Agronomy Journal

doi: 10.1002/agj2.20734pmid: N/A

Rastegari, Faramarz; Tohidinejad, Enayatollah; Mohammadi‐Nejad, Ghasem

doi: 10.1002/agj2.20843pmid: N/A

Indigo (Indigoferatinctoria L.), as a forgotten crop, has immense industrial and medicinal value. In this research, the effect of sowing date on the leaf, seed, and dye yield of indigo was examined at Jiroft, Iran, during the 2013 and 2014 growing seasons. The experiment was arranged as a split‐plot based on a randomized complete block design with three replications. Planting dates (5 May, 20 May, and 5 June) and indigo ecotypes as landraces of Jiroft, Roudbar, Rigan, and Ghale‐ganj were considered as main and subplots, respectively, aiming to evaluate their effects on pod number/plant, 1,000‐seed weight, seed number/pod, leaf dry weight, seed yield, as well as indigo dye percentage and yield. The results indicated that the indigo content was greater at the second sowing date (0.68%) than the first (0.66%) and third (0.65%) dates. Further, the indigo percentage was greater in Jiroft and Roudbar ecotypes compared with Rigan and Ghale‐ganj. Seed yield at the second and third sowing dates significantly increased (560.3 kg ha–1) and reduced (188.4 kg ha–1), respectively, compared with the first sowing date (261.4 kg ha–1). Furthermore, the highest value of leaf dry weight, indigo yield, and seed yield were obtained from the Jiroft ecotype at the second sowing date; in contrast, the lowest of these parameters were recorded in the Ghale‐ganj ecotype at the latest sowing date. Moreover, the genetic diversity of ecotypes was studied using the amplified fragment length polymorphism (AFLP) marker. Based on the dendrogram, the four ecotypes of indigo were divided into three groups; thus, Jiroft and Rudbar, geographically close to each other and almost the same, were in one group, and Reagan and Ghale‐Ganj were in separate groups. Overall, based on this research results, Jiroft and 20 May could be suggested as the best ecotype and sowing date of indigo for the examined region. Obtained results can also be useful for expanding and facilitating the cultivation of neglected plants.

Casagrande, Cleiton Renato; Sant'ana, Gustavo César; Meda, Anderson Rotter; Garcia, Alexandre; Souza Carneiro, Pedro Crescêncio; Nardino, Maicon; Borem, Aluizio

doi: 10.1002/agj2.21047pmid: N/A

Identifying agronomic traits correlated to grain yield can be very useful for soybean [Glycine max (L.) Merr.] breeding, especially if these traits can be measured through unmanned aerial vehicle high‐throughput phenotyping rather than through manual measurements. The objective of the present study was to assess the association between canopy coverage and soybean grain yield through different statistical methodologies. A panel with 97 soybean genotypes was evaluated in two field experiments conducted in Paraná State, Brazil. Canopy coverage was determined by using an RGB camera coupled to a drone. Images taken during flights at phenological stages V3‐V4, V5‐V6, V7‐V8, and V9‐R1 were used to calculate canopy coverage based on the green pixel ratio in each experimental unit. There were significant genotype × environment interactions in all evaluated traits. Selective accuracy values (0.73–0.96) revealed indirect yield selection efficiency based on canopy coverage. High genetic correlation estimates (0.76) were observed between grain yield and canopy coverage at flowering in one of the assessed environments. These results were confirmed through genetic correlation coefficient decomposition in direct and indirect effects and of gain estimates presenting indirect selection. Thus, canopy coverage data remotely collected using drones to soybean indirect selection for grain yield can be a promising strategy to accelerate genetic gains in soybean breeding programs.

Liu, Shi‐hui; Wu, Qiu‐yun; Xu, Ting; Wang, Hui‐cong; Wang, Jun‐wei; Zhang, Zhong‐Lin; Liu, Ming‐yue; Huang, Ke

