by examining sums of squared error scree plots. F-statistics were calculated for each variable based on their cluster grouping to assess the relative magnitude of the “cluster effect”, i.e. higher F-statistics indicate more differentiation among clusters for a given variable.The 13 organically-managed Roma-type tomato fields spanned a three-fold range of soil C and N and had similar soil texture, soil types, and soil pH . Field numbers are in order of increasing total soil C. Variation in nutrient inputs, including highly-labile secondary inputs indicated diverse and intensive organic management strategies across these farms . The 13 fields encompassed the majority of the variation in the focal landscape , i.e. all but one of the five clusters, or landscape types, identified by GIS and multivariate analysis were represented . Thus, a range of soil characteristics representative of this region was accounted for by the fields sampled. Other characteristics, such as the low number of crop rotation types differed little across the clusters and reflect the intensity of agricultural management in this region.Measures of tomato N sufficiency varied widely across the 13 organic fields, ranging from deficient to luxury N levels.

Total above ground N concentration at mid-season overlapped or fell slightly below the critical N concentration for processing tomatoes in most fields , with N concentrations between 2.5 and 3.5% . Exceptions were fields 1 and 2 which were markedly lower and field 4, which was higher . The same general pattern occurred for the harvest sampling. Petiole NO3 – concentration in four fields overlapped the sufficient concentration, based on published guidelines , while five fell below it, and four rose above it . Petiole NO3 – was especially high in field 4. Petiole NO3 – -N showed a broadly similar pattern to total above ground N concentration, as reflected in the strong linear relationship between them . At the mid-season sampling, shoot δ15N ranged from 4.22 ± 0.65‰ in field 10 to 13.29 ± 1.18‰ in field 6. Fields 3, 4, 6, and 9 had the highest shoot δ15N, all above 12‰, and all but field 3 used seabird guano. Fields 8, 10, 11, and 13 had the lowest shoot δ15N, close to 4‰, and all but field 8 used Chilean nitrate. Mean harvestable fruit yield across all 13 fields was 86.7 ± 7.2 Mg ha-1 and was similar to the overall Yolo County mean 2011 tomato yield , which included both conventional and organic fields . Field 4 had the highest yield overall followed closely by field 9 , and field 1 had the lowest . Nine of 13 fields had means higher than the county average, and six of these fields were significantly higher. There was also substantial variability in tomato above ground biomass and N content at harvest across fields , which largely reflected the pattern of fresh weight yields. For instance, total above ground N ranged from 64 kg N ha-1 in field 1 to 243 kg N ha-1 in field 4 with a mean across all fields of 154 kg ha-1.Expression of cytosolic glutamine synthetase GS1 in roots was more strongly related to indicators of plant-soil N cycling than were the other six key genes involved in root N metabolism . Of the soil variables, GS1 was more strongly related to soil bio-assays for N availability than to inorganic N pools .