doi: 10.1002/agj2.21065pmid: N/A

Chinese broccoli [Brassica oleracea var. alboglabra (L. H. Bailey) Musil] is an annual herbaceous healthy vegetable plant mainly cultivated in southern China. Previous studies have been primarily focused on investigating the nutritional ingredients of this plant, little is known about its medicinal potentials. Here we report the profiling of sulforaphane, an active ingredient with potent anticancer activities, in 47 Chinese broccoli germplasms collected from China and some southeast‐Asian countries. High‐performance liquid chromatography technology was used to systemically quantify the sulforaphane content in leaf, stem, and flower bud clusters of all 47 Chinese broccoli germplasms. The results indicated a diverse distribution pattern of sulforaphane among different tissues. Flower bud contained the highest average of sulforaphane, roughly twice as much as in leaf and stem tissues. Interestingly, different germplasms exhibited great differences in terms of sulforaphane abundance. Germplasm BOK15‐20 is extremely rich in sulforaphane in all tissues tested, ∼2,500 times of BOK15‐15 in leaf, 66 times of BOK15‐42 in the stem, and 77 times of BOK15‐40 in flower bud. The tremendous disparity of sulforaphane content among different germplasms suggests considerable variations in germplasms’ medicinal potentials. In addition, we systemically characterized a series of morphological and phenotypic traits of all 47 Chinese broccoli germplasms. Cluster analysis through NTSYSpc v2.2 showed that the 47 germplasms were classified into five different groups, respectively, based on sulforaphane content and qualitative phenotypic traits. Our results not only confirmed the medicinal values of Chinese broccoli but also provided crucial information that will eventually benefit future germplasm development and new variety breeding.

Burton, Amanda B.; Kemanian, Armen R.

doi: 10.1002/agj2.21006pmid: N/A

Maize (Zea mays L.) silage is an important source of feed for ruminant animals. However, maize monocultures are exposed to both abiotic and biotic stresses that can reduce yield and contribute to environmental degradation. Over the past century, maize + soy [Glycine max (L.) Merr.] polycultures gained traction because polycultures diversify silage cropping systems and can increase the nutritional quality of silage compared with maize monocultures. However, it remains unclear under which conditions these polycultures provide biomass yields like those of maize monocultures. We compiled paired data from 30 papers (529 records) that reported maize and maize + soy yields for silage. Using random forest, we created two models to investigate the factors determining yield and the yield differential with respect to maize monocultures. We found that the most important variables in determining the polyculture yield were the maize proportion in the mixture and year, where year represents mostly technology trends. Precipitation and temperature remain pivotal, with yields stabilizing when yearly precipitation exceeds 100 cm and average temperature exceeds 15 °C. Maize + soy polycultures may produce similarly to maize monocultures if the maize density is at least 5.3 plants m−2. This signals that whereas biomass production in polycultures is maize‐driven, maize stands can be supplemented with soy or with other suitable companion crops without sacrificing yield, perhaps capturing additional production and ecosystem benefits. Research on polycultures for silage production should focus on economical ways of planting mixtures and on suitable maize companions for each region.

Akley, Edwin K.; Rice, Charles W.; Adotey, Nutifafa; Ampim, Peter A. Y.; Vara Prasad, P. V.; Owusu Danquah, Eric; Denwar, Nicholas N.

doi: 10.1002/agj2.21037pmid: N/A

The persistence of inoculants from year to year in soybean [Glycine max (L.) Merr.] cultivation and the residual benefits in soybean production are pertinent to adopting such practices in sub‐Saharan Africa countries such as Ghana. A study was conducted to determine the residual effect of commercial rhizobium inoculants on soybean and selected soil health parameters after three cropping seasons. The experimental design was a split‐plot. The main plot consisted of three soybean cultivars (Jenguma, Afayak, and Songda), and the subplot comprised of three peat‐based commercial bradyrhizobium inoculants (Biofix, Legumefix, and NoduMax) and an uninoculated control. Assessments were made on nodulation, shoot dry matter (DM), grain yield, grain total N uptake, permanganate‐oxidizable carbon (POXC), soil pH, and potentially mineralizable C. Among the soybean cultivars, Afayak produced greater nodule mass on the lateral root and the whole root system compared with the other cultivars. Jenguma and Afayak yielded greater shoot DM relative to Songda. Regarding the inoculants, Biofix increased nodule mass on the lateral root and the whole root system compared with the control. Biofix and NoduMax produced superior grain yield relative to the control. Biofix also produced greater grain yield than Legumefix. A superior pod harvest index and an improved grain total N uptake were produced by Biofix compared with Legumefix and the control. Commercial inoculants enhanced POXC availability at harvest, whereas potentially mineralizable C declined with inoculation treatments. Commercial inoculants (Biofix and NoduMax) enhanced nodulation, grain yield, and selected soil health indicators 3 yr after inoculation.

Strock, Jeffrey S.; Johnson, Jane M. F.; Tollefson, David; Ranaivoson, Andry

doi: 10.1002/agj2.21045pmid: N/A

Changes to land management over the last 150 years, primarily the conversion of perennial grasslands to agricultural production dominated by annual row crops, have greatly changed soil properties and reduced the soil's ability to infiltrate and store water in the soil profile. Direct near‐term response at the time of conversion of an uncultivated remnant prairie to row crops is rare, especially responses that include repeated measurements on the same parcel of land and resampling of soils to a depth of 1 m to document rapid changes in soil organic carbon, nitrogen, and selected soil physical properties related to hydraulic properties. The objective of this research was to measure changes in soil chemical and physical properties after the conversion of perennial grassland to annual row‐crop production. A before‐and‐after approach was used to compare soil properties from a 0.31‐ha field in southwest Minnesota. Cultivation resulted in a negative shift in soil properties. Two years postcultivation, there was an overall reduction in soil organic carbon of 18.6 Mg ha−1 for the 0–1.0 m soil profile. Infiltration rates and soil sorptivity exhibited significant decreases following cultivation. The average decrease in the mean postcultivation infiltration and sorptivity rates were 0.30 mm s−1 and 0.12 mm s−0.5, respectively. Bulk density increased on average by 0.10 Mg m−3 between 0–0.2 m and 0.14 Mg m−3 between 0.2–1.0 m. This work provided a rare glimpse of the vast shift in soil properties, which occurred when the plow ripped through virgin prairie decades ago during the massive expansion of agriculture.

Carvalho, Geovany Macêdo; Brito, Liziane de Figueiredo; Coelho, Larissa de Melo; Cardoso, Abmael da Silva; Messana, Juliana Duarte; Colovate, Paulo Henrique Detogni; Ganga, Maria Júlia Generoso; Cruz, Mara Cristina Pessôa da; Malheiros, Euclides Braga; Berchielli, Telma Teresinha

Matcham, Emma G.; Matias, Filipe; Luck, Brian D.; Conley, Shawn P.

doi: 10.1002/agj2.21055pmid: N/A

Cleaning yield monitor observations to remove erroneous points can improve the accuracy of yield estimates used for farm record keeping or on‐farm research data collection, but current practices are time‐intensive and cumbersome. cleanRfield is an open‐source R package to improve the efficiency of processing spatial agricultural data such as yield maps. Compared with current standard yield monitor data cleaning solutions, cleanRfield can read and interpret a broader range of input data formats. Other key features of cleanRfield include automatic field boundary delineation and batch processing of data from multiple fields. In this Scientific Note, we overview functions within the cleanRfield package and introduce an integrative pipeline to evaluate and visualize yield monitor data. The package is being distributed under the GNU General Public License 2, and a more detailed tutorial including downloading instructions is available at https://github.com/filipematias23/cleanRfield.

Prudente Junior, Amauri Cassio; Vianna, Murilo S.; Williams, Karina; Galdos, Marcelo V.; Marin, Fábio R.

doi: 10.1002/agj2.21066pmid: N/A

Maize (Zea mays L.) is a prominent Brazilian commodity, being the second largest crop produced and fifth exported product by the country. Due to its importance for the agricultural sector, there is a concern about the effect of climate change on the crop. Process‐based models are valuable tools to evaluate the effects of climate on crop yields. The Joint UK Land Environment Simulator (JULES) is a land‐surface model that can be run with an integrated crop model parameterization. The resulting model (JULES‐crop) thus integrates crop physiology principles with the complexity of atmosphere–biosphere coupling. It has been shown to be a valuable tool for large‐scale simulations of crop yields as a function of environmental and management variables. In this study, we calibrated JULES‐crop using a robust experimental dataset collected for summer and off‐season maize fields across Brazil. A targeted local sensitivity analysis was performed to detect parameters of major importance during the calibration process. After calibration, the model was able to satisfactorily simulate both season and off‐season cultivars. Modeling efficiency (EF) was high for leaf area index (EF = .73 and .71, respectively, for summer season and off‐season datasets), crop height (EF = .89), and grain dry mass (EF = .61 and .89, respectively, for summer season and off‐season datasets). The model showed a lower accuracy for simulating leaf dry mass in summer season cultivars (EF = .39) and soil moisture (EF = .44), demonstrating the necessity of further improvements including additional parametrizations of the rainfed conditions.