Microbial biomass N and PMN were most strongly associated with expression of GS1 in roots, followed by soil NO3 – . Permanganate oxidizable C and MBC, both indicators of labile soil C pools, also had significant associations with GS1 expression in roots, but soil NH4 + did not. Expression of GS1 also was positively associated with shoot N and petiole NO3 – , as was glutamate synthase NADH-GOGAT. Inclusion of GWC as a covariate in multiple linear regression models improved the proportion of explained variation in GS1 expression .PCA of 28 indicators of yield and plant nutrient status, root N metabolism, and soil C and N cycling showed strong relationships among suites of variables, which clearly differentiated fields along the first two principal components . The first principal component explained 28.3% of the variation; on the left side of the biplot are higher values of most variables, including yield, soil bio-assays, expression of root GS1 and NADH-GOGAT, and labile and total soil C and N pools . Soil NH4 + and NO3 – concentrations from all three sampling times as well as AMT1.2 were associated with one another and with positive values along principal component 2, which explained 19.4% of the variation. Total soil C and N were strongly associated with EOC and EON,hydroponic fodder system the soil C:N ratio, and POXC. These variables had negative values along axis 2 and thus contrasted with the pattern of soil inorganic N. Weak loading of AMT1.1, NRT2.1, Nii, and GS2 on the first two principal components reflects the lack of association of expression levels of these genes with bio-geochemical and plant variables. Non-overlapping confidence ellipses for seven out of 13 fields on the PCA biplot indicated distinct N cycling patterns . Fields 1 and 2, with the highest values along axis 1, had low values of all variables included in the analysis. Field 4 had the highest values along axis 2 corresponding with higher soil NH4 + and NO3 – . Fields 10, 11, 12, and 13 were associated with high values of labile and total soil C and N. Overlapping confidence ellipses of fields 3, 5, 6, 7, 8, and 9 close to the origin indicate similar, moderate values of this suite of variables for these fields. Three groups of fields were identified by k-means cluster analysis of the same 28 variables included in the PCA . Group 1 included fields 1 and 2, which had low mean values for yield , the lowest mean soil C and N and soil inorganic N pools , and the lowest mean value of GS1 relative expression in roots. Groups 2 and 3 had similarly higher mean yield , shoot N, and petiole NO3 – than group 1, but these two groups differed substantially in their soil C and N pools. Group 2 had higher soil NH4 + and NO3 – pools as well as root expression of AMT1.2 while group 3 had higher total and labile soil C pools. Expression of GS1 was similar in both groups. Based on the relative magnitude of F-statistics calculated for each variable, soil C and N, EOC, EON, shoot N, and soil NO3 – at transplant and anthesis were most strongly differentiated across the three groups. The high F-statistics of AMT1.2 and GS1 relative to other N metabolism genes indicate that root expression of these genes are most responsive to soil N cycling.This study confirms that working organic farms can produce high yields with tightly-coupled N cycling that minimizes the potential for N losses.

Such farms had the highest soil C and N and used high C:N organic matter inputs coupled with labile N inputs that resulted in high soil biological activity, low soil inorganic N pools, high expression for a root N assimilation gene, adequate plant N, and high yields. Organic systems trials have previously shown crop N deficiencies that lead to less-than-ideal crop productivity; losses of N when Navailability is poorly synchronized with crop N demand; or alternatively, that organic production can reduce N losses. But how working organic farms achieve yields competitive with high-input conventional production with low potential for N losses has not been demonstrated. Elevated expression of a key gene involved in root N assimilation, cytosolic glutamine synthetase GS1, in fields with tightly coupled N cycling confirmed that plant N assimilation was high when plant-soil-microbe N cycling was rapid and inorganic N pools were low, thus showing potential as a novel indicator of N availability to plants. Improving biologically-based farming systems will benefit from research that uses novel tools to uncover innovations happening on farms, especially if the research process helps facilitate knowledge exchange among farmers and researchers.To characterize the substantial variation in crop yield, plant-soil N cycling, and root gene expression across 13 fields growing the same crop on similar soil types, we propose three N cycling scenarios: “tightly-coupled N cycling”, “N surplus”, and “N deficient”. Values of indicator variables suggest differing levels of provisioning, regulating, and supporting ecosystem services in each scenario . Fields in group 3 show evidence of tightly-coupled plant-soil N cycling, a desirable scenario in which crop productivity is supported by adequate N availability but low potential for N loss. Despite consistently low soil NO3 – pools in these fields, well below the critical mid-season level for conventional processing tomatoes in California, total above ground N concentrations were very close to or only slightly below the critical N concentration for processing tomatoes. Tomato yields were also above the county average . This discrepancy between low soil inorganic N pool sizes and adequate tomato N status is due to N pools that were turning over rapidly as a result of efficient N management, high soil microbial activity, and rapid plant N uptake. Composted yard waste inputs with relatively high C:N ratios in concert with limited use of labile organic fertilizers applied during peak plant N demand provided organic matter inputs with a range of N availability. A companion study showed how high potential activities of N-cycling soil enzymes but lower activities of C-cycling enzymes in this set of fields reflect an abundant supply of C but N limitation for the microbial community, thus stimulating production of microbial enzymes to mineralize N. Plant roots can effectively compete with microbes for this mineralized N, especially over time and when plant N demand is high